McDonald's.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading the Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from subprocess import check_output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mcdonalds = pd.read_csv('mcdonalds.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Item</th>\n",
       "      <th>Serving Size</th>\n",
       "      <th>Calories</th>\n",
       "      <th>Calories from Fat</th>\n",
       "      <th>Total Fat</th>\n",
       "      <th>Total Fat (% Daily Value)</th>\n",
       "      <th>Saturated Fat</th>\n",
       "      <th>Saturated Fat (% Daily Value)</th>\n",
       "      <th>Trans Fat</th>\n",
       "      <th>...</th>\n",
       "      <th>Carbohydrates</th>\n",
       "      <th>Carbohydrates (% Daily Value)</th>\n",
       "      <th>Dietary Fiber</th>\n",
       "      <th>Dietary Fiber (% Daily Value)</th>\n",
       "      <th>Sugars</th>\n",
       "      <th>Protein</th>\n",
       "      <th>Vitamin A (% Daily Value)</th>\n",
       "      <th>Vitamin C (% Daily Value)</th>\n",
       "      <th>Calcium (% Daily Value)</th>\n",
       "      <th>Iron (% Daily Value)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Egg McMuffin</td>\n",
       "      <td>4.8 oz (136 g)</td>\n",
       "      <td>300</td>\n",
       "      <td>120</td>\n",
       "      <td>13.0</td>\n",
       "      <td>20</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Egg White Delight</td>\n",
       "      <td>4.8 oz (135 g)</td>\n",
       "      <td>250</td>\n",
       "      <td>70</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McMuffin</td>\n",
       "      <td>3.9 oz (111 g)</td>\n",
       "      <td>370</td>\n",
       "      <td>200</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35</td>\n",
       "      <td>8.0</td>\n",
       "      <td>42</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McMuffin with Egg</td>\n",
       "      <td>5.7 oz (161 g)</td>\n",
       "      <td>450</td>\n",
       "      <td>250</td>\n",
       "      <td>28.0</td>\n",
       "      <td>43</td>\n",
       "      <td>10.0</td>\n",
       "      <td>52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McMuffin with Egg Whites</td>\n",
       "      <td>5.7 oz (161 g)</td>\n",
       "      <td>400</td>\n",
       "      <td>210</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35</td>\n",
       "      <td>8.0</td>\n",
       "      <td>42</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Category                              Item    Serving Size  Calories  \\\n",
       "0  Breakfast                      Egg McMuffin  4.8 oz (136 g)       300   \n",
       "1  Breakfast                 Egg White Delight  4.8 oz (135 g)       250   \n",
       "2  Breakfast                  Sausage McMuffin  3.9 oz (111 g)       370   \n",
       "3  Breakfast         Sausage McMuffin with Egg  5.7 oz (161 g)       450   \n",
       "4  Breakfast  Sausage McMuffin with Egg Whites  5.7 oz (161 g)       400   \n",
       "\n",
       "   Calories from Fat  Total Fat  Total Fat (% Daily Value)  Saturated Fat  \\\n",
       "0                120       13.0                         20            5.0   \n",
       "1                 70        8.0                         12            3.0   \n",
       "2                200       23.0                         35            8.0   \n",
       "3                250       28.0                         43           10.0   \n",
       "4                210       23.0                         35            8.0   \n",
       "\n",
       "   Saturated Fat (% Daily Value)  Trans Fat          ...           \\\n",
       "0                             25        0.0          ...            \n",
       "1                             15        0.0          ...            \n",
       "2                             42        0.0          ...            \n",
       "3                             52        0.0          ...            \n",
       "4                             42        0.0          ...            \n",
       "\n",
       "   Carbohydrates  Carbohydrates (% Daily Value)  Dietary Fiber  \\\n",
       "0             31                             10              4   \n",
       "1             30                             10              4   \n",
       "2             29                             10              4   \n",
       "3             30                             10              4   \n",
       "4             30                             10              4   \n",
       "\n",
       "   Dietary Fiber (% Daily Value)  Sugars  Protein  Vitamin A (% Daily Value)  \\\n",
       "0                             17       3       17                         10   \n",
       "1                             17       3       18                          6   \n",
       "2                             17       2       14                          8   \n",
       "3                             17       2       21                         15   \n",
       "4                             17       2       21                          6   \n",
       "\n",
       "   Vitamin C (% Daily Value)  Calcium (% Daily Value)  Iron (% Daily Value)  \n",
       "0                          0                       25                    15  \n",
       "1                          0                       25                     8  \n",
       "2                          0                       25                    10  \n",
       "3                          0                       30                    15  \n",
       "4                          0                       25                    10  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mcdonalds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Category', 'Item', 'Serving Size', 'Calories', 'Calories from Fat',\n",
       "       'Total Fat', 'Total Fat (% Daily Value)', 'Saturated Fat',\n",
       "       'Saturated Fat (% Daily Value)', 'Trans Fat', 'Cholesterol',\n",
       "       'Cholesterol (% Daily Value)', 'Sodium', 'Sodium (% Daily Value)',\n",
       "       'Carbohydrates', 'Carbohydrates (% Daily Value)', 'Dietary Fiber',\n",
       "       'Dietary Fiber (% Daily Value)', 'Sugars', 'Protein',\n",
       "       'Vitamin A (% Daily Value)', 'Vitamin C (% Daily Value)',\n",
       "       'Calcium (% Daily Value)', 'Iron (% Daily Value)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mcdonalds.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Checking for the Number of Counts based on Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Coffee & Tea          95\n",
       "Breakfast             42\n",
       "Smoothies & Shakes    28\n",
       "Beverages             27\n",
       "Chicken & Fish        27\n",
       "Beef & Pork           15\n",
       "Snacks & Sides        13\n",
       "Desserts               7\n",
       "Salads                 6\n",
       "Name: Category, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mcdonalds['Category'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16 fl oz cup      45\n",
       "12 fl oz cup      38\n",
       "22 fl oz cup      20\n",
       "20 fl oz cup      16\n",
       "30 fl oz cup       7\n",
       "21 fl oz cup       7\n",
       "5.7 oz (161 g)     5\n",
       "32 fl oz cup       5\n",
       "3.9 oz (111 g)     3\n",
       "7.1 oz (201 g)     3\n",
       "Name: Serving Size, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mcdonalds['Serving Size'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fats on Their Menu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Max_Fat</th>\n",
       "      <th>Max_Trans_Fat</th>\n",
       "      <th>Max_Sat_Fat</th>\n",
       "      <th>Max_Cholestrol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Beef &amp; Pork</td>\n",
       "      <td>66</td>\n",
       "      <td>2.5</td>\n",
       "      <td>96</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Chicken &amp; Fish</td>\n",
       "      <td>182</td>\n",
       "      <td>1.0</td>\n",
       "      <td>101</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>48</td>\n",
       "      <td>1.5</td>\n",
       "      <td>101</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Desserts</td>\n",
       "      <td>19</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Salads</td>\n",
       "      <td>33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>102</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Snacks &amp; Sides</td>\n",
       "      <td>37</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Category  Max_Fat  Max_Trans_Fat  Max_Sat_Fat  Max_Cholestrol\n",
       "0         Beef & Pork       66            2.5           96              53\n",
       "1           Beverages        4            0.0            8               3\n",
       "2           Breakfast       93            1.5          100             192\n",
       "3      Chicken & Fish      182            1.0          101              89\n",
       "4        Coffee & Tea       48            1.5          101              32\n",
       "5            Desserts       19            0.0           35              10\n",
       "6              Salads       33            0.0           29              29\n",
       "7  Smoothies & Shakes       50            1.0          102              30\n",
       "8      Snacks & Sides       37            0.0           27              16"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grp_by_mcdonalds=mcdonalds.groupby(['Category'],as_index=False)['Total Fat (% Daily Value)','Trans Fat','Saturated Fat (% Daily Value)','Cholesterol (% Daily Value)'].agg(np.max)\n",
    "grp_by_mcdonalds.columns=['Category','Max_Fat','Max_Trans_Fat','Max_Sat_Fat','Max_Cholestrol']\n",
    "\n",
    "grp_by_mcdonalds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Item</th>\n",
       "      <th>Total Fat (% Daily Value)</th>\n",
       "      <th>Cholesterol (% Daily Value)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Hotcakes (Large Biscuit)</td>\n",
       "      <td>93</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Beef &amp; Pork</td>\n",
       "      <td>Double Quarter Pounder with Cheese</td>\n",
       "      <td>66</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Chicken &amp; Fish</td>\n",
       "      <td>Chicken McNuggets (40 piece)</td>\n",
       "      <td>182</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Premium Bacon Ranch Salad with Crispy Chicken</td>\n",
       "      <td>33</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Salads</td>\n",
       "      <td>Premium Southwest Salad with Crispy Chicken</td>\n",
       "      <td>33</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Snacks &amp; Sides</td>\n",
       "      <td>Large French Fries</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Desserts</td>\n",
       "      <td>Baked Apple Pie</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>1% Low Fat Milk Jug</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Frappé Chocolate Chip (Large)</td>\n",
