{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "02cfa8ae",
   "metadata": {},
   "source": [
    "# Capstone Project - Wine Quality (White)\n",
    "#### Rogelio J. Montemayor\n",
    "## 1. Introduction\n",
    "The goal of this project is to create a model that estimates the subjective rating of a wine as graded by experts, using as inputs (features) the physicochemical properties of the wine.\n",
    "\n",
    "There are two datasets, one for white wine (4,898 wines) and one for red (1,599 wines). They are all variants of the Portuguese \"Vinho Verde\" wine.\n",
    "\n",
    "This dataset could be used as a classification or a regression problem. I will be doing regression. Since wine properties are very different for white and red wines, I will be doing a separate analysis for each type of wine. I will be only doing the white wine dataset in this notebook. There is another notebook for the red wine.\n",
    "\n",
    "We found that it is possible to achieve reasonably accurate predictions of the rating by using a Random Forest approach. Using this data based approach can help wine producers supplement their traditional tasting methods.\n",
    "\n",
    "### 1.1 Acknowledgements\n",
    "\n",
    "#### This project was made possible by the generosity of: \n",
    "\n",
    "P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis.   \n",
    "\"Modeling wine preferences by data mining from physicochemical properties.\"  \n",
    "In Decision Support Systems, Elsevier, 47(4):547-553. ISSN: 0167-9236.\n",
    "\n",
    "#### Available at:  \n",
    "@Elsevier: http://dx.doi.org/10.1016/j.dss.2009.05.016    \n",
    "Pre-press (pdf): http://www3.dsi.uminho.pt/pcortez/winequality09.pdf  \n",
    "bib: http://www3.dsi.uminho.pt/pcortez/dss09.bib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aec99197",
   "metadata": {},
   "source": [
    "## 2. Library Imports\n",
    "\n",
    "#### The first step is to import the libraries we are going to need in the project.\n",
    "* basic libraries\n",
    "* preprocessing libraries\n",
    "* model selection libraries\n",
    "* finally, import the models we will use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f9d13255",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import basic libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set_style('darkgrid')\n",
    "import pickle\n",
    "\n",
    "# import pipeline and preprocessing libraries\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# import model selection and metrics libraries\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import r2_score, mean_squared_error\n",
    "\n",
    "# import the different models we are going to use\n",
    "from sklearn.linear_model import Lasso, Ridge, ElasticNet\n",
    "from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b9c7f48",
   "metadata": {},
   "source": [
    "## 3. Exploratory Analysis\n",
    "\n",
    "#### Initial exploration\n",
    "We will explore the dataset, to get a feel for it, see what needs to be fixed, get a sense of the features, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e8e03225",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read the datasets\n",
    "df = pd.read_csv('winequality-white.csv', sep=';')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06407a80",
   "metadata": {},
   "source": [
    "Let's look at the first five lines of our data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8a8438b7",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0010</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.9951</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "0            7.0              0.27         0.36            20.7      0.045   \n",
       "1            6.3              0.30         0.34             1.6      0.049   \n",
       "2            8.1              0.28         0.40             6.9      0.050   \n",
       "3            7.2              0.23         0.32             8.5      0.058   \n",
       "4            7.2              0.23         0.32             8.5      0.058   \n",
       "\n",
       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                 45.0                 170.0   1.0010  3.00       0.45   \n",
       "1                 14.0                 132.0   0.9940  3.30       0.49   \n",
       "2                 30.0                  97.0   0.9951  3.26       0.44   \n",
       "3                 47.0                 186.0   0.9956  3.19       0.40   \n",
       "4                 47.0                 186.0   0.9956  3.19       0.40   \n",
       "\n",
       "   alcohol  quality  \n",
       "0      8.8        6  \n",
       "1      9.5        6  \n",
       "2     10.1        6  \n",
       "3      9.9        6  \n",
       "4      9.9        6  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cef92bd",
   "metadata": {},
   "source": [
    "And the last 5 as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "209fb104",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4893</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.039</td>\n",
       "      <td>24.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>0.99114</td>\n",
       "      <td>3.27</td>\n",
       "      <td>0.50</td>\n",
       "      <td>11.2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4894</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.36</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.047</td>\n",
