food_recommend.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "</title> Food Recommendation <title>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from IPython.display import display\n",
    "from itertools import combinations\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.inspection import DecisionBoundaryDisplay\n",
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "\n",
    "from scipy.stats import skewnorm\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extract required data from JSON"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('food_datasets/test.json', 'r') as file:\n",
    "    data = json.load(file)\n",
    "\n",
    "#convert JSON data to DataFrame\n",
    "food_list = []\n",
    "for entry in data['all']:\n",
    "    for menu_item in entry['menu']:\n",
    "        for food_item in menu_item['items']:\n",
    "            if 'calories' in food_item['nutrition'] and food_item['nutrition']['calories'] != None:\n",
    "                food = {\n",
    "                    'type': menu_item['category'],\n",
    "                    'name': food_item['name'],\n",
    "                    'calories': float(food_item['nutrition']['calories']),\n",
    "                }\n",
    "                food_list.append(food)\n",
    "\n",
    "\n",
    "# with open('food_datasets/food_samples.json', 'r') as file:\n",
    "#     data = json.load(file)\n",
    "# food_list = []\n",
    "# for category in data:\n",
    "#     for food_item in category['items']:\n",
    "#         if 'calories' in food_item['nutrition'] and food_item['nutrition']['calories'] != None:\n",
    "#             food = {\n",
    "#                 'type': category['category'],\n",
    "#                 'name': food_item['name'],\n",
    "#                 'calories': float(food_item['nutrition']['calories']),\n",
    "#             }\n",
    "#             food_list.append(food)\n",
    "\n",
    "\n",
    "food_df = pd.DataFrame(food_list)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the Food DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>name</th>\n",
       "      <th>calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Entr脙漏es</td>\n",
       "      <td>Beef Harissa Rice Bowl</td>\n",
       "      <td>260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Entr脙漏es</td>\n",
       "      <td>Grilled BBQ Pork Chops</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sides</td>\n",
       "      <td>Baked Potato Wedges</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Pizza</td>\n",
       "      <td>Classic Cheese Pizza</td>\n",
       "      <td>340.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pizza</td>\n",
       "      <td>Onion, Jalapeno &amp; Sausage Pizza</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Pizza</td>\n",
       "      <td>Pepperoni Pizza</td>\n",
       "      <td>370.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Entr脙漏es</td>\n",
       "      <td>Chicken Teriyaki</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sides</td>\n",
       "      <td>Spicy Vegetable Lo Mein</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sides</td>\n",
       "      <td>Brown Rice</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sides</td>\n",
       "      <td>Jasmine Rice</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Hot Sandwiches</td>\n",
       "      <td>Grilled Black Bean Burger</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Hot Sandwiches</td>\n",
       "      <td>Hamburger</td>\n",
       "      <td>320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Hot Sandwiches</td>\n",
       "      <td>Classic Hot Dog</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Hot Sandwiches</td>\n",
       "      <td>Classic Grilled Cheese</td>\n",
       "      <td>320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sides</td>\n",
       "      <td>Crispy Shoestring French Fries</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Protein</td>\n",
       "      <td>American Cheese</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Green Leaf Lettuce</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Sliced Red Onions</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Sliced Tomatoes</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>Dill Pickle Slices</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Entr脙漏es</td>\n",
       "      <td>Grilled Chicken Breast</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Entr脙漏es</td>\n",
       "      <td>Thai Red Curry Bowl</td>\n",
       "      <td>500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Soups</td>\n",
       "      <td>Chicken Noodle Soup</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Soups</td>\n",
       "      <td>Vegetable Bean Soup</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Breads</td>\n",
       "      <td>Dinner Roll</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Cold Beverages</td>\n",
       "      <td>Citrus Water</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Protein</td>\n",
       "      <td>Chopped Hard-Cooked Egg</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Protein</td>\n",
       "      <td>Shredded Cheddar Cheese</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Protein</td>\n",
       "      <td>Sunflower Seeds</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Grains</td>\n",