       "      <td>48</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>McFlurry with M&amp;M’s Candies (Medium)</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>McFlurry with Reese's Peanut Butter Cups (Medium)</td>\n",
       "      <td>50</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Category                                               Item  \\\n",
       "32            Breakfast        Big Breakfast with Hotcakes (Large Biscuit)   \n",
       "47          Beef & Pork                 Double Quarter Pounder with Cheese   \n",
       "82       Chicken & Fish                       Chicken McNuggets (40 piece)   \n",
       "85               Salads      Premium Bacon Ranch Salad with Crispy Chicken   \n",
       "88               Salads        Premium Southwest Salad with Crispy Chicken   \n",
       "98       Snacks & Sides                                 Large French Fries   \n",
       "103            Desserts                                    Baked Apple Pie   \n",
       "130           Beverages                                1% Low Fat Milk Jug   \n",
       "231        Coffee & Tea                      Frappé Chocolate Chip (Large)   \n",
       "253  Smoothies & Shakes               McFlurry with M&M’s Candies (Medium)   \n",
       "258  Smoothies & Shakes  McFlurry with Reese's Peanut Butter Cups (Medium)   \n",
       "\n",
       "     Total Fat (% Daily Value)  Cholesterol (% Daily Value)  \n",
       "32                          93                          192  \n",
       "47                          66                           53  \n",
       "82                         182                           89  \n",
       "85                          33                           23  \n",
       "88                          33                           17  \n",
       "98                          37                            0  \n",
       "103                         19                            0  \n",
       "130                          4                            3  \n",
       "231                         48                           32  \n",
       "253                         50                           25  \n",
       "258                         50                           20  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mcdonalds=mcdonalds.merge(grp_by_mcdonalds,left_on=['Category'],right_on=['Category'])\n",
    "fatty_mcdonalds=mcdonalds.loc[mcdonalds['Total Fat (% Daily Value)']==mcdonalds.Max_Fat,['Category','Item','Total Fat (% Daily Value)','Cholesterol (% Daily Value)']]\n",
    "fatty_mcdonalds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Item</th>\n",
       "      <th>Total Fat (% Daily Value)</th>\n",
       "      <th>Trans Fat</th>\n",
       "      <th>Saturated Fat (% Daily Value)</th>\n",
       "      <th>Cholesterol (% Daily Value)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Beef &amp; Pork</td>\n",
       "      <td>Double Quarter Pounder with Cheese</td>\n",
       "      <td>66</td>\n",
       "      <td>2.5</td>\n",
       "      <td>96</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Steak, Egg &amp; Cheese Bagel</td>\n",
       "      <td>53</td>\n",
       "      <td>1.5</td>\n",
       "      <td>63</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Frappé Chocolate Chip (Large)</td>\n",
       "      <td>48</td>\n",
       "      <td>1.5</td>\n",
       "      <td>101</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Frappé Caramel (Large)</td>\n",
       "      <td>42</td>\n",
       "      <td>1.5</td>\n",
       "      <td>87</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Shamrock Shake (Large)</td>\n",
       "      <td>35</td>\n",
       "      <td>1.0</td>\n",
       "      <td>73</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Shamrock Shake (Medium)</td>\n",
       "      <td>29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>61</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Chocolate Shake (Large)</td>\n",
       "      <td>36</td>\n",
       "      <td>1.0</td>\n",
       "      <td>74</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Chocolate Shake (Medium)</td>\n",
       "      <td>30</td>\n",
       "      <td>1.0</td>\n",
       "      <td>62</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>McFlurry with M&amp;M’s Candies (Medium)</td>\n",
       "      <td>50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>102</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Strawberry Shake (Large)</td>\n",
       "      <td>36</td>\n",
       "      <td>1.0</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Strawberry Shake (Medium)</td>\n",
       "      <td>30</td>\n",
       "      <td>1.0</td>\n",
       "      <td>63</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Strawberry Shake (Small)</td>\n",
       "      <td>25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>52</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Vanilla Shake (Large)</td>\n",
       "      <td>35</td>\n",
       "      <td>1.0</td>\n",
       "      <td>73</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Vanilla Shake (Medium)</td>\n",
       "      <td>29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>61</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Vanilla Shake (Small)</td>\n",
       "      <td>24</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>McFlurry with Oreo Cookies (Medium)</td>\n",
       "      <td>35</td>\n",
       "      <td>1.0</td>\n",
       "      <td>58</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>Chocolate Shake (Small)</td>\n",
       "      <td>25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>Smoothies &amp; Shakes</td>\n",
       "      <td>McFlurry with Reese's Peanut Butter Cups (Medium)</td>\n",
       "      <td>50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>76</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Chicken &amp; Fish</td>\n",
       "      <td>Chicken McNuggets (40 piece)</td>\n",
       "      <td>182</td>\n",
       "      <td>1.0</td>\n",
       "      <td>101</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Category                                               Item  \\\n",
       "47          Beef & Pork                 Double Quarter Pounder with Cheese   \n",
       "26            Breakfast                          Steak, Egg & Cheese Bagel   \n",
       "231        Coffee & Tea                      Frappé Chocolate Chip (Large)   \n",
       "228        Coffee & Tea                             Frappé Caramel (Large)   \n",
       "251  Smoothies & Shakes                             Shamrock Shake (Large)   \n",
       "250  Smoothies & Shakes                            Shamrock Shake (Medium)   \n",
       "249  Smoothies & Shakes                            Chocolate Shake (Large)   \n",
       "248  Smoothies & Shakes                           Chocolate Shake (Medium)   \n",
       "253  Smoothies & Shakes               McFlurry with M&M’s Candies (Medium)   \n",
       "246  Smoothies & Shakes                           Strawberry Shake (Large)   \n",
       "245  Smoothies & Shakes                          Strawberry Shake (Medium)   \n",
       "244  Smoothies & Shakes                           Strawberry Shake (Small)   \n",
       "243  Smoothies & Shakes                              Vanilla Shake (Large)   \n",
       "242  Smoothies & Shakes                             Vanilla Shake (Medium)   \n",
       "241  Smoothies & Shakes                              Vanilla Shake (Small)   \n",
       "256  Smoothies & Shakes                McFlurry with Oreo Cookies (Medium)   \n",
       "247  Smoothies & Shakes                            Chocolate Shake (Small)   \n",
       "258  Smoothies & Shakes  McFlurry with Reese's Peanut Butter Cups (Medium)   \n",
       "82       Chicken & Fish                       Chicken McNuggets (40 piece)   \n",
       "\n",
       "     Total Fat (% Daily Value)  Trans Fat  Saturated Fat (% Daily Value)  \\\n",
       "47                          66        2.5                             96   \n",
       "26                          53        1.5                             63   \n",
       "231                         48        1.5                            101   \n",
       "228                         42        1.5                             87   \n",
       "251                         35        1.0                             73   \n",
       "250                         29        1.0                             61   \n",
       "249                         36        1.0                             74   \n",
       "248                         30        1.0                             62   \n",
       "253                         50        1.0                            102   \n",
       "246                         36        1.0                             75   \n",
       "245                         30        1.0                             63   \n",
       "244                         25        1.0                             52   \n",
       "243                         35        1.0                             73   \n",
       "242                         29        1.0                             61   \n",
       "241                         24        1.0                             49   \n",
       "256                         35        1.0                             58   \n",
       "247                         25        1.0                             51   \n",
       "258                         50        1.0                             76   \n",
       "82                         182        1.0                            101   \n",
       "\n",
       "     Cholesterol (% Daily Value)  \n",
       "47                            53  \n",
       "26                            99  \n",
       "231                           32  \n",
       "228                           32  \n",
       "251                           29  \n",
       "250                           24  \n",
       "249                           29  \n",
       "248                           24  \n",
       "253                           25  \n",
       "246                           30  \n",
       "245                           25  \n",
       "244                           21  \n",
       "243                           29  \n",
       "242                           24  \n",
       "241                           20  \n",
       "256                           19  \n",
       "247                           20  \n",
       "258                           20  \n",
       "82                            89  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fatty_mcdonalds=mcdonalds.loc[mcdonalds['Trans Fat']==mcdonalds.Max_Trans_Fat,['Category','Item','Total Fat (% Daily Value)','Trans Fat','Saturated Fat (% Daily Value)','Cholesterol (% Daily Value)']]\n",