       "      <td>57.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.99490</td>\n",
       "      <td>3.15</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4895</th>\n",
       "      <td>6.5</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.041</td>\n",
       "      <td>30.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>0.99254</td>\n",
       "      <td>2.99</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4896</th>\n",
       "      <td>5.5</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.022</td>\n",
       "      <td>20.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.98869</td>\n",
       "      <td>3.34</td>\n",
       "      <td>0.38</td>\n",
       "      <td>12.8</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4897</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.020</td>\n",
       "      <td>22.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0.98941</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.32</td>\n",
       "      <td>11.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "4893            6.2              0.21         0.29             1.6      0.039   \n",
       "4894            6.6              0.32         0.36             8.0      0.047   \n",
       "4895            6.5              0.24         0.19             1.2      0.041   \n",
       "4896            5.5              0.29         0.30             1.1      0.022   \n",
       "4897            6.0              0.21         0.38             0.8      0.020   \n",
       "\n",
       "      free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "4893                 24.0                  92.0  0.99114  3.27       0.50   \n",
       "4894                 57.0                 168.0  0.99490  3.15       0.46   \n",
       "4895                 30.0                 111.0  0.99254  2.99       0.46   \n",
       "4896                 20.0                 110.0  0.98869  3.34       0.38   \n",
       "4897                 22.0                  98.0  0.98941  3.26       0.32   \n",
       "\n",
       "      alcohol  quality  \n",
       "4893     11.2        6  \n",
       "4894      9.6        5  \n",
       "4895      9.4        6  \n",
       "4896     12.8        7  \n",
       "4897     11.8        6  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.tail())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3be7ea8",
   "metadata": {},
   "source": [
    "We can also verify that the dataset has 1,599 wines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cfb4e201",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4898, 12)\n"
     ]
    }
   ],
   "source": [
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf955b6e",
   "metadata": {},
   "source": [
    "Let's now take a look at the data type of the variables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c772edf6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fixed acidity           float64\n",
      "volatile acidity        float64\n",
      "citric acid             float64\n",
      "residual sugar          float64\n",
      "chlorides               float64\n",
      "free sulfur dioxide     float64\n",
      "total sulfur dioxide    float64\n",
      "density                 float64\n",
      "pH                      float64\n",
      "sulphates               float64\n",
      "alcohol                 float64\n",
      "quality                   int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f082e756",
   "metadata": {},
   "source": [
    "We can see the basic properties of the different features, they all seem to make sense. Since the features are have different ranges of values we will need to do some standardization before using the machine learning models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8727a2ce",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "      <td>4898.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.854788</td>\n",
       "      <td>0.278241</td>\n",
       "      <td>0.334192</td>\n",
       "      <td>6.391415</td>\n",
       "      <td>0.045772</td>\n",
       "      <td>35.308085</td>\n",
       "      <td>138.360657</td>\n",
       "      <td>0.994027</td>\n",
       "      <td>3.188267</td>\n",
       "      <td>0.489847</td>\n",
       "      <td>10.514267</td>\n",
       "      <td>5.877909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.843868</td>\n",
       "      <td>0.100795</td>\n",
       "      <td>0.121020</td>\n",
       "      <td>5.072058</td>\n",
       "      <td>0.021848</td>\n",
       "      <td>17.007137</td>\n",
       "      <td>42.498065</td>\n",
       "      <td>0.002991</td>\n",
       "      <td>0.151001</td>\n",
       "      <td>0.114126</td>\n",
       "      <td>1.230621</td>\n",
       "      <td>0.885639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.009000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0.987110</td>\n",
       "      <td>2.720000</td>\n",
       "      <td>0.220000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.300000</td>\n",
       "      <td>0.210000</td>\n",
       "      <td>0.270000</td>\n",
       "      <td>1.700000</td>\n",
       "      <td>0.036000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>0.991723</td>\n",
       "      <td>3.090000</td>\n",
       "      <td>0.410000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.800000</td>\n",