       "      <td>Croutons</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Black Beans</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Black Olives</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Cantaloupe</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Chopped Fresh Spinach</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Corn</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Cucumbers</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Garbanzo Beans</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Honeydew Melon</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Iceberg Lettuce</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Romaine Lettuce</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Shredded Carrots</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Sliced Beets</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Sliced Green Bell Peppers</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Sliced Red Onions</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Tomato Wedges</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>Balsamic Vinaigrette</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>Creamy Caesar Dressing</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>Lite Italian Dressing</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>Oil &amp; Vinegar</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>Ranch Dressing</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Condiments</td>\n",
       "      <td>1000 Island Dressing</td>\n",
       "      <td>220.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               type                             name  calories\n",
       "0          Entr脙漏es           Beef Harissa Rice Bowl     260.0\n",
       "1          Entr脙漏es           Grilled BBQ Pork Chops     180.0\n",
       "2             Sides              Baked Potato Wedges      90.0\n",
       "3             Pizza             Classic Cheese Pizza     340.0\n",
       "4             Pizza  Onion, Jalapeno & Sausage Pizza     350.0\n",
       "5             Pizza                  Pepperoni Pizza     370.0\n",
       "6          Entr脙漏es                 Chicken Teriyaki     130.0\n",
       "7             Sides          Spicy Vegetable Lo Mein     180.0\n",
       "8             Sides                       Brown Rice     110.0\n",
       "9             Sides                     Jasmine Rice     130.0\n",
       "10  Hot Sandwiches         Grilled Black Bean Burger     250.0\n",
       "11  Hot Sandwiches                         Hamburger     320.0\n",
       "12  Hot Sandwiches                   Classic Hot Dog     300.0\n",
       "13  Hot Sandwiches            Classic Grilled Cheese     320.0\n",
       "14            Sides   Crispy Shoestring French Fries     110.0\n",
       "15          Protein                  American Cheese      45.0\n",
       "16           Salads               Green Leaf Lettuce       5.0\n",
       "17           Salads                Sliced Red Onions      10.0\n",
       "18           Salads                  Sliced Tomatoes      15.0\n",
       "19       Condiments               Dill Pickle Slices      10.0\n",
       "20         Entr脙漏es           Grilled Chicken Breast     160.0\n",
       "21         Entr脙漏es              Thai Red Curry Bowl     500.0\n",
       "22            Soups              Chicken Noodle Soup      90.0\n",
       "23            Soups              Vegetable Bean Soup      90.0\n",
       "24           Breads                      Dinner Roll      60.0\n",
       "25   Cold Beverages                     Citrus Water       5.0\n",
       "26          Protein          Chopped Hard-Cooked Egg      70.0\n",
       "27          Protein          Shredded Cheddar Cheese     110.0\n",
       "28          Protein                  Sunflower Seeds     100.0\n",
       "29           Grains                         Croutons      60.0\n",
       "30           Salads                      Black Beans      50.0\n",
       "31           Salads                     Black Olives      60.0\n",
       "32           Salads                       Cantaloupe      25.0\n",
       "33           Salads            Chopped Fresh Spinach       5.0\n",
       "34           Salads                             Corn      35.0\n",
       "35           Salads                        Cucumbers      10.0\n",
       "36           Salads                   Garbanzo Beans      60.0\n",
       "37           Salads                   Honeydew Melon      25.0\n",
       "38           Salads                  Iceberg Lettuce      10.0\n",
       "39           Salads                  Romaine Lettuce       5.0\n",
       "40           Salads                 Shredded Carrots      15.0\n",
       "41           Salads                     Sliced Beets      10.0\n",
       "42           Salads        Sliced Green Bell Peppers      10.0\n",
       "43           Salads                Sliced Red Onions      10.0\n",
       "44           Salads                    Tomato Wedges      15.0\n",
       "45       Condiments             Balsamic Vinaigrette      60.0\n",
       "46       Condiments           Creamy Caesar Dressing     140.0\n",
       "47       Condiments            Lite Italian Dressing      40.0\n",
       "48       Condiments                    Oil & Vinegar     180.0\n",
       "49       Condiments                   Ranch Dressing     100.0\n",
       "50       Condiments             1000 Island Dressing     220.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(food_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [],
   "source": [
    "le = LabelEncoder()\n",
    "food_df['type'] = le.fit_transform(food_df['type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>name</th>\n",
       "      <th>calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>Beef Harissa Rice Bowl</td>\n",