    "fatty_mcdonalds.sort_values(by='Trans Fat',ascending=False)[0:19]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Double Quarter Pounder with Cheese is the most unhealthiest item on the menu with 2.5g of trans fat. \n",
    "40 Chicken McNuggets has more than the daily alotted value for total fat."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Anything that Will Not Give Me Cholestrol:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Item</th>\n",
       "      <th>Total Fat (% Daily Value)</th>\n",
       "      <th>Cholesterol (% Daily Value)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>Snacks &amp; Sides</td>\n",
       "      <td>Side Salad</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Snacks &amp; Sides</td>\n",
       "      <td>Apple Slices</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Coca-Cola Classic (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Coca-Cola Classic (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Coca-Cola Classic (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Coca-Cola Classic (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Coke (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Coke (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Coke (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Coke (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Dr Pepper (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Dr Pepper (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Dr Pepper (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Dr Pepper (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Dr Pepper (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Dr Pepper (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Dr Pepper (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Diet Dr Pepper (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Sprite (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Sprite (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Sprite (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Sprite (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Minute Maid 100% Apple Juice Box</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Minute Maid Orange Juice (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Minute Maid Orange Juice (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Minute Maid Orange Juice (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Dasani Water Bottle</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Iced Tea (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Iced Tea (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Iced Tea (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Iced Tea (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Sweet Tea (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Sweet Tea (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Sweet Tea (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Sweet Tea (Child)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Coffee (Small)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Coffee (Medium)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Coffee &amp; Tea</td>\n",
       "      <td>Coffee (Large)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Category                               Item  \\\n",
       "100  Snacks & Sides                         Side Salad   \n",
       "101  Snacks & Sides                       Apple Slices   \n",
       "110       Beverages          Coca-Cola Classic (Small)   \n",
       "111       Beverages         Coca-Cola Classic (Medium)   \n",
       "112       Beverages          Coca-Cola Classic (Large)   \n",
       "113       Beverages          Coca-Cola Classic (Child)   \n",
       "114       Beverages                  Diet Coke (Small)   \n",
       "115       Beverages                 Diet Coke (Medium)   \n",
       "116       Beverages                  Diet Coke (Large)   \n",
       "117       Beverages                  Diet Coke (Child)   \n",
       "118       Beverages                  Dr Pepper (Small)   \n",
       "119       Beverages                 Dr Pepper (Medium)   \n",
       "120       Beverages                  Dr Pepper (Large)   \n",
       "121       Beverages                  Dr Pepper (Child)   \n",
       "122       Beverages             Diet Dr Pepper (Small)   \n",
       "123       Beverages            Diet Dr Pepper (Medium)   \n",
       "124       Beverages             Diet Dr Pepper (Large)   \n",
       "125       Beverages             Diet Dr Pepper (Child)   \n",
       "126       Beverages                     Sprite (Small)   \n",
       "127       Beverages                    Sprite (Medium)   \n",
       "128       Beverages                     Sprite (Large)   \n",
       "129       Beverages                     Sprite (Child)   \n",
       "132       Beverages   Minute Maid 100% Apple Juice Box   \n",
       "133       Beverages   Minute Maid Orange Juice (Small)   \n",
       "134       Beverages  Minute Maid Orange Juice (Medium)   \n",
       "135       Beverages   Minute Maid Orange Juice (Large)   \n",
       "136       Beverages                Dasani Water Bottle   \n",
       "137    Coffee & Tea                   Iced Tea (Small)   \n",
       "138    Coffee & Tea                  Iced Tea (Medium)   \n",
       "139    Coffee & Tea                   Iced Tea (Large)   \n",
       "140    Coffee & Tea                   Iced Tea (Child)   \n",
       "141    Coffee & Tea                  Sweet Tea (Small)   \n",
       "142    Coffee & Tea                 Sweet Tea (Medium)   \n",
       "143    Coffee & Tea                  Sweet Tea (Large)   \n",
       "144    Coffee & Tea                  Sweet Tea (Child)   \n",
       "145    Coffee & Tea                     Coffee (Small)   \n",
       "146    Coffee & Tea                    Coffee (Medium)   \n",
       "147    Coffee & Tea                     Coffee (Large)   \n",
       "\n",
       "     Total Fat (% Daily Value)  Cholesterol (% Daily Value)  \n",
       "100                          0                            0  \n",
       "101                          0                            0  \n",
       "110                          0                            0  \n",
       "111                          0                            0  \n",
       "112                          0                            0  \n",
       "113                          0                            0  \n",
       "114                          0                            0  \n",
       "115                          0                            0  \n",
       "116                          0                            0  \n",
       "117                          0                            0  \n",
       "118                          0                            0  \n",
       "119                          0                            0  \n",
       "120                          0                            0  \n",
       "121                          0                            0  \n",
       "122                          0                            0  \n",
       "123                          0                            0  \n",
       "124                          0                            0  \n",
       "125                          0                            0  \n",
       "126                          0                            0  \n",
       "127                          0                            0  \n",
       "128                          0                            0  \n",
       "129                          0                            0  \n",
       "132                          0                            0  \n",
       "133                          0                            0  \n",
       "134                          0                            0  \n",
       "135                          0                            0  \n",
       "136                          0                            0  \n",
       "137                          0                            0  \n",
       "138                          0                            0  \n",
       "139                          0                            0  \n",
       "140                          0                            0  \n",
       "141                          0                            0  \n",
       "142                          0                            0  \n",
       "143                          0                            0  \n",
       "144                          0                            0  \n",
       "145                          0                            0  \n",
       "146                          0                            0  \n",
       "147                          0                            0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = mcdonalds.sort_values(by=['Total Fat (% Daily Value)','Cholesterol (% Daily Value)'])\n",
    "g.loc[:,['Category','Item','Total Fat (% Daily Value)','Cholesterol (% Daily Value)']][0:38]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the information about McDonald's, it has been determined that most items are unhealthy, however, there are better alternatives to have when going out to McDonald's."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Breakfast Counts as an Example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Item</th>\n",
       "      <th>Serving Size</th>\n",
       "      <th>Calories</th>\n",
       "      <th>Calories from Fat</th>\n",
       "      <th>Total Fat</th>\n",
       "      <th>Total Fat (% Daily Value)</th>\n",
       "      <th>Saturated Fat</th>\n",
       "      <th>Saturated Fat (% Daily Value)</th>\n",
       "      <th>Trans Fat</th>\n",
       "      <th>...</th>\n",
       "      <th>Sugars</th>\n",
       "      <th>Protein</th>\n",
       "      <th>Vitamin A (% Daily Value)</th>\n",
       "      <th>Vitamin C (% Daily Value)</th>\n",
       "      <th>Calcium (% Daily Value)</th>\n",
       "      <th>Iron (% Daily Value)</th>\n",
       "      <th>Max_Fat</th>\n",
       "      <th>Max_Trans_Fat</th>\n",
       "      <th>Max_Sat_Fat</th>\n",
       "      <th>Max_Cholestrol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Egg McMuffin</td>\n",
       "      <td>4.8 oz (136 g)</td>\n",
       "      <td>300</td>\n",
       "      <td>120</td>\n",
       "      <td>13.0</td>\n",
       "      <td>20</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Egg White Delight</td>\n",
       "      <td>4.8 oz (135 g)</td>\n",
       "      <td>250</td>\n",
       "      <td>70</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>8</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McMuffin</td>\n",
       "      <td>3.9 oz (111 g)</td>\n",
       "      <td>370</td>\n",
       "      <td>200</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35</td>\n",
       "      <td>8.0</td>\n",
       "      <td>42</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McMuffin with Egg</td>\n",