       "      <td>0.260000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>5.200000</td>\n",
       "      <td>0.043000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>134.000000</td>\n",
       "      <td>0.993740</td>\n",
       "      <td>3.180000</td>\n",
       "      <td>0.470000</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.300000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>0.390000</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>0.996100</td>\n",
       "      <td>3.280000</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>11.400000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>14.200000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>1.660000</td>\n",
       "      <td>65.800000</td>\n",
       "      <td>0.346000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>1.038980</td>\n",
       "      <td>3.820000</td>\n",
       "      <td>1.080000</td>\n",
       "      <td>14.200000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
       "count    4898.000000       4898.000000  4898.000000     4898.000000   \n",
       "mean        6.854788          0.278241     0.334192        6.391415   \n",
       "std         0.843868          0.100795     0.121020        5.072058   \n",
       "min         3.800000          0.080000     0.000000        0.600000   \n",
       "25%         6.300000          0.210000     0.270000        1.700000   \n",
       "50%         6.800000          0.260000     0.320000        5.200000   \n",
       "75%         7.300000          0.320000     0.390000        9.900000   \n",
       "max        14.200000          1.100000     1.660000       65.800000   \n",
       "\n",
       "         chlorides  free sulfur dioxide  total sulfur dioxide      density  \\\n",
       "count  4898.000000          4898.000000           4898.000000  4898.000000   \n",
       "mean      0.045772            35.308085            138.360657     0.994027   \n",
       "std       0.021848            17.007137             42.498065     0.002991   \n",
       "min       0.009000             2.000000              9.000000     0.987110   \n",
       "25%       0.036000            23.000000            108.000000     0.991723   \n",
       "50%       0.043000            34.000000            134.000000     0.993740   \n",
       "75%       0.050000            46.000000            167.000000     0.996100   \n",
       "max       0.346000           289.000000            440.000000     1.038980   \n",
       "\n",
       "                pH    sulphates      alcohol      quality  \n",
       "count  4898.000000  4898.000000  4898.000000  4898.000000  \n",
       "mean      3.188267     0.489847    10.514267     5.877909  \n",
       "std       0.151001     0.114126     1.230621     0.885639  \n",
       "min       2.720000     0.220000     8.000000     3.000000  \n",
       "25%       3.090000     0.410000     9.500000     5.000000  \n",
       "50%       3.180000     0.470000    10.400000     6.000000  \n",
       "75%       3.280000     0.550000    11.400000     6.000000  \n",
       "max       3.820000     1.080000    14.200000     9.000000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3769f9e",
   "metadata": {},
   "source": [
    "It is good to see there are no missing values in our data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f3e2255d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fixed acidity           0\n",
      "volatile acidity        0\n",
      "citric acid             0\n",
      "residual sugar          0\n",
      "chlorides               0\n",
      "free sulfur dioxide     0\n",
      "total sulfur dioxide    0\n",
      "density                 0\n",
      "pH                      0\n",
      "sulphates               0\n",
      "alcohol                 0\n",
      "quality                 0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8a8fab6",
   "metadata": {},
   "source": [
    "#### Visual Exploration\n",
    "Let's take a look at the distribution of the features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a183071f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist(figsize=(14,14), xrot=-45, column=sorted(df.columns))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "780345c3",
   "metadata": {},
   "source": [
    "#### Relationship of target variable with the features\n",
    "We can visualize the distribution of our target variable vs the other features to look for patterns that could help us in our analysis.\n",
    "\n",
    "The violin plots can also help us look for outliers in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "80ab21ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "columns = list(df.columns)\n",
    "columns.remove('quality')\n",
    "for col in columns:\n",
    "    sns.violinplot(x=\"quality\", y=col, data=df)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b89b6f28",
   "metadata": {},
   "source": [
    "We can also take a look at the correlations between the variables with the help of a heatmap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "571a8667",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate correlations\n",
    "correlations = df.corr()\n",
    "\n",
    "# create a mask to see only the bottom triangle\n",
    "mask = np.zeros_like(correlations)\n",
    "mask[np.triu_indices_from(mask)] = 1\n",
    "\n",
    "# crate the heatmap\n",