       "      <td>260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>Grilled BBQ Pork Chops</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>Baked Potato Wedges</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>Classic Cheese Pizza</td>\n",
       "      <td>340.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>Onion, Jalapeno &amp; Sausage Pizza</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Pepperoni Pizza</td>\n",
       "      <td>370.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3</td>\n",
       "      <td>Chicken Teriyaki</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9</td>\n",
       "      <td>Spicy Vegetable Lo Mein</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Brown Rice</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Jasmine Rice</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5</td>\n",
       "      <td>Grilled Black Bean Burger</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5</td>\n",
       "      <td>Hamburger</td>\n",
       "      <td>320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5</td>\n",
       "      <td>Classic Hot Dog</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>5</td>\n",
       "      <td>Classic Grilled Cheese</td>\n",
       "      <td>320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>9</td>\n",
       "      <td>Crispy Shoestring French Fries</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7</td>\n",
       "      <td>American Cheese</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8</td>\n",
       "      <td>Green Leaf Lettuce</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>8</td>\n",
       "      <td>Sliced Red Onions</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>8</td>\n",
       "      <td>Sliced Tomatoes</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2</td>\n",
       "      <td>Dill Pickle Slices</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>3</td>\n",
       "      <td>Grilled Chicken Breast</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3</td>\n",
       "      <td>Thai Red Curry Bowl</td>\n",
       "      <td>500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10</td>\n",
       "      <td>Chicken Noodle Soup</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10</td>\n",
       "      <td>Vegetable Bean Soup</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>Dinner Roll</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>Citrus Water</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7</td>\n",
       "      <td>Chopped Hard-Cooked Egg</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7</td>\n",
       "      <td>Shredded Cheddar Cheese</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>7</td>\n",
       "      <td>Sunflower Seeds</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>4</td>\n",
       "      <td>Croutons</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>8</td>\n",
       "      <td>Black Beans</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>8</td>\n",
       "      <td>Black Olives</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>8</td>\n",
       "      <td>Cantaloupe</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>8</td>\n",
       "      <td>Chopped Fresh Spinach</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>8</td>\n",
       "      <td>Corn</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>8</td>\n",
       "      <td>Cucumbers</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>8</td>\n",
       "      <td>Garbanzo Beans</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>8</td>\n",
       "      <td>Honeydew Melon</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>8</td>\n",
       "      <td>Iceberg Lettuce</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>8</td>\n",
       "      <td>Romaine Lettuce</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>8</td>\n",
       "      <td>Shredded Carrots</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>8</td>\n",
       "      <td>Sliced Beets</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>8</td>\n",
       "      <td>Sliced Green Bell Peppers</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>8</td>\n",
       "      <td>Sliced Red Onions</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>8</td>\n",
       "      <td>Tomato Wedges</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2</td>\n",
       "      <td>Balsamic Vinaigrette</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2</td>\n",
       "      <td>Creamy Caesar Dressing</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2</td>\n",
       "      <td>Lite Italian Dressing</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2</td>\n",
       "      <td>Oil &amp; Vinegar</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2</td>\n",
       "      <td>Ranch Dressing</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2</td>\n",
       "      <td>1000 Island Dressing</td>\n",
       "      <td>220.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    type                             name  calories\n",
       "0      3           Beef Harissa Rice Bowl     260.0\n",
       "1      3           Grilled BBQ Pork Chops     180.0\n",
       "2      9              Baked Potato Wedges      90.0\n",
       "3      6             Classic Cheese Pizza     340.0\n",
       "4      6  Onion, Jalapeno & Sausage Pizza     350.0\n",
       "5      6                  Pepperoni Pizza     370.0\n",
       "6      3                 Chicken Teriyaki     130.0\n",
       "7      9          Spicy Vegetable Lo Mein     180.0\n",