       "      <td>5.7 oz (161 g)</td>\n",
       "      <td>450</td>\n",
       "      <td>250</td>\n",
       "      <td>28.0</td>\n",
       "      <td>43</td>\n",
       "      <td>10.0</td>\n",
       "      <td>52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McMuffin with Egg Whites</td>\n",
       "      <td>5.7 oz (161 g)</td>\n",
       "      <td>400</td>\n",
       "      <td>210</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35</td>\n",
       "      <td>8.0</td>\n",
       "      <td>42</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Steak &amp; Egg McMuffin</td>\n",
       "      <td>6.5 oz (185 g)</td>\n",
       "      <td>430</td>\n",
       "      <td>210</td>\n",
       "      <td>23.0</td>\n",
       "      <td>36</td>\n",
       "      <td>9.0</td>\n",
       "      <td>46</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>30</td>\n",
       "      <td>20</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese Biscuit (Regular Biscuit)</td>\n",
       "      <td>5.3 oz (150 g)</td>\n",
       "      <td>460</td>\n",
       "      <td>230</td>\n",
       "      <td>26.0</td>\n",
       "      <td>40</td>\n",
       "      <td>13.0</td>\n",
       "      <td>65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese Biscuit (Large Biscuit)</td>\n",
       "      <td>5.8 oz (164 g)</td>\n",
       "      <td>520</td>\n",
       "      <td>270</td>\n",
       "      <td>30.0</td>\n",
       "      <td>47</td>\n",
       "      <td>14.0</td>\n",
       "      <td>68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese Biscuit with Egg Whites (R...</td>\n",
       "      <td>5.4 oz (153 g)</td>\n",
       "      <td>410</td>\n",
       "      <td>180</td>\n",
       "      <td>20.0</td>\n",
       "      <td>32</td>\n",
       "      <td>11.0</td>\n",
       "      <td>56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese Biscuit with Egg Whites (L...</td>\n",
       "      <td>5.9 oz (167 g)</td>\n",
       "      <td>470</td>\n",
       "      <td>220</td>\n",
       "      <td>25.0</td>\n",
       "      <td>38</td>\n",
       "      <td>12.0</td>\n",
       "      <td>59</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Biscuit (Regular Biscuit)</td>\n",
       "      <td>4.1 oz (117 g)</td>\n",
       "      <td>430</td>\n",
       "      <td>240</td>\n",
       "      <td>27.0</td>\n",
       "      <td>42</td>\n",
       "      <td>12.0</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Biscuit (Large Biscuit)</td>\n",
       "      <td>4.6 oz (131 g)</td>\n",
       "      <td>480</td>\n",
       "      <td>280</td>\n",
       "      <td>31.0</td>\n",
       "      <td>48</td>\n",
       "      <td>13.0</td>\n",
       "      <td>65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Biscuit with Egg (Regular Biscuit)</td>\n",
       "      <td>5.7 oz (163 g)</td>\n",
       "      <td>510</td>\n",
       "      <td>290</td>\n",
       "      <td>33.0</td>\n",
       "      <td>50</td>\n",
       "      <td>14.0</td>\n",
       "      <td>71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Biscuit with Egg (Large Biscuit)</td>\n",
       "      <td>6.2 oz (177 g)</td>\n",
       "      <td>570</td>\n",
       "      <td>330</td>\n",
       "      <td>37.0</td>\n",
       "      <td>57</td>\n",
       "      <td>15.0</td>\n",
       "      <td>74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Biscuit with Egg Whites (Regular Biscuit)</td>\n",
       "      <td>5.9 oz (167 g)</td>\n",
       "      <td>460</td>\n",
       "      <td>250</td>\n",
       "      <td>27.0</td>\n",
       "      <td>42</td>\n",
       "      <td>12.0</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Biscuit with Egg Whites (Large Biscuit)</td>\n",
       "      <td>6.4 oz (181 g)</td>\n",
       "      <td>520</td>\n",
       "      <td>280</td>\n",
       "      <td>32.0</td>\n",
       "      <td>49</td>\n",
       "      <td>13.0</td>\n",
       "      <td>65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Southern Style Chicken Biscuit (Regular Biscuit)</td>\n",
       "      <td>5 oz (143 g)</td>\n",
       "      <td>410</td>\n",
       "      <td>180</td>\n",
       "      <td>20.0</td>\n",
       "      <td>31</td>\n",
       "      <td>8.0</td>\n",
       "      <td>41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Southern Style Chicken Biscuit (Large Biscuit)</td>\n",
       "      <td>5.5 oz (157 g)</td>\n",
       "      <td>470</td>\n",
       "      <td>220</td>\n",
       "      <td>24.0</td>\n",
       "      <td>37</td>\n",
       "      <td>9.0</td>\n",
       "      <td>45</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Steak &amp; Egg Biscuit (Regular Biscuit)</td>\n",
       "      <td>7.1 oz (201 g)</td>\n",
       "      <td>540</td>\n",
       "      <td>290</td>\n",
       "      <td>32.0</td>\n",
       "      <td>49</td>\n",
       "      <td>16.0</td>\n",
       "      <td>78</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese McGriddles</td>\n",
       "      <td>6.1 oz (174 g)</td>\n",
       "      <td>460</td>\n",
       "      <td>190</td>\n",
       "      <td>21.0</td>\n",
       "      <td>32</td>\n",
       "      <td>9.0</td>\n",
       "      <td>44</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese McGriddles with Egg Whites</td>\n",
       "      <td>6.3 oz (178 g)</td>\n",
       "      <td>400</td>\n",
       "      <td>140</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24</td>\n",
       "      <td>7.0</td>\n",
       "      <td>34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage McGriddles</td>\n",
       "      <td>5 oz (141 g)</td>\n",
       "      <td>420</td>\n",
       "      <td>200</td>\n",
       "      <td>22.0</td>\n",
       "      <td>34</td>\n",
       "      <td>8.0</td>\n",
       "      <td>40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage, Egg &amp; Cheese McGriddles</td>\n",
       "      <td>7.1 oz (201 g)</td>\n",
       "      <td>550</td>\n",
       "      <td>280</td>\n",
       "      <td>31.0</td>\n",
       "      <td>48</td>\n",
       "      <td>12.0</td>\n",
       "      <td>61</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage, Egg &amp; Cheese McGriddles with Egg Whites</td>\n",
       "      <td>7.2 oz (205 g)</td>\n",
       "      <td>500</td>\n",
       "      <td>230</td>\n",
       "      <td>26.0</td>\n",
       "      <td>40</td>\n",
       "      <td>10.0</td>\n",
       "      <td>52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese Bagel</td>\n",
       "      <td>6.9 oz (197 g)</td>\n",
       "      <td>620</td>\n",
       "      <td>280</td>\n",
       "      <td>31.0</td>\n",
       "      <td>48</td>\n",
       "      <td>11.0</td>\n",
       "      <td>56</td>\n",
       "      <td>0.5</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Bacon, Egg &amp; Cheese Bagel with Egg Whites</td>\n",
       "      <td>7.1 oz (201 g)</td>\n",
       "      <td>570</td>\n",
       "      <td>230</td>\n",
       "      <td>25.0</td>\n",
       "      <td>39</td>\n",
       "      <td>9.0</td>\n",
       "      <td>45</td>\n",
       "      <td>0.5</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>30</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Steak, Egg &amp; Cheese Bagel</td>\n",
       "      <td>8.5 oz (241 g)</td>\n",
       "      <td>670</td>\n",
       "      <td>310</td>\n",
       "      <td>35.0</td>\n",
       "      <td>53</td>\n",
       "      <td>13.0</td>\n",
       "      <td>63</td>\n",
       "      <td>1.5</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>33</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast (Regular Biscuit)</td>\n",
       "      <td>9.5 oz (269 g)</td>\n",
       "      <td>740</td>\n",
       "      <td>430</td>\n",
       "      <td>48.0</td>\n",
       "      <td>73</td>\n",
       "      <td>17.0</td>\n",
       "      <td>87</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast (Large Biscuit)</td>\n",
       "      <td>10 oz (283 g)</td>\n",
       "      <td>800</td>\n",
       "      <td>470</td>\n",
       "      <td>52.0</td>\n",
       "      <td>80</td>\n",
       "      <td>18.0</td>\n",
       "      <td>90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>30</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Egg Whites (Regular Biscuit)</td>\n",
       "      <td>9.6 oz (272 g)</td>\n",
       "      <td>640</td>\n",
       "      <td>330</td>\n",
       "      <td>37.0</td>\n",
       "      <td>57</td>\n",
       "      <td>14.0</td>\n",
       "      <td>69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Egg Whites (Large Biscuit)</td>\n",
       "      <td>10.1 oz (286 g)</td>\n",
       "      <td>690</td>\n",
       "      <td>370</td>\n",
       "      <td>41.0</td>\n",
       "      <td>63</td>\n",
       "      <td>14.0</td>\n",
       "      <td>72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>26</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Hotcakes (Regular Biscuit)</td>\n",
       "      <td>14.8 oz (420 g)</td>\n",
       "      <td>1090</td>\n",
       "      <td>510</td>\n",
       "      <td>56.0</td>\n",
       "      <td>87</td>\n",
       "      <td>19.0</td>\n",
       "      <td>96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>36</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>40</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Hotcakes (Large Biscuit)</td>\n",
       "      <td>15.3 oz (434 g)</td>\n",
       "      <td>1150</td>\n",
       "      <td>540</td>\n",
       "      <td>60.0</td>\n",
       "      <td>93</td>\n",
       "      <td>20.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>36</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>30</td>\n",
       "      <td>40</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Hotcakes and Egg Whites (Re...</td>\n",
       "      <td>14.9 oz (423 g)</td>\n",
       "      <td>990</td>\n",
       "      <td>410</td>\n",
       "      <td>46.0</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Big Breakfast with Hotcakes and Egg Whites (La...</td>\n",
       "      <td>15.4 oz (437 g)</td>\n",
       "      <td>1050</td>\n",
       "      <td>450</td>\n",
       "      <td>50.0</td>\n",
       "      <td>77</td>\n",
       "      <td>16.0</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Hotcakes</td>\n",
       "      <td>5.3 oz (151 g)</td>\n",
       "      <td>350</td>\n",
       "      <td>80</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Hotcakes and Sausage</td>\n",
       "      <td>6.8 oz (192 g)</td>\n",
       "      <td>520</td>\n",
       "      <td>210</td>\n",
       "      <td>24.0</td>\n",
       "      <td>37</td>\n",
       "      <td>7.0</td>\n",
       "      <td>36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Sausage Burrito</td>\n",
       "      <td>3.9 oz (111 g)</td>\n",
       "      <td>300</td>\n",
       "      <td>150</td>\n",