    "sns.set_style('white')\n",
    "plt.figure(figsize=(9,8))\n",
    "sns.heatmap(correlations * 100,\n",
    "            cmap='RdBu_r',\n",
    "            annot=True,\n",
    "            fmt='.0f',\n",
    "            mask=mask,\n",
    "            cbar=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1db39e0",
   "metadata": {},
   "source": [
    "The highest correlation is between _density_ and _residual sugar_. The second highest correlation is between _total sulfur dioxide_ and _free sulfur dioxide_ which makes sense.\n",
    "\n",
    "Quality, our target variable, has its highest correlation with _alcohol_and _density_ but neither is that high.\n",
    "\n",
    "#### Additional Visual Exploration\n",
    "With this correlation information, we can perform some additional visual exploration.\n",
    "\n",
    "First, let's explore our target variable with the two features that it has the highest correlation: _alcohol_ and _density_:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cbc8ca20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=\"quality\", y=\"alcohol\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "07e5cdbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=\"quality\", y=\"density\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94351543",
   "metadata": {},
   "source": [
    "#### We can also inspect pairs of highly correlated variables\n",
    "\n",
    "Let's visualize 3 variable pairs with high correlation:\n",
    "* _density_ vs _residual sugar_\n",
    "* _density_ vs _alcohol_\n",
    "* _total sulfur dioxide_ vs _free sulfur dioxide_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fcccb515",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=\"density\", y=\"residual sugar\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a554068e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=\"density\", y=\"alcohol\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "49dab5cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=\"total sulfur dioxide\", y=\"free sulfur dioxide\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f24073f0",
   "metadata": {},
   "source": [
    "## 4. Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "115ed259",
   "metadata": {},
   "source": [
    "Look for duplicated rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b43aeb6e",
   "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.99560</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.99510</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.100000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.00100</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.800000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.99400</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>6.2</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.029</td>\n",
       "      <td>29.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.98920</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.39</td>\n",
       "      <td>12.800000</td>\n",
       "      <td>8</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4828</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.35</td>\n",
       "      <td>10.3</td>\n",
       "      <td>0.042</td>\n",
       "      <td>54.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.99670</td>\n",
       "      <td>3.23</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4850</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.35</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.048</td>\n",
       "      <td>67.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>0.99146</td>\n",
       "      <td>3.05</td>\n",
       "      <td>0.56</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4851</th>\n",
       "      <td>6.4</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.44</td>\n",
       "      <td>8.9</td>\n",
       "      <td>0.055</td>\n",
       "      <td>52.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>0.99488</td>\n",
       "      <td>3.10</td>\n",
       "      <td>0.48</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4856</th>\n",
       "      <td>7.1</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.39</td>\n",
       "      <td>13.7</td>\n",
       "      <td>0.058</td>\n",
       "      <td>26.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>0.99755</td>\n",
       "      <td>2.90</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4880</th>\n",
       "      <td>6.6</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.40</td>\n",
       "      <td>8.1</td>\n",
       "      <td>0.046</td>\n",
       "      <td>68.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.99494</td>\n",
       "      <td>3.15</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.533333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>937 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "4               7.2              0.23         0.32             8.5      0.058   \n",
       "5               8.1              0.28         0.40             6.9      0.050   \n",
       "7               7.0              0.27         0.36            20.7      0.045   \n",
       "8               6.3              0.30         0.34             1.6      0.049   \n",
       "20              6.2              0.66         0.48             1.2      0.029   \n",
       "...             ...               ...          ...             ...        ...   \n",