       "8      9                       Brown Rice     110.0\n",
       "9      9                     Jasmine Rice     130.0\n",
       "10     5        Grilled Black Bean Burger     250.0\n",
       "11     5                        Hamburger     320.0\n",
       "12     5                  Classic Hot Dog     300.0\n",
       "13     5           Classic Grilled Cheese     320.0\n",
       "14     9   Crispy Shoestring French Fries     110.0\n",
       "15     7                  American Cheese      45.0\n",
       "16     8               Green Leaf Lettuce       5.0\n",
       "17     8                Sliced Red Onions      10.0\n",
       "18     8                  Sliced Tomatoes      15.0\n",
       "19     2               Dill Pickle Slices      10.0\n",
       "20     3           Grilled Chicken Breast     160.0\n",
       "21     3              Thai Red Curry Bowl     500.0\n",
       "22    10              Chicken Noodle Soup      90.0\n",
       "23    10              Vegetable Bean Soup      90.0\n",
       "24     0                      Dinner Roll      60.0\n",
       "25     1                     Citrus Water       5.0\n",
       "26     7          Chopped Hard-Cooked Egg      70.0\n",
       "27     7          Shredded Cheddar Cheese     110.0\n",
       "28     7                  Sunflower Seeds     100.0\n",
       "29     4                         Croutons      60.0\n",
       "30     8                      Black Beans      50.0\n",
       "31     8                     Black Olives      60.0\n",
       "32     8                       Cantaloupe      25.0\n",
       "33     8            Chopped Fresh Spinach       5.0\n",
       "34     8                             Corn      35.0\n",
       "35     8                        Cucumbers      10.0\n",
       "36     8                   Garbanzo Beans      60.0\n",
       "37     8                   Honeydew Melon      25.0\n",
       "38     8                  Iceberg Lettuce      10.0\n",
       "39     8                  Romaine Lettuce       5.0\n",
       "40     8                 Shredded Carrots      15.0\n",
       "41     8                     Sliced Beets      10.0\n",
       "42     8        Sliced Green Bell Peppers      10.0\n",
       "43     8                Sliced Red Onions      10.0\n",
       "44     8                    Tomato Wedges      15.0\n",
       "45     2             Balsamic Vinaigrette      60.0\n",
       "46     2           Creamy Caesar Dressing     140.0\n",
       "47     2            Lite Italian Dressing      40.0\n",
       "48     2                    Oil & Vinegar     180.0\n",
       "49     2                   Ranch Dressing     100.0\n",
       "50     2             1000 Island Dressing     220.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(food_df)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we are recommending based on the user's daily calories intake. Deploying distance method is a good way for predicting the food. In this case, we will use Lp norm where p=2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_foods(input_calories, c=1, debug=False):\n",
    "    \"\"\"\n",
    "    Find k top food that have closest calories to the input calories\n",
    "    : k - number of food in ranked list\n",
    "    : c - size of combinations of food items\n",
    "    \"\"\"\n",
    "    # random split of input calories to get different combinations of food\n",
    "    def skewed_random(a, b, skewness=2, size=None):\n",
    "        # usually one food of a meal should have larger weight (e.g. primary dish)\n",
    "        # therefore we need to skew the splits\n",
    "        loc = (a + b) / 2\n",
    "        scale = (b - a) / 6\n",
    "        a_param = skewness\n",
    "        x = skewnorm.rvs(a_param, loc, scale, size)\n",
    "        return x\n",
    "\n",
    "    # generate c random calories splits (skewed)\n",
    "    cal_seg = []\n",
    "    total_cal = input_calories\n",
    "    for _ in range(c):\n",
    "        cal = skewed_random(0, total_cal, skewness=-2)\n",
    "        cal_seg.append(cal)\n",
    "        total_cal -= cal\n",
    "\n",
    "    if debug == True:\n",
    "        print(cal_seg)\n",
    "\n",
    "    # find c foods closest to the c splits\n",
    "    cdist = [(0, None)] * c\n",
    "    for idx, cal in enumerate(cal_seg):\n",
    "        min_cal = sys.float_info.max\n",
    "        for _, row in food_df[['name', 'calories']].iterrows():\n",
    "            dist = np.abs(cal - row.values[1])\n",
    "            \n",
    "            if dist < min_cal:\n",
    "                cdist[idx] = (dist, row.values[0])\n",
    "                min_cal = dist\n",
    "\n",
    "    return cdist"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's say we want to recommend three foods for the user's lunch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[89.4013616891857, 344.59499543108745, 151.88083959006087]\n",
      "\u001b[1mFood Name\u001b[0m: Baked Potato Wedges \t \u001b[1mDist\u001b[0m: 0.5986383108142945\n",
      "\u001b[1mFood Name\u001b[0m: Classic Cheese Pizza \t \u001b[1mDist\u001b[0m: 4.594995431087455\n",
      "\u001b[1mFood Name\u001b[0m: Grilled Chicken Breast \t \u001b[1mDist\u001b[0m: 8.119160409939127\n"
     ]
    }
   ],
   "source": [
    "lunch_cal = 2200 * 0.4\n",
    "\n",
    "foods = find_foods(input_calories=lunch_cal, c=3, debug=True)\n",
    "\n",
    "for dist, food_name in foods:\n",
    "    print(f\"\\033[1mFood Name\\033[0m: {food_name} \\t \\033[1mDist\\033[0m: {dist}\")\n"
   ]
  }
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