       "      <td>16.0</td>\n",
       "      <td>25</td>\n",
       "      <td>7.0</td>\n",
       "      <td>33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Hash Brown</td>\n",
       "      <td>2 oz (56 g)</td>\n",
       "      <td>150</td>\n",
       "      <td>80</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14</td>\n",
       "      <td>1.5</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Cinnamon Melts</td>\n",
       "      <td>4 oz (114 g)</td>\n",
       "      <td>460</td>\n",
       "      <td>170</td>\n",
       "      <td>19.0</td>\n",
       "      <td>30</td>\n",
       "      <td>9.0</td>\n",
       "      <td>43</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Fruit &amp; Maple Oatmeal</td>\n",
       "      <td>9.6 oz (251 g)</td>\n",
       "      <td>290</td>\n",
       "      <td>35</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Breakfast</td>\n",
       "      <td>Fruit &amp; Maple Oatmeal without Brown Sugar</td>\n",
       "      <td>9.6 oz (251 g)</td>\n",
       "      <td>260</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>93</td>\n",
       "      <td>1.5</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>42 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Category                                               Item  \\\n",
       "0   Breakfast                                       Egg McMuffin   \n",
       "1   Breakfast                                  Egg White Delight   \n",
       "2   Breakfast                                   Sausage McMuffin   \n",
       "3   Breakfast                          Sausage McMuffin with Egg   \n",
       "4   Breakfast                   Sausage McMuffin with Egg Whites   \n",
       "5   Breakfast                               Steak & Egg McMuffin   \n",
       "6   Breakfast      Bacon, Egg & Cheese Biscuit (Regular Biscuit)   \n",
       "7   Breakfast        Bacon, Egg & Cheese Biscuit (Large Biscuit)   \n",
       "8   Breakfast  Bacon, Egg & Cheese Biscuit with Egg Whites (R...   \n",
       "9   Breakfast  Bacon, Egg & Cheese Biscuit with Egg Whites (L...   \n",
       "10  Breakfast                  Sausage Biscuit (Regular Biscuit)   \n",
       "11  Breakfast                    Sausage Biscuit (Large Biscuit)   \n",
       "12  Breakfast         Sausage Biscuit with Egg (Regular Biscuit)   \n",
       "13  Breakfast           Sausage Biscuit with Egg (Large Biscuit)   \n",
       "14  Breakfast  Sausage Biscuit with Egg Whites (Regular Biscuit)   \n",
       "15  Breakfast    Sausage Biscuit with Egg Whites (Large Biscuit)   \n",
       "16  Breakfast   Southern Style Chicken Biscuit (Regular Biscuit)   \n",
       "17  Breakfast     Southern Style Chicken Biscuit (Large Biscuit)   \n",
       "18  Breakfast              Steak & Egg Biscuit (Regular Biscuit)   \n",
       "19  Breakfast                     Bacon, Egg & Cheese McGriddles   \n",
       "20  Breakfast     Bacon, Egg & Cheese McGriddles with Egg Whites   \n",
       "21  Breakfast                                 Sausage McGriddles   \n",
       "22  Breakfast                   Sausage, Egg & Cheese McGriddles   \n",
       "23  Breakfast   Sausage, Egg & Cheese McGriddles with Egg Whites   \n",
       "24  Breakfast                          Bacon, Egg & Cheese Bagel   \n",
       "25  Breakfast          Bacon, Egg & Cheese Bagel with Egg Whites   \n",
       "26  Breakfast                          Steak, Egg & Cheese Bagel   \n",
       "27  Breakfast                    Big Breakfast (Regular Biscuit)   \n",
       "28  Breakfast                      Big Breakfast (Large Biscuit)   \n",
       "29  Breakfast    Big Breakfast with Egg Whites (Regular Biscuit)   \n",
       "30  Breakfast      Big Breakfast with Egg Whites (Large Biscuit)   \n",
       "31  Breakfast      Big Breakfast with Hotcakes (Regular Biscuit)   \n",
       "32  Breakfast        Big Breakfast with Hotcakes (Large Biscuit)   \n",
       "33  Breakfast  Big Breakfast with Hotcakes and Egg Whites (Re...   \n",
       "34  Breakfast  Big Breakfast with Hotcakes and Egg Whites (La...   \n",
       "35  Breakfast                                           Hotcakes   \n",
       "36  Breakfast                               Hotcakes and Sausage   \n",
       "37  Breakfast                                    Sausage Burrito   \n",
       "38  Breakfast                                         Hash Brown   \n",
       "39  Breakfast                                     Cinnamon Melts   \n",
       "40  Breakfast                              Fruit & Maple Oatmeal   \n",
       "41  Breakfast          Fruit & Maple Oatmeal without Brown Sugar   \n",
       "\n",
       "       Serving Size  Calories  Calories from Fat  Total Fat  \\\n",
       "0    4.8 oz (136 g)       300                120       13.0   \n",
       "1    4.8 oz (135 g)       250                 70        8.0   \n",
       "2    3.9 oz (111 g)       370                200       23.0   \n",
       "3    5.7 oz (161 g)       450                250       28.0   \n",
       "4    5.7 oz (161 g)       400                210       23.0   \n",
       "5    6.5 oz (185 g)       430                210       23.0   \n",
       "6    5.3 oz (150 g)       460                230       26.0   \n",
       "7    5.8 oz (164 g)       520                270       30.0   \n",
       "8    5.4 oz (153 g)       410                180       20.0   \n",
       "9    5.9 oz (167 g)       470                220       25.0   \n",
       "10   4.1 oz (117 g)       430                240       27.0   \n",
       "11   4.6 oz (131 g)       480                280       31.0   \n",
       "12   5.7 oz (163 g)       510                290       33.0   \n",
       "13   6.2 oz (177 g)       570                330       37.0   \n",
       "14   5.9 oz (167 g)       460                250       27.0   \n",
       "15   6.4 oz (181 g)       520                280       32.0   \n",
       "16     5 oz (143 g)       410                180       20.0   \n",
       "17   5.5 oz (157 g)       470                220       24.0   \n",
       "18   7.1 oz (201 g)       540                290       32.0   \n",
       "19   6.1 oz (174 g)       460                190       21.0   \n",
       "20   6.3 oz (178 g)       400                140       15.0   \n",
       "21     5 oz (141 g)       420                200       22.0   \n",
       "22   7.1 oz (201 g)       550                280       31.0   \n",
       "23   7.2 oz (205 g)       500                230       26.0   \n",
       "24   6.9 oz (197 g)       620                280       31.0   \n",
       "25   7.1 oz (201 g)       570                230       25.0   \n",
       "26   8.5 oz (241 g)       670                310       35.0   \n",
       "27   9.5 oz (269 g)       740                430       48.0   \n",
       "28    10 oz (283 g)       800                470       52.0   \n",
       "29   9.6 oz (272 g)       640                330       37.0   \n",
       "30  10.1 oz (286 g)       690                370       41.0   \n",
       "31  14.8 oz (420 g)      1090                510       56.0   \n",
       "32  15.3 oz (434 g)      1150                540       60.0   \n",
       "33  14.9 oz (423 g)       990                410       46.0   \n",
       "34  15.4 oz (437 g)      1050                450       50.0   \n",
       "35   5.3 oz (151 g)       350                 80        9.0   \n",
       "36   6.8 oz (192 g)       520                210       24.0   \n",
       "37   3.9 oz (111 g)       300                150       16.0   \n",
       "38      2 oz (56 g)       150                 80        9.0   \n",
       "39     4 oz (114 g)       460                170       19.0   \n",
       "40   9.6 oz (251 g)       290                 35        4.0   \n",
       "41   9.6 oz (251 g)       260                 40        4.0   \n",
       "\n",
       "    Total Fat (% Daily Value)  Saturated Fat  Saturated Fat (% Daily Value)  \\\n",
       "0                          20            5.0                             25   \n",
       "1                          12            3.0                             15   \n",
       "2                          35            8.0                             42   \n",
       "3                          43           10.0                             52   \n",
       "4                          35            8.0                             42   \n",
       "5                          36            9.0                             46   \n",
       "6                          40           13.0                             65   \n",
       "7                          47           14.0                             68   \n",
       "8                          32           11.0                             56   \n",
       "9                          38           12.0                             59   \n",
       "10                         42           12.0                             62   \n",
       "11                         48           13.0                             65   \n",
       "12                         50           14.0                             71   \n",
       "13                         57           15.0                             74   \n",
       "14                         42           12.0                             62   \n",
       "15                         49           13.0                             65   \n",
       "16                         31            8.0                             41   \n",
       "17                         37            9.0                             45   \n",
       "18                         49           16.0                             78   \n",
       "19                         32            9.0                             44   \n",
       "20                         24            7.0                             34   \n",
       "21                         34            8.0                             40   \n",
       "22                         48           12.0                             61   \n",
       "23                         40           10.0                             52   \n",
       "24                         48           11.0                             56   \n",
       "25                         39            9.0                             45   \n",
       "26                         53           13.0                             63   \n",
       "27                         73           17.0                             87   \n",
       "28                         80           18.0                             90   \n",
       "29                         57           14.0                             69   \n",
       "30                         63           14.0                             72   \n",
       "31                         87           19.0                             96   \n",
       "32                         93           20.0                            100   \n",