       "4828            6.4              0.23         0.35            10.3      0.042   \n",
       "4850            7.0              0.36         0.35             2.5      0.048   \n",
       "4851            6.4              0.33         0.44             8.9      0.055   \n",
       "4856            7.1              0.23         0.39            13.7      0.058   \n",
       "4880            6.6              0.34         0.40             8.1      0.046   \n",
       "\n",
       "      free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "4                    47.0                 186.0  0.99560  3.19       0.40   \n",
       "5                    30.0                  97.0  0.99510  3.26       0.44   \n",
       "7                    45.0                 170.0  1.00100  3.00       0.45   \n",
       "8                    14.0                 132.0  0.99400  3.30       0.49   \n",
       "20                   29.0                  75.0  0.98920  3.33       0.39   \n",
       "...                   ...                   ...      ...   ...        ...   \n",
       "4828                 54.0                 140.0  0.99670  3.23       0.47   \n",
       "4850                 67.0                 161.0  0.99146  3.05       0.56   \n",
       "4851                 52.0                 164.0  0.99488  3.10       0.48   \n",
       "4856                 26.0                 172.0  0.99755  2.90       0.46   \n",
       "4880                 68.0                 170.0  0.99494  3.15       0.50   \n",
       "\n",
       "        alcohol  quality  \n",
       "4      9.900000        6  \n",
       "5     10.100000        6  \n",
       "7      8.800000        6  \n",
       "8      9.500000        6  \n",
       "20    12.800000        8  \n",
       "...         ...      ...  \n",
       "4828   9.200000        5  \n",
       "4850  11.100000        6  \n",
       "4851   9.600000        5  \n",
       "4856   9.000000        6  \n",
       "4880   9.533333        6  \n",
       "\n",
       "[937 rows x 12 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "duplicated_rows = df[df.duplicated()]\n",
    "display(duplicated_rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "455c2c07",
   "metadata": {},
   "source": [
    "This seems to be that several wine tasters rated the same wine similarly. We will keep the duplicates for now.\n",
    "\n",
    "From our visual exploration, there does not seem to be other structural errors, outliers or missing data that needs to be fixed for now.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "275f9ecd",
   "metadata": {},
   "source": [
    "## 5. Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdb91fdb",
   "metadata": {},
   "source": [
    "Without further domain knowledge, it is hard to choose interaction features or indicator features that could help us engineer new features. \n",
    "\n",
    "We will leave the data as is for now."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "044e59cc",
   "metadata": {},
   "source": [
    "Let's create our **analytical base table (ABT)**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "31617205",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('analytical_base_table.csv', index=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9cf81d8",
   "metadata": {},
   "source": [
    "## 6. Algorithm Selection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a8bfc3c",
   "metadata": {},
   "source": [
    "#### Regression problem\n",
    "We can treat this problem as a classification problem with 7 classes (all wines have a score of either 3, 4, 5, 6, 7, 8, or 9). \n",
    "\n",
    "We could also see it as a regression problem since the model can predict a continuous value and it will correctly represent the relative quality of the wine. That is, if our model predicts a wine to have quality 3.1 and the true value was 3, we can see it as good prediction.  \n",
    "I believe it is a better approach to model the problem as a regression problem. \n",
    "\n",
    "#### Algorithms to test\n",
    "We will use the following algorithms and see which one performs best:\n",
    "\n",
    "* Lasso Linear Regression\n",
    "* Ridge Linear Regression\n",
    "* ElasticNet Linear Regression\n",
    "* Random Forest Regressor\n",
    "* Gradient Boosting Regressor\n",
    "\n",
    "I chose the first three because the regularization they provide normally improves the linear regression, especially in a case like this where there linear regression has many variables to fit.\n",
    "\n",
    "Random Forest and Gradient Boosting Regressors are normally good choices in regression problems. \n",
    "\n",
    "#### Hyperparameter tuning\n",
    "For Lasso and Ridge we will tune the alpha parameter. For ElasticNet we will focus on the alpha and the l1 ratio.\n",
    "\n",
    "For the Random Forest Regressor we will focus on the number of trees and the number of features to use per tree.\n",
    "\n",
    "For the Gradient Boosting Regressor we will tune the number of estimators, the learning rate and the maximum depth."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55ba15a9",
   "metadata": {},
   "source": [
    "## 7. Model Training"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32be0998",
   "metadata": {},
   "source": [
    "Now that we have selected our algorithms, we can start to train them on the white wine data. The first step is to separate the features from our target variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "59b3dab6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load ABT\n",
    "df = pd.read_csv('analytical_base_table.csv')\n",
    "\n",
    "# Create X and y tables\n",
    "y = df.quality\n",
    "X = df.drop('quality', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4105d4df",
   "metadata": {},
   "source": [
    "We can now split our data into train and test data. We will keep 20% for testing and train and select the model on the train split. We also set random_state to 775 for reproducibility."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0f9ef904",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y,\n",
    "                                                   test_size=0.2,\n",
    "                                                   random_state=775)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71122771",
   "metadata": {},
   "source": [
    "From our exploration, we saw that we have different ranges of values in our data. Our models will be better if the data has similar scales, so we will add a scaling step to our pipeline. \n",
    "\n",
    "#### Create pipelines dictionary\n",
    "With this dictionary, we can keep our pipelines for each algorithm in the same place. We will set random_state to 111 for repoducibility."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f453105c",
   "metadata": {},
   "outputs": [],
   "source": [
    "pipelines = {\n",
    "    'lasso' : make_pipeline(StandardScaler(), Lasso(random_state=111)),\n",
    "    'ridge' : make_pipeline(StandardScaler(), Ridge(random_state=111)),\n",
    "    'enet' : make_pipeline(StandardScaler(), ElasticNet(random_state=111)),\n",
    "    'rf' : make_pipeline(StandardScaler(), RandomForestRegressor(random_state=111)),\n",
    "    'gb' : make_pipeline(StandardScaler(), GradientBoostingRegressor(random_state=111)),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1eea92ab",
   "metadata": {},
   "source": [
    "As a sanity check, let's confirm that the pipelines were created:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "915a00db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lasso <class 'sklearn.pipeline.Pipeline'>\n",
      "ridge <class 'sklearn.pipeline.Pipeline'>\n",
      "enet <class 'sklearn.pipeline.Pipeline'>\n",
      "rf <class 'sklearn.pipeline.Pipeline'>\n",
      "gb <class 'sklearn.pipeline.Pipeline'>\n"
     ]
    }
   ],
   "source": [
    "for pipeline in pipelines:\n",
    "    print(pipeline, type(pipelines[pipeline]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f004aafd",
   "metadata": {},
   "source": [
    "#### Create hyperparameters dictionary\n",
    "The next step will be to train our algorithms. We will create a dictionary with the hyperparameters to tune for each algorithm. As an intermediate step, I like to take a look at the tunable parameters for each algorithm so that we can:\n",
    "* get the name of the hyperparameter correctly\n",
    "* make sure not to miss an important hyperparameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fa0fe1e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'memory': None,\n",
       " 'steps': [('standardscaler', StandardScaler()),\n",
       "  ('lasso', Lasso(random_state=111))],\n",
       " 'verbose': False,\n",
       " 'standardscaler': StandardScaler(),\n",
       " 'lasso': Lasso(random_state=111),\n",
       " 'standardscaler__copy': True,\n",
       " 'standardscaler__with_mean': True,\n",
       " 'standardscaler__with_std': True,\n",
       " 'lasso__alpha': 1.0,\n",
       " 'lasso__copy_X': True,\n",
       " 'lasso__fit_intercept': True,\n",
       " 'lasso__max_iter': 1000,\n",
       " 'lasso__normalize': False,\n",
       " 'lasso__positive': False,\n",
       " 'lasso__precompute': False,\n",
       " 'lasso__random_state': 111,\n",
       " 'lasso__selection': 'cyclic',\n",
       " 'lasso__tol': 0.0001,\n",
       " 'lasso__warm_start': False}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'memory': None,\n",
       " 'steps': [('standardscaler', StandardScaler()),\n",
       "  ('ridge', Ridge(random_state=111))],\n",
       " 'verbose': False,\n",
       " 'standardscaler': StandardScaler(),\n",
       " 'ridge': Ridge(random_state=111),\n",
       " 'standardscaler__copy': True,\n",
       " 'standardscaler__with_mean': True,\n",
       " 'standardscaler__with_std': True,\n",
       " 'ridge__alpha': 1.0,\n",
       " 'ridge__copy_X': True,\n",
       " 'ridge__fit_intercept': True,\n",
       " 'ridge__max_iter': None,\n",
       " 'ridge__normalize': False,\n",
       " 'ridge__random_state': 111,\n",
       " 'ridge__solver': 'auto',\n",
       " 'ridge__tol': 0.001}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'memory': None,\n",
       " 'steps': [('standardscaler', StandardScaler()),\n",
       "  ('elasticnet', ElasticNet(random_state=111))],\n",
       " 'verbose': False,\n",
       " 'standardscaler': StandardScaler(),\n",
       " 'elasticnet': ElasticNet(random_state=111),\n",
       " 'standardscaler__copy': True,\n",
       " 'standardscaler__with_mean': True,\n",
       " 'standardscaler__with_std': True,\n",
       " 'elasticnet__alpha': 1.0,\n",
       " 'elasticnet__copy_X': True,\n",
       " 'elasticnet__fit_intercept': True,\n",
       " 'elasticnet__l1_ratio': 0.5,\n",