       "33                         70           16.0                             78   \n",
       "34                         77           16.0                             81   \n",
       "35                         13            2.0                              9   \n",
       "36                         37            7.0                             36   \n",
       "37                         25            7.0                             33   \n",
       "38                         14            1.5                              6   \n",
       "39                         30            9.0                             43   \n",
       "40                          6            1.5                              8   \n",
       "41                          6            1.5                              8   \n",
       "\n",
       "    Trans Fat       ...        Sugars  Protein  Vitamin A (% Daily Value)  \\\n",
       "0         0.0       ...             3       17                         10   \n",
       "1         0.0       ...             3       18                          6   \n",
       "2         0.0       ...             2       14                          8   \n",
       "3         0.0       ...             2       21                         15   \n",
       "4         0.0       ...             2       21                          6   \n",
       "5         1.0       ...             3       26                         15   \n",
       "6         0.0       ...             3       19                         10   \n",
       "7         0.0       ...             4       19                         15   \n",
       "8         0.0       ...             3       20                          2   \n",
       "9         0.0       ...             4       20                          6   \n",
       "10        0.0       ...             2       11                          0   \n",
       "11        0.0       ...             3       11                          4   \n",
       "12        0.0       ...             2       18                          6   \n",
       "13        0.0       ...             3       18                         10   \n",
       "14        0.0       ...             3       18                          0   \n",
       "15        0.0       ...             3       18                          4   \n",
       "16        0.0       ...             3       17                          0   \n",
       "17        0.0       ...             4       17                          4   \n",
       "18        1.0       ...             3       25                         10   \n",
       "19        0.0       ...            15       19                         10   \n",
       "20        0.0       ...            16       20                          2   \n",
       "21        0.0       ...            15       11                          0   \n",
       "22        0.0       ...            15       20                         10   \n",
       "23        0.0       ...            15       21                          2   \n",
       "24        0.5       ...             7       30                         20   \n",
       "25        0.5       ...             8       30                         10   \n",
       "26        1.5       ...             7       33                         20   \n",
       "27        0.0       ...             3       28                         15   \n",
       "28        0.0       ...             3       28                         15   \n",
       "29        0.0       ...             3       26                          0   \n",
       "30        0.0       ...             4       26                          4   \n",
       "31        0.0       ...            17       36                         15   \n",
       "32        0.0       ...            17       36                         15   \n",
       "33        0.0       ...            17       35                          0   \n",
       "34        0.0       ...            18       35                          4   \n",
       "35        0.0       ...            14        8                          0   \n",
       "36        0.0       ...            14       15                          0   \n",
       "37        0.0       ...             2       12                         10   \n",
       "38        0.0       ...             0        1                          0   \n",
       "39        0.0       ...            32        6                          4   \n",
       "40        0.0       ...            32        5                          2   \n",
       "41        0.0       ...            18        5                          2   \n",
       "\n",
       "    Vitamin C (% Daily Value)  Calcium (% Daily Value)  Iron (% Daily Value)  \\\n",
       "0                           0                       25                    15   \n",
       "1                           0                       25                     8   \n",
       "2                           0                       25                    10   \n",
       "3                           0                       30                    15   \n",
       "4                           0                       25                    10   \n",
       "5                           2                       30                    20   \n",
       "6                           8                       15                    15   \n",
       "7                           8                       20                    20   \n",
       "8                           8                       15                    10   \n",
       "9                           8                       15                    15   \n",
       "10                          0                        6                    15   \n",
       "11                          0                        8                    15   \n",
       "12                          0                       10                    20   \n",
       "13                          0                       10                    20   \n",
       "14                          0                        8                    15   \n",
       "15                          0                        8                    15   \n",
       "16                          2                        6                    15   \n",
       "17                          2                        8                    15   \n",
       "18                          2                       20                    25   \n",
       "19                         10                       20                    15   \n",
       "20                         10                       15                    10   \n",
       "21                          0                        8                    10   \n",
       "22                          0                       20                    15   \n",
       "23                          0                       20                    10   \n",
       "24                         15                       20                    20   \n",
       "25                         15                       20                    15   \n",
       "26                          4                       25                    25   \n",
       "27                          2                       15                    25   \n",
       "28                          2                       15                    30   \n",
       "29                          2                       10                    15   \n",
       "30                          2                       10                    15   \n",
       "31                          2                       25                    40   \n",
       "32                          2                       30                    40   \n",
       "33                          2                       25                    30   \n",
       "34                          2                       25                    30   \n",
       "35                          0                       15                    15   \n",
       "36                          0                       15                    15   \n",
       "37                          2                       15                    15   \n",
       "38                          2                        0                     2   \n",
       "39                          0                        6                    15   \n",
       "40                        130                       10                    10   \n",
       "41                        130                        6                    10   \n",
       "\n",
       "    Max_Fat  Max_Trans_Fat  Max_Sat_Fat  Max_Cholestrol  \n",
       "0        93            1.5          100             192  \n",
       "1        93            1.5          100             192  \n",
       "2        93            1.5          100             192  \n",
       "3        93            1.5          100             192  \n",
       "4        93            1.5          100             192  \n",
       "5        93            1.5          100             192  \n",
       "6        93            1.5          100             192  \n",
       "7        93            1.5          100             192  \n",
       "8        93            1.5          100             192  \n",
       "9        93            1.5          100             192  \n",
       "10       93            1.5          100             192  \n",
       "11       93            1.5          100             192  \n",
       "12       93            1.5          100             192  \n",
       "13       93            1.5          100             192  \n",
       "14       93            1.5          100             192  \n",
       "15       93            1.5          100             192  \n",
       "16       93            1.5          100             192  \n",
       "17       93            1.5          100             192  \n",
       "18       93            1.5          100             192  \n",
       "19       93            1.5          100             192  \n",
       "20       93            1.5          100             192  \n",
       "21       93            1.5          100             192  \n",
       "22       93            1.5          100             192  \n",
       "23       93            1.5          100             192  \n",
       "24       93            1.5          100             192  \n",
       "25       93            1.5          100             192  \n",
       "26       93            1.5          100             192  \n",
       "27       93            1.5          100             192  \n",
       "28       93            1.5          100             192  \n",
       "29       93            1.5          100             192  \n",
       "30       93            1.5          100             192  \n",
       "31       93            1.5          100             192  \n",
       "32       93            1.5          100             192  \n",
       "33       93            1.5          100             192  \n",