       " 'elasticnet__max_iter': 1000,\n",
       " 'elasticnet__normalize': False,\n",
       " 'elasticnet__positive': False,\n",
       " 'elasticnet__precompute': False,\n",
       " 'elasticnet__random_state': 111,\n",
       " 'elasticnet__selection': 'cyclic',\n",
       " 'elasticnet__tol': 0.0001,\n",
       " 'elasticnet__warm_start': False}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'memory': None,\n",
       " 'steps': [('standardscaler', StandardScaler()),\n",
       "  ('randomforestregressor', RandomForestRegressor(random_state=111))],\n",
       " 'verbose': False,\n",
       " 'standardscaler': StandardScaler(),\n",
       " 'randomforestregressor': RandomForestRegressor(random_state=111),\n",
       " 'standardscaler__copy': True,\n",
       " 'standardscaler__with_mean': True,\n",
       " 'standardscaler__with_std': True,\n",
       " 'randomforestregressor__bootstrap': True,\n",
       " 'randomforestregressor__ccp_alpha': 0.0,\n",
       " 'randomforestregressor__criterion': 'mse',\n",
       " 'randomforestregressor__max_depth': None,\n",
       " 'randomforestregressor__max_features': 'auto',\n",
       " 'randomforestregressor__max_leaf_nodes': None,\n",
       " 'randomforestregressor__max_samples': None,\n",
       " 'randomforestregressor__min_impurity_decrease': 0.0,\n",
       " 'randomforestregressor__min_impurity_split': None,\n",
       " 'randomforestregressor__min_samples_leaf': 1,\n",
       " 'randomforestregressor__min_samples_split': 2,\n",
       " 'randomforestregressor__min_weight_fraction_leaf': 0.0,\n",
       " 'randomforestregressor__n_estimators': 100,\n",
       " 'randomforestregressor__n_jobs': None,\n",
       " 'randomforestregressor__oob_score': False,\n",
       " 'randomforestregressor__random_state': 111,\n",
       " 'randomforestregressor__verbose': 0,\n",
       " 'randomforestregressor__warm_start': False}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'memory': None,\n",
       " 'steps': [('standardscaler', StandardScaler()),\n",
       "  ('gradientboostingregressor', GradientBoostingRegressor(random_state=111))],\n",
       " 'verbose': False,\n",
       " 'standardscaler': StandardScaler(),\n",
       " 'gradientboostingregressor': GradientBoostingRegressor(random_state=111),\n",
       " 'standardscaler__copy': True,\n",
       " 'standardscaler__with_mean': True,\n",
       " 'standardscaler__with_std': True,\n",
       " 'gradientboostingregressor__alpha': 0.9,\n",
       " 'gradientboostingregressor__ccp_alpha': 0.0,\n",
       " 'gradientboostingregressor__criterion': 'friedman_mse',\n",
       " 'gradientboostingregressor__init': None,\n",
       " 'gradientboostingregressor__learning_rate': 0.1,\n",
       " 'gradientboostingregressor__loss': 'ls',\n",
       " 'gradientboostingregressor__max_depth': 3,\n",
       " 'gradientboostingregressor__max_features': None,\n",
       " 'gradientboostingregressor__max_leaf_nodes': None,\n",
       " 'gradientboostingregressor__min_impurity_decrease': 0.0,\n",
       " 'gradientboostingregressor__min_impurity_split': None,\n",
       " 'gradientboostingregressor__min_samples_leaf': 1,\n",
       " 'gradientboostingregressor__min_samples_split': 2,\n",
       " 'gradientboostingregressor__min_weight_fraction_leaf': 0.0,\n",
       " 'gradientboostingregressor__n_estimators': 100,\n",
       " 'gradientboostingregressor__n_iter_no_change': None,\n",
       " 'gradientboostingregressor__random_state': 111,\n",
       " 'gradientboostingregressor__subsample': 1.0,\n",
       " 'gradientboostingregressor__tol': 0.0001,\n",
       " 'gradientboostingregressor__validation_fraction': 0.1,\n",
       " 'gradientboostingregressor__verbose': 0,\n",
       " 'gradientboostingregressor__warm_start': False}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for pipeline in pipelines:\n",
    "    display(pipelines[pipeline].get_params())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09987724",
   "metadata": {},
   "source": [
    "After checking, we can now create the hyperparameter grid. First we create a dictionary for each algorithm with the hyperparameters we want to tune and the values to use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f6047124",
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_hyperparameters = {\n",
    "    'lasso__alpha' : [0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 5, 10]\n",
    "}\n",
    "ridge_hyperparameters = {\n",
    "    'ridge__alpha' : [0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 5, 10]\n",
    "}\n",
    "enet_hyperparameters = {\n",
    "    'elasticnet__alpha' : [0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 5, 10],\n",
    "    'elasticnet__l1_ratio' : [0.1, 0.3, 0.5, 0.7, 0.9]\n",
    "}\n",
    "rf_hyperparameters = {\n",
    "    'randomforestregressor__n_estimators' : [100, 200, 300, 400, 500],\n",
    "    'randomforestregressor__max_features' : ['auto', 'sqrt', 0.33]\n",
    "}\n",
    "gb_hyperparameters = {\n",
    "    'gradientboostingregressor__n_estimators' : [100, 200],\n",
    "    'gradientboostingregressor__learning_rate' : [0.05, 0.1, 0.2],\n",
    "    'gradientboostingregressor__max_depth' : [1, 3, 5]\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8920ced6",
   "metadata": {},
   "source": [
    "And to keep everything in one place, we create a dictionary with all the hyperparameter dictionaries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c52d1ade",
   "metadata": {},
   "outputs": [],
   "source": [
    "hyperparameters = {\n",
    "    'lasso' : lasso_hyperparameters,\n",
    "    'ridge' : ridge_hyperparameters,\n",
    "    'enet' : enet_hyperparameters,\n",
    "    'rf' : rf_hyperparameters,  \n",
    "    'gb' : gb_hyperparameters\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54e1e81e",
   "metadata": {},
   "source": [
    "With this setup, we can now loop over our dictionary and train each of our algorithms and tune the hyperparameters all in one step. We will use 10 fold cross-validation for the hyperparameter tuning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ab99ae80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lasso has been fitted\n",
      "ridge has been fitted\n",
      "enet has been fitted\n",
      "rf has been fitted\n",
      "gb has been fitted\n"
     ]
    }
   ],
   "source": [
    "fitted_models = {}\n",
    "\n",
    "for name, pipeline in pipelines.items():\n",
    "    model = GridSearchCV(pipeline, hyperparameters[name], cv=10)\n",
    "    model.fit(X_train, y_train)\n",
    "    fitted_models[name] = model\n",
    "    print(name, 'has been fitted')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "562b055d",
   "metadata": {},
   "source": [
    "#### Choose the best performing algorithm\n",
    "It seems that Random Forest gets the best results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9266c89b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lasso 0.27855099133259004\n",
      "ridge 0.2785310732323244\n",
      "enet 0.27963894991160776\n",
      "rf 0.5417770593072861\n",
      "gb 0.48340324064416196\n"
     ]
    }
   ],
   "source": [
    "for name, model in fitted_models.items():\n",
    "    print(name, model.best_score_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f66bf27d",
   "metadata": {},
   "source": [
    "Let's calculate the R squared error and the Mean Squared error to select the best algorithm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b660e76b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lasso\n",
      "--------\n",
      "R^2: 0.24763868296405078\n",
      "MSE: 0.5974895730410107\n",
      "\n",
      "ridge\n",
      "--------\n",
      "R^2: 0.2491886891065973\n",
      "MSE: 0.596258631886341\n",
      "\n",
      "enet\n",
      "--------\n",
      "R^2: 0.24863075786174593\n",
      "MSE: 0.5967017143438307\n",
      "\n",
      "rf\n",
      "--------\n",
      "R^2: 0.5137982992091297\n",
      "MSE: 0.3861182653061224\n",
      "\n",
      "gb\n",
      "--------\n",
      "R^2: 0.4522951893692222\n",
      "MSE: 0.4349611098368771\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for name, model in fitted_models.items():\n",
    "    pred = model.predict(X_test)\n",
    "    print(name)\n",
    "    print('-'*8)\n",
    "    print(f'R^2: {r2_score(y_test, pred)}')\n",
    "    print(f'MSE: {mean_squared_error(y_test, pred)}')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e475b8c",
   "metadata": {},
   "source": [
    "Random Forest gives us the best R squared and the lowest MSE.\n",
    "\n",
    "We can visualize predicted versus actual values using our trained model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "376e5e3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf_pred = fitted_models['rf'].predict(X_test)\n",
    "plt.scatter(rf_pred, y_test)\n",
    "plt.xlabel('predicted')\n",
    "plt.ylabel('actual')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ef532dd",
   "metadata": {},
   "source": [
    "We can also get a look at the parameters that worked best for this algorithm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6486f099",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('standardscaler', StandardScaler()),\n",
       "                ('randomforestregressor',\n",
       "                 RandomForestRegressor(max_features='sqrt', n_estimators=500,\n",
       "                                       random_state=111))])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fitted_models['rf'].best_estimator_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d18b7f2",
   "metadata": {},
   "source": [
    "#### Save the final model\n",
    "We can now create a pickle file of our best model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "140f2dd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('final_model_white.pkl', 'wb') as f:\n",
    "    pickle.dump(fitted_models['rf'].best_estimator_, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6e80441",
   "metadata": {},
   "source": [
    "## 8. Insights & Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71b27e10",
   "metadata": {},
   "source": [
    "Random forest beat out boosted trees and regularized regression approaches. \n",
    "\n",
    "A mean squared error lower that 0.39 is enough to help winemakers to estimate ratings and supplement their regular testing protocols.\n",
    "\n",
    "This model could be further improved in several ways:\n",
    "* Acquire domain expertise to get more context on the features.\n",
    "* Engineer better features through domain knowledge or even trial and error."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d478ab8e",
   "metadata": {},
   "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": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}