       "34       93            1.5          100             192  \n",
       "35       93            1.5          100             192  \n",
       "36       93            1.5          100             192  \n",
       "37       93            1.5          100             192  \n",
       "38       93            1.5          100             192  \n",
       "39       93            1.5          100             192  \n",
       "40       93            1.5          100             192  \n",
       "41       93            1.5          100             192  \n",
       "\n",
       "[42 rows x 28 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breakfast = mcdonalds[mcdonalds['Category']=='Breakfast']\n",
    "breakfast"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the information that is given for both serving size and categories listed, it seems that McDonald's is making progress in offering more products, however, they are still lacking in the menu offerings for healthier food. With coffee and tea being the most offered, it has been determined that consumers can drink too much to get into the sugar and caffeine crash during the day."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Checking for NA Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 260 entries, 0 to 259\n",
      "Data columns (total 24 columns):\n",
      "Category                         260 non-null object\n",
      "Item                             260 non-null object\n",
      "Serving Size                     260 non-null object\n",
      "Calories                         260 non-null int64\n",
      "Calories from Fat                260 non-null int64\n",
      "Total Fat                        260 non-null float64\n",
      "Total Fat (% Daily Value)        260 non-null int64\n",
      "Saturated Fat                    260 non-null float64\n",
      "Saturated Fat (% Daily Value)    260 non-null int64\n",
      "Trans Fat                        260 non-null float64\n",
      "Cholesterol                      260 non-null int64\n",
      "Cholesterol (% Daily Value)      260 non-null int64\n",
      "Sodium                           260 non-null int64\n",
      "Sodium (% Daily Value)           260 non-null int64\n",
      "Carbohydrates                    260 non-null int64\n",
      "Carbohydrates (% Daily Value)    260 non-null int64\n",
      "Dietary Fiber                    260 non-null int64\n",
      "Dietary Fiber (% Daily Value)    260 non-null int64\n",
      "Sugars                           260 non-null int64\n",
      "Protein                          260 non-null int64\n",
      "Vitamin A (% Daily Value)        260 non-null int64\n",
      "Vitamin C (% Daily Value)        260 non-null int64\n",
      "Calcium (% Daily Value)          260 non-null int64\n",
      "Iron (% Daily Value)             260 non-null int64\n",
      "dtypes: float64(3), int64(18), object(3)\n",
      "memory usage: 48.8+ KB\n"
     ]
    }
   ],
   "source": [
    "mcdonalds.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d89eec8f60>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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S0LNnT7Ru3Rr/+c9/NNeZPHkyevTogYsXL8LKygoPHjxQag8AnDt3DvPmzUN+fj569eqF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\nRVGfgE6YFEVRFPUJ/g8euUQvC+wu5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d89eebd8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(mcdonalds.isnull(),yticklabels=False,cbar=False,cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No NA Values have been found in the McDonald's dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview of the Categories of Calories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1d8a16d2cc0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8a16d2d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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PKve9v8zu/PS82Z2dr2p2pxhPmX6SI0aM4PHHH+enn37ij3/8I2fOnGHWrFn+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\n6kmTa8K5hWYLf8rAk59J8Zt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hQgBsNhvjx4+nYcOG5X6e0SmkVTOFLjtnHCeoERxLaDUa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\nPIHm7AUDUnBWCHEgaKUmVJgQ9QjUyk33+H7YvHk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u897sSTXeQdqkmh6P/c+9hL1ufb+G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\nInnob7xsEDf0dqAXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8a16d20b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "sns.FacetGrid(data=mcdonalds, hue='Category', size=7).map(plt.scatter, 'Calories','Protein').add_legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Protein Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JOQAAgAKJOQAAgAKJOQAAgAKJOQAAgAKJOQAAgAKJOQAAgAKJOQAAgAINLeVNnU4nn/vc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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2908003a780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "ax = sns.boxplot(x='Category', y='Protein', data=mcdonalds)\n",
    "ax = sns.stripplot(x='Category', y='Protein', data=mcdonalds, jitter = True, edgecolor=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trans Fat Comparisons Based on Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x290805ef6a0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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583rX40iA3DkzBwAAkCExBwAAkCExBwAAkCExBwAAkCExBwAAkCExBwAAkCEx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\nBC+etdgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x290805ef8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.countplot(x='Category',data=mcdonalds, hue='Trans Fat',palette='seismic')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It turns out that Coffee & Tea has the least amount of trans fat. In comparison, their meats have the highest\n",
    "amounts of trans fat. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Looking for Cholesterol Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29080090f98>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QevXqI0mKixugwsLdJqcDAAAAYFeUuWbauPE1TZqUJEkyDEMOh0OS5HK5VVVV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\nAAAAAGx31cLcjTfeqEWLFrl+//bbb/XnP/9ZktS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AgIUIcwAAAABgIcIcAAAAAFiIMAcA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x290809f49b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "sns.countplot(x='Category',data=mcdonalds, hue='Cholesterol',palette='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the information that is given, it turns out that breakfast has the highest amounts of cholesterol, then it involves with their poultry too. Beverages have the least amount of cholesterol."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total Amount of Calories in Food in Correlation to Trans Fat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29080a34160>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mSQoNDVVOTo6cTqfCw0+/WT40NFROp7PY+KlrrSr7hEsH96WZHQMAAACAhdnP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\nIiINx8SPiIiIiIhIw/0/KXjk13ZVQKwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x290806fefd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.swarmplot(x='Category',y='Calories',data=mcdonalds, hue='Trans Fat',palette='magma')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Looking for Saturated Fats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29081588518>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AAACoRchTzY7dyQGvTiBgU2mpEdO4K1e+raysLA0cOKjR/mHDrtN9983Sc8/9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\nZt3N5JVI4loiIiIiI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RUVREVFAVBaWkpYWJh2V701f39/Xn31Vfbv34/RaKSpqQmA1atX\ns337dtauXUtUVFSna8FvJM5iW1JSQnl5OVlZWQA0NjZy2223YbFYOH78OMnJyUBznM+ePet0v0eO\nHOHDDz/EbDZTWFjIggULOH/+PMXFxbi5tW3yixcvZsyYMW1e+/zzz4mMjNTu1A0bNkx7Vq/lvEPz\nXXaj0UhdXd01iMa10bdv33bPYpw5c4Yff/wRgIEDB+Lh4QHQLhanTp0iLi4OgCFDhjBkyBA2btxI\nSUkJbm5u2qycxWLh0KFDvPvuu0DzDCiAr68vffr0AaBPnz7U19e32X9GRgbz589n8ODBJCUlcfDg\nQUaPHt1uBtTb2xuz2dzmtR9++EH7Oy8vj/Xr12Oz2Rg9erT2+uDBg4Hm68hms3UrXn8233//PUaj\nkdWrVwNw7Ngx5s2bh8lkIjs7G09PT6qqqtrc+QOc5ptz584REREBNLeLlnOzdOlSXnzxRXbu3Elw\ncDATJky4vh/yKnQUn5Y733fccQcAgYGB2Gw2brrpJqqrq1m0aBGenp7U1dXR2NjY7baekpLCli1b\neOSRRwgICNDi2aI7bbqqqorLly/zzDPPAM3X2dy5cxk6dKj2ntOnT3P33XcDEBkZqV2bznLhmDFj\nOH36NI899hhubm4sWLDg2gb5Ojh37hxTp06lqKioXU53Vu+ctdnO8pCvr2+7/9NV62gLZ/W0rq6u\nXfsJDQ3Fbrdz9uxZ9u3bxyuvvMKuXbs6rK8tNa+j/onVamXgwIEADB06lH379mGxWDh37hyzZ88G\nms/N999/f0Pmns5qanl5OcOGDUOn0+Hu7k5kZGSHz4ZXV1djtVpZuHAhAJcvX2bUqFH88ssvTvuQ\nLSubfkt/xhmLxUJBQQFbtmzB4XBgMBgwGAxUVVXx1FNPaXmx5Xxera5ydHh4OABeXl6EhoZqf9fX\n11NeXs6oUaMAMBqNhISEcObMGaxWq7Za4a677nL6fGNnfRtnucJoNLJs2TJWrFhBTU0N999/f5tt\nuhv3Q4cOMX36dOLi4mhoaGDbtm3k5ORgMpkYMGAA3t7eQHON/vXXX+nduzcFBQUYDAZqa2u1WTib\nzcbJkye1lRyVlZVUV1drtaS2tpbKysoua9KV/tzz5H8y/v7+2t86nQ6A4OBgJk+ejNlsZtu2bUya\nNAl3d3eef/55NmzYwKpVq7jpppu0gjJ27Fg2bdrEc889R1VVVZv9b9++naioKNatW8ekSZO0bXbv\n3k1WVhY7d+7km2++4YsvvkCv1+NwOK7TJ//jtY5tUFAQa9aswWw2s3jxYsaOHUtwcDDDhw/HbDbz\n6quvEhMT0+FyvMbGRu38xMbGUlNTQ2BgoPZaV4KDg/nqq69oampCKUVZWZlW6FovLQkPD2fr1q0U\nFRVx4sSJ3/vRr6lx48Zx4MABKisrgeZY5ObmYrFYADqNQUhICMeOHQOgrKxMW3r2yCOPsHTpUkwm\nE3a7neDgYGbPno3ZbOa5557TkmNX8W25seHl5cX8+fMpLS0lODj4N32+hoYG3nvvPfLz89mxYwd7\n9uzpcLB/Izp58iT//Oc/tVgFBQXh5eVFTk4OOTk55Obm0rt37zYd1EuXLjnNN6GhoRw9ehRoHmi0\n5Jtdu3aRlpbGzp07ASguLr7On/L36yg+Vy4LblFSUsL58+fJz89n0aJFXL58GaVUt9t6UVERM2bM\nwGw2M3DgQHbv3t1m/91p0zabjcWLF1NTUwNAv3798PX1bbPcNiQkRDtXX3/9tdbhcpYLDx8+TO/e\nvdm+fTsLFiwgPz//qmJ6vdXU1FBYWEivXr2c5nRn9c5Zm+0oD7XO0a3rpLP9uqqWehoWFtau/QDE\nxcWRl5dHaGgoXl5endbXlrzeUf8kMDCQ7777Dmj+IjRorqGhoaHs2LEDs9lMbGwsYWFhN2Tu6aym\nhoSEaEs1Gxsb+eKLL7j11lud7sfX15fAwEAKCgowm82kpKQwYsQIp31IHx8fbbur7c8EBQVhMpkw\nm81kZmZy77338sknn2Cz2Vi/fj0LFy6kvr7+mt30+K05urWQkBCOHDkCNOcJi8VC//796d27t9bH\nKisr05bO6nQ67fruLB7OcoXVauX48eO88MILbN26lby8vDYD3e7GfceOHbz99ttA89L81oNNZ8eU\nnZ3NE088wZo1axg0aJAWd39/f15++WW+++47SkpK6N+/P3369GH79u2YzWYeeughoqKiuqxJV5KZ\nvC4cOnSI5ORk9Ho9tbW1LFmyhD179mj/npCQQEZGBg899BA1NTUkJSVhNBoZMmQI8fHxuLm54eXl\nhdVqpX///kDzyUxLS2PZsmW89NJL2r7GjRvHqlWr2LdvH7169aJHjx40DeUzwwAAB9dJREFUNDQQ\nFhZGUlISPXv2JCAggMjISIxGI5s3byY8PJzJkydf97hcC85iazAYyMzMxGQyac8XZWdnc9ttt1Fa\nWkpSUhJ1dXVMmDChw3XII0eO5LPPPiMhIQGlFPHx8VRUVFBYWMisWbO6PK6wsDBiYmJITEzE4XAw\ndOhQJkyY4HQgZzAYWLlyJSaTicLCQu3i/l8xGo3k5uaSkZGhPb81btw4kpKSKC0t7XTblJQUli1b\nRlFREQA5OTns3bsXaP7mp/fff59t27aRkpLC8uXL2b17NzU1NaSmpnbr2J555hmeffZZNm3ahNFo\n5IUXXmDz5s2MGTOm23Hz8PDA29ubBx98EIPBwN///nf69u3brW1vBNHR0ZSXlxMXF4enpydKKdLT\n0ykrK2PWrFncfPPN+Pv7Y7VatW06yjexsbF89tlnzJw5k759+2qzGxERETz66KP07NkTT09PreN3\nI+goPr169XL6/oiICAoKCpg1axY6nY4BAwZgtVq73dZHjhxJRkYGN998M3q9XnuGpkV32nR4eLj2\nrYcGgwG73c7MmTPbDAYTExNJT08nMTGR4OBgbQDoLBf6+PiwaNEi/vOf/9DU1MTjjz9+zeN8rbXO\n9Xa7nbS0NCZOnEhubm67nO6s3tXU1LRrs2PHju0yDw0aNEirk87260qc1dNBgwa1az/Q/BxpdnY2\nmzdvBuCee+7psr521D9ZuXIly5Ytw9PTE3d3dwICArj99tsZOXIkiYmJNDQ0EBERoc063Gi5p7Oa\nqtPpKC0tJT4+nsbGRiZNmkR4eDgnT55stx+9Xs/y5cuZP38+Sil69uzJ2rVrGTp0aLs+ZOsbFVfb\nn1m6dClZWVnU19fT0NDAihUrCAgIYMuWLVpe7N+/P1arVVvtcTV+a45u7cEHH2TFihUkJiZSX19P\namoqfn5+rFq1imeffRalFD169CAnJwdoXmU1f/78LnOgsz7LLbfcwoULF0hISECv1zNnzpw2M3Td\njXtWVhZZWVm88sorGAwGfH19yczMpLGx0emx3H///Tz55JN4eXkRGBioPScIaNfo3Llz2b17N7Nn\nzyY5ORm73U6/fv2IiYmhoaGh05p0JZ1ytTULQgghhBDiD/faa68RExPD3/72NzZs2IC7u3u3b/wJ\nIf5YMpMnhBBCCCF+Mz8/P+bMmYOnpye9evUiNzf3f31IQoj/JzN5QgghhBBCCOFC5ItXhBBCCCGE\nEMKFyCBPCCGEEEIIIVyIDPKEEEIIIYQQwoXIIE8IIYTLq6mpISsriylTpjBt2jSSk5M5fvx4p9u0\n/Di0EEIIcaORb9cUQgjh0hwOB/PmzWP48OHs3bsXNzc3Dh06xLx583jnnXe03xC8Ule/LSmEEEL8\nWclMnhBCCJd2+PBhrFYrTzzxhPaDtyNGjGD16tU4HA4yMjKIj49n/PjxzJ07l8uXL7Nq1SoAZs6c\nCUBJSQlxcXFMnz6d1NRU7UdsDx8+zNSpU5k+fTqZmZna7N+pU6dITk5m6tSpxMfH89VXXwGwZMkS\nUlJSiImJ4YMPPiAhIUE7zj179rBy5crrFhchhBCuSwZ5QgghXNrXX3/NnXfeiV7ftuTdfffdVFRU\n4O7uzq5duyguLqa+vp5PP/2UjIwMAAoLC6murmb9+vW8/PLL7N27l3/84x+sW7eOxsZG0tPTycvL\n02YIWyxevJjk5GTeeustli5dypNPPklDQwMAPj4+vPvuu4wfP54LFy5QWVkJNA/yYmNjr1NUhBBC\nuDJZrimEEMKl6fV6OvpJ2LvuugsfHx9ee+01KioqOH36NHV1dW3e8+WXX3L+/HkefvhhoHn5p7e3\nNxaLBT8/P26//XYA4uLiyM7Opra2lsrKSqKjowGIiorC29ubiooKACIiIgDQ6XTMmDGDoqIiYmNj\nuXjxIpGRkX9IDIQQQvy1yCBPCCGESxs8eDD//ve/UUqh0+m01/Pz84mIiGDjxo08/PDDxMbG8tNP\nP7UbENrtdoYMGcKWLVsAqK+vp7a2FqvVisPhaPf/KaXa7UMphd1uB8BgMGivz5gxg7lz5+Lh4cG0\nadOu2WcWQgjx1ybLNYUQQri0YcOG4efnx6ZNm7SB1oEDB3jjjTc4cOAAMTExPPDAA/j7+1NWVqa9\np0ePHjQ1NREZGcnRo0c5deoUAAUFBaxdu5bg4GD++9//cvLkSQDeeustAIxGIwMGDGD//v0AHD16\nFJvNxsCBA9sdW79+/QgMDOT111+XQZ4QQohrRmbyhBBCuDSdTkdBQQGrV69mypQpuLm54evry9at\nW+nRowdPP/007733Hh4eHkRFRfHDDz8AMH78eKZNm8Ybb7xBTk4OCxcuxOFwEBAQQF5eHh4eHqxd\nuxaTyYRerycoKEibpcvLyyMzM5ONGzfi7u7Oxo0b8fDwcHp89913H/v37ycgIOC6xUQIIYRr06mO\nHlQQQgghRIccDgfr1q0jNTUVT09P/vWvf1FVVcWSJUu6vY+mpibS09OZNGmS9gyfEEIIcbVkJk8I\nIYT4HfR6PT4+PsTFxeHu7k6/fv3Izs7u9vZKKUaPHs2oUaOYMGHCH3ikQggh/mpkJk8IIYQQQggh\nXIh88YoQQgghhBBCuBAZ5AkhhBBCCCGEC5FBnhBCCCGEEEK4EBnkCSGEEEIIIYQLkUGeEEIIIYQQ\nQriQ/wOnb/lFCy0GCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x290814c4630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "sns.swarmplot(x='Category',y='Sugars',data=mcdonalds, hue='Saturated Fat',palette='bwr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It turns out that the smoothies have the highest amount of sugar and a high amount of saturated fat. It is unusual that for a smoothie that is made from scratch, it allows the consumer to choose the correct ingredients and to make a healthier option."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Protein and Saturated Fat Correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d8a18c79e8>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AAAALIswBAAAAgAVxzxwAAACAc0PQkPu1ctn2+hW9IEvBEUWS25v0sEVFP5DH\nc3ycrKxsTZnycKy2evVKLVnygux2uwoKClVYeGPS/c4UYQ4AAACA5TnfWyHfnGI5Pj15z5zrtXId\nLZ6j0NWJ3zN37NgxmaapsrJFzWrhcFilpXO1eHGl3G63xo4dpfz8weratVvC/VqDbZYAAAAArC1o\nNAtykuT4tEa+OcVS0Eh46O3bt6mhoUH33Xe3JkwYo+rqTbHazp07lJ3dU+np6XI6nerXr7+qqjYk\n3Ku1CHMAAAAALM39WnmzIHeC49MauX5VkfDYLpdLt956u+bOLdP99z+oxx6bpnA4LEkyDEM+ny/2\nrcfjlWEcTbhXa7HNEgAAAICl2fb649btp6nH07NnL/Xo0UMpKSnq1eside7cWfv379MFF1wor9er\nQODkql8g0DTctTdW5gAAAABYWvSCrLj1yGnq8bzxxu9UWvq0JGnfvjoZhqFu3c6TJPXufbF2796l\nI0cOKxQKqapqg/Ly+iXcq7VSTNM0v7RurVRXV9/RUwAAAABwtgsa6nJbfotbLcO9cnXw52sktyeh\noUOhkEpKHtHevXuUkpKisWPHq7a2VsFgQMOGDY+dZhmNRlVQUKgRI25O9tc0kZmZdsoaYQ4AAACA\n5bV0mmW4V27Sp1l2NMIcAAAAgHNf0JDrVxWy7/UrckGWGoYXJbwid7YgzAEAAACABcULcxyAAgAA\nAAAWRJgDAAAAAAsizAEAAACABRHmAAAAAMCCHB09AQAAAABoEw2G3MvLZdvvV7RbloL/WSS5vEkP\nu3RphVavXqlQKKThw2/S9773/VjtxD1zdrtdBQWFKiy8Mel+Z4owBwAAAMDynB+tkO/5Yjn8J++Z\ncy0v19ExcxQakPg9c+vXf6RNmzZqwYL/UUNDg15+eWmsFg6HVVo6V4sXV8rtdmvs2FHKzx+srl27\nJfVbzhTbLAEAAABYW4PRLMhJksNfI9/zxVKDkfDQH364Vrm5fTRlyv164IH79K1vfTtW27lzh7Kz\neyo9PV1Op1P9+vVXVdWGhHu1FmEOAAAAgKW5l5c3C3InOPw1cv2+IuGxDx8+pC1b/qoZM2aruPhB\nPfroNJ24qtswDPl8vti3Ho9XhnE04V6txTZLAAAAAJZm2++PW7fvi1+PJz29s3r16i2n06levXor\nNbWTDh06qC5dusrr9SoQOLnqFwg0DXftjZU5AAAAAJYW7ZYVtx45L349nn79/k0ffPCeTNPUvn11\namgIKj3gP4f7AAAgAElEQVS9sySpd++LtXv3Lh05clihUEhVVRuUl9cv4V6tlWKeWCM8C9XV1Xf0\nFAAAAACc7RoMdRmX3+JWy3BWrg6WrZFcnoSHf+65Z7R+/Z8VjUZ155136/DhwwoGAxo2bHjsNMto\nNKqCgkKNGHFzMr+kmczMtFPWCHMAAAAALK+l0yzDWblJn2bZ0QhzAAAAAM59DYZcv6+QfZ9fkfOy\n1HBDUVIrcmcDwhwAAAAAWFC8MMcBKAAAAABgQYQ5AAAAALAgwhwAAAAAWBBhDgAAAAAsyNHREwAA\nAACANnHMkPtP5bId9CvaJUvBfy+SOnmTGnL58te1fPnrkqTGxkZt3/43/fa3bykt7fjBJCfumbPb\n7SooKFRh4Y1J/4wzxWmWAAAAACzPWb1CvpeL5fjsc/fMnZ+ro7fOUSivbe6Ze+qp2erT5xINGzb8\n+PjhsH7wg5u0eHGl3G63xo4dpSefnKeuXbu1ST+J0ywBAAAAnMuOGc2CnCQ5PquR7+Vi6ZiRdIst\nW/6qHTtqYkFOknbu3KHs7J5KT0+X0+lUv379VVW1IeleZ4owBwAAAMDS3H8qbxbkTnB8ViPXyoqk\ne1RWVqioaHSTd4ZhyOfzxZ49Hq8M42jSvc4UYQ4AAACApdkO+uPW7aepn059fb0+/fQTff3rA5q8\n93q9CgROrvoFAk3DXXsjzAEAAACwtGiXrLj1yGnqp/OXv6zXgAFXNnvfu/fF2r17l44cOaxQKKSq\nqg3Ky+uXVK/W4DRLAAAAAJYW/PciuU6x1TJ8fq4aBhclNf6nn36irKzs2PPbb7+pYDCgYcOGa9y4\n+zRx4nhFo1EVFBQqM/P8pHq1BqdZAgAAALC8L+M0y44Q7zRLwhwAAACAc8MxQ66VFbIf9CvSJev4\nilwnT0fPKimEOQAAAACwIO6ZAwAAAIBzDGEOAAAAACyIMAcAAAAAFkSYAwAAAAAL4p45AAAAAOeG\nRkPudeWyHfYr2jlLwSuLpFRvUkOGw2HNnPmw9uyplc1m0wMPTNNFF/WO1VevXqklS16Q3W5XQUGh\nCgtvTPJHnDnCHAAAAADLc25bId//Fcux/+Q9c64Py3X0e3MUuiTxe+bef3+1IpGInn++XOvWrdWi\nRc+qpGSOpONBr7R0rhYvrpTb7dbYsaOUnz9YXbt2S/r3nAm2WQIAAACwtkajWZCTJMf+Gvn+r1hq\nNBIeumfPixSJRBSNRmUYhhyOk+thO3fuUHZ2T6Wnp8vpdKpfv/6qqtqQcK/WYmUOAAAAgKW515U3\nC3InOPbXyLWuQg3fGpfY2G639uzx67bbbtLhw4f05JPzYjXDMOTz+WLPHo9XhnE0oT6JYGUOAAAA\ngKXZDvvj1u1H4tfj+cUvfq6rrhqkV175lZYs+blKSh7RsWPHJEler1eBwMlVv0Cgabhrb4Q5AAAA\nAJYW7ZwVtx5Jj1+PJy0tXV7v8YCWnt5Z4XBY0WhUktS798XavXuXjhw5rFAopKqqDcrL65dwr9ZK\nMU3T/NK6tVJdXX1HTwEAAADA2a7RUJdn81vcahnulquDd6+RUj0JDR0IBPTEE49p//59CoVC+q//\nulWSFAwGNGzY8NhpltFoVAUFhRox4uakfsoXZWamnbJGmAMAAABgeS2dZhnulpv0aZYdjTAHAAAA\n4NzXaMi1rkL2I35F0rPUcGVRwityZwvCHAAAAABYULwwxwEoAAAAAGBBhDkAAAAAsCDCHAAAAABY\nEGEOAAAAACzI0dETAAAAAIA2ETLk3lwum+FX1Jul4FeLJKc3qSEbGxv1+OOPyu//h7xeryZOfEA9\ne/aK1U/cM2e321VQUKjCwhuT/RVnjDAHAAAAwPKcn6yQb3WxHIdP3jPn2lyuo/lzFLoo8XvmXn/9\n13K7PVq0aIk+/XSn5s17UnPnlkmSwuGwSkvnavHiSrndbo0dO0r5+YPVtWu3pH/PmWCbJQAAAABr\nCxnNgpwkOQ7XyLe6WAoZCQ+9Y8cOffObV0uSevXqrZ07d8RqO3fuUHZ2T6Wnp8vpdKpfv/6qqtqQ\ncK/WIswBAAAAsDT35vJmQe4Ex+EauTZXJDz2JZd8Re+9t0qmaaq6epP27atTJBKRJBmGIZ/PF/vW\n4/HKMI4m3Ku1CHMAAAAALM1m+OPW7aepx1NQUCiv16u77vpvrVz5B1166WWy2+2SJK/Xq0Dg5Kpf\nINA03LU3whwAAAAAS4t6s+LWI6epx7Nly1/1jW9cpQUL/kf/8R/XKisrO1br3fti7d69S0eOHFYo\nFFJV1Qbl5fVLuFdrpZimaX5p3Vqprq6+o6cAAAAA4GwXMtTlF/ktbrUMd87VwZvXSE5PQkMfOnRI\nDz88RQ0NQfl8aXrwwelav/7PCgYDGjZseOw0y2g0qoKCQo0YcXOyv6aJzMy0U9YIcwAAAAAsr6XT\nLMOdc5M+zbKjEeYAAAAAnPtChlybK2Q3/Ip4s9Tw1aKEV+TOFoQ5AAAAALCgeGGOA1AAAAAAwIII\ncwAAAABgQYQ5AAAAALAgwhwAAAAAWJCjoycAAAAAAG0ibMj993LZGvyKurIUzCmSHN6kh928uVoL\nFsxXWdki7d69SyUljyglJUU5ObmaOPEB2Wwn18ii0aieemqWtm/fJqfTqcmTp6tHj55Jz6ElrMwB\nAAAAsDznnhXq8k6+fNVT5dn+rHzVU9XlnXw596xIatxly17U7Nkz1NjYKEkqLZ2rO+4Yq+eee0Gm\naWrVqj81+X7Vqj+qsbFRCxdWaMyY8Sorm5dU/3gIcwAAAACsLWzI95diOYyaJq8dRo18fymWwkbC\nQ2dn91BJyZzY89atW/S1r31DkvTNb16tjz76sMn3GzdWaeDAQZKkvLy+2rLl44R7nw5hDgAAAICl\nuf9e3izIneAwauTaUZHw2EOGDJXDcfKv00zTVEpKiiTJ4/HKMI42+d4wDHm9vtizzWZTOBxOuH88\nhDkAAAAAlmZr8Met24Px663q9bm/jwsEDPl8viZ1r9erQCAQezZNs0kYbEuEOQAAAACWFnVlxa1H\n3PHrrXHJJZdq/fqPJElr176n/v2/1qTet29/rV27RpJUXb1JOTl92qz3FxHmAAAAAFhaMKdIYW9u\ni7WwN1cNFxe1Wa9x4+5Vefki3XnnTxQKhTRkyFBJ0owZD2nPnj0aPPgapaamasyYIpWWztWECRPb\nrPcXpZimabbb6Emqq6vv6CkAAAAAsADnnhXNDkEJe3N1tP8chS68tgNnlpzMzLRT1ghzAAAAAM4N\nYUOuHRWyB/2KuLOOr8g5PB09q6QQ5gAAAADAguKFOf5mDgAAAAAsiDAHAAAAABZEmAMAAAAACyLM\nAQAAAIAFEeYAAAAAnBsihtz+Unk/eVBuf6kUMdpk2M2bqzVu3Ogm7+bPf0q/+c0vm30bjUY1Z87j\nuvPOn2jcuNHavXtXm8yhJYQ5AAAAAJbnPLRCXTbly/fpVHlqn5Xv06nqsilfzkMrkhp32bIXNXv2\nDDU2NkqSDh48qJ/+dIJWr17Z4verVv1RjY2NWriwQmPGjFdZ2byk+sdDmAMAAABgbRFDvp3FcjTU\nNHntaKiRb2dxUit02dk9VFIyJ/YcDAZUVDRa3/nOf7b4/caNVRo4cJAkKS+vr7Zs+Tjh3qdDmAMA\nAABgae695c2C3AmOhhq5PqtIeOwhQ4bK4XDEnrOysvXVr+ad8nvDMOT1+mLPNptN4XA44f7xEOYA\nAAAAWJot5I9btzfGr7clr9erQCAQezZNs0kYbEuEOQAAAACWFnVmxa1HUuPX21Lfvv21du0aSVJ1\n9Sbl5PRpt16EOQAAAACWFrygSGFXbou1sCtXDecXtfscZsx4SHv27NHgwdcoNTVVY8YUqbR0riZM\nmNhuPVNM0zTbbfQk1dXVd/QUAAAAAFiA89CKZoeghF25Otp7jkIZ13bgzJKTmZl2yhphDgAAAMC5\nIWLI9VmF7I1+RVKzjq/I2T0dPaukEOYAAAAAwILihTn+Zg4AAAAALIgwBwAAAAAWRJgDAAAAAAsi\nzAEAAACABbXPVeQAAAAA8GWLGnLXl8sW9ivqyFIwrUiyeZMedvPmai1YMF9lZYu0bdtWzZs3Rzab\nTampqZo27VF17drt5BSiUT311Cxt375NTqdTkydPV48ePZOeQ0tYmQMAAABgec7ACnXx58t3cKo8\n9c/Kd3Cquvjz5QysSGrcZcte1OzZM9TY2ChJeuaZp3TffcUqK1ukwYOv0bJlLzb5ftWqP6qxsVEL\nF1ZozJjxKiubl1T/eAhzAAAAAKwtash3oFiOcE2T145wjXwHiqWokfDQ2dk9VFIyJ/b8yCOP65JL\nLpUkRSIRpaZ2avL9xo1VGjhwkCQpL6+vtmz5OOHep9Ou2ywXLlyod999V6FQSLfeequuuuoqTZ48\nWSkpKbrkkkv08MMPy2YjTwIAAABInLu+vFmQO8ERrpGrvkINncclNPaQIUNVW+uPPZ933nmSpE2b\n/qJf/eoXKitb3OR7wzDk9fpizzabTeFwWA5H20evdktSH3zwgTZs2KCXX35ZS5cu1Z49e/TEE0/o\n3nvv1c9//nOZpql33nmnvdoDAAAA+BdhC/vj1u2nqbfWO++8rZ/97Ak9+eTT6tKlS5Oa1+tVIBCI\nPZum2S5BTmrHMLd69Wp95Stf0d13360xY8ZoyJAh2rx5s6666ipJ0uDBg/Xee++1V3sAAAAA/yKi\njqy49chp6q3x1lvL9dprv1Bp6UJlZ/doVu/bt7/Wrl0jSaqu3qScnD5t1vuL2m2b5cGDB+X3+/X8\n889r9+7dGjt2rEzTVEpKiqTjibW+vj7uGF26eORw2NtrigAAAADOBV3vkQJLpGPbmtc6XaK0i+9R\nmt2T8PDHjnnldNrVtatH8+c/pe7du+uRRx6UJF155ZWaMGGCJk2apHvvvVcjRhRq06b1Gj/+Dpmm\nqccff1yZmWkJ946n3cJcRkaGcnJylJqaqpycHHXq1El79uyJ1Q3DUHp6etwxDh4MxK0DAAAAgCQ5\nO89udghK2JGro51nK3QgIin+QlI8nTp11rPP/o8OHAjojTea/6lYXV29iounS5L27zc0fnxxs3qi\n4gXBdttm+Y1vfEOrVq2SaZrau3evgsGgBg0apA8++ECStHLlSg0YMKC92gMAAAD4FxLyXKuDWatV\n3+VxBdLGqb7L4zqYtUYhz7UdPbV2k2Kaptlegz/55JP64IMPZJqm7rvvPvXo0UPTp09XKBRSTk6O\nZs6cKbv91Nsok0mwAAAAAGB18Vbm2jXMJYswBwAAAOBfWYdsswQAAAAAtB/CHAAAAABYEGEOAAAA\nACyo3a4mAAAAAIAvlWnIHSmXTX5FlaWgvUhK8SY97ObN1VqwYL7KyhZpx46/68knSySZ6tGjlx54\nYJocjpOxKhqN6qmnZmn79m1yOp2aPHm6evTomfQcWsLKHAAAAADLc0ZXqEsoX77oVHmiz8oXnaou\noXw5oyuSGnfZshc1e/YMNTY2SpIWLXpWd955txYsKJckrVmzqsn3q1b9UY2NjVq4sEJjxoxXWdm8\npPrHQ5gDAAAAYG2mIV+4WA7VNHntUI184WLJNBIeOju7h0pK5sSeZ858Uv/2b19XKBTS/v375fP5\nmny/cWOVBg4cJEnKy+urLVs+Trj36RDmAAAAAFiaO1LeLMid4FCNXJGKhMceMmRok22Udrtde/bU\n6vbbb9bhw4fUp88lTb43DENe78mAZ7PZFA6HE+4fD2EOAAAAgKXZ5I9bt5+m3loXXthdr7zya33/\n+yNUWtp0G6XX61UgEIg9m6bZJAy2JcIcAAAAAEuLKituPXKaems88MB92rXrU0mSx+ORzdY0UvXt\n219r166RJFVXb1JOTp826/1FnGYJAAAAwNKC9iK5oi1vtQwrVw32ojbr9cMf/liPP/6IHA6nXC6X\nHnhguiRpxoyHdMcdd2nw4Gu0bt0HGjOmSKZpasqUh9us9xelmKZpttvoSaqrq+/oKQAAAACwAGd0\nRbNDUMLK1VHHHIVs13bgzJKTmZl2yhphDgAAAMC5wTTkilTILr8iyjq+Ipfi6ehZJYUwBwAAAAAW\nFC/McQAKAAAAAFgQYQ4AAAAALIgwBwAAAAAWRJgDAAAAAAsizAEAAAA4RxhydyqV1/2g3J1KJRlt\nMurmzdUaN250k3dvv/2m7rzzJ82+jUajmjPncd155080btxo7d69q03m0BIuDQcAAABgeU7HCvm8\nxXLYT94z53KV66gxR6Fw4vfMLVv2ot56a7lcLnfs3d/+tkVvvPFbtXQxwKpVf1RjY6MWLqxQdfUm\nlZXN06xZcxPuHw8rcwAAAAAszmgW5CTJYa+Rz1usZFbosrN7qKRkTuz58OFDWrjwOU2Y8NMWv9+4\nsUoDBw6SJOXl9dWWLR8n3Pt0CHMAAAAALM3dqbxZkDvBYa+Rq1NFwmMPGTJUDsfxDY2RSESzZs3Q\n+PH3yeNp+TJywzDk9fpizzabTeFwOOH+8bDNEgAAAICl2Wz+uHX7aepnauvWj7Vr1y797GdPqLGx\nUTt37tAzzzyle+45uUrn9XoVCARiz6ZpxsJgWyPMAQAAALC0aDQrbj1ymvqZuuKKPL300i8kSbW1\nfj388JQmQU6S+vbtrzVrVmno0OtUXb1JOTl92qR3S9hmCQAAAMDSgseKFI7ktlgLR3LVcKyo3ecw\nY8ZD2rNnjwYPvkapqakaM6ZIpaVzNWHCxHbrmWK2dATLWaKurr6jpwAAAADAAlo6zTIcyU36NMuO\nlpmZdsoaYQ4AAADAOcKQq1OF7Da/ItGsf67ItXxQiVUQ5gAAAADAguKFOf5mDgAAAAAsiDAHAAAA\nABZEmAMAAAAACyLMAQAAAIAFcWk4AAAAgHNEUG73/8pm+0zR6PkKBv9LkjvpUTdvrtaCBfNVVrZI\nf/vbFk2adJ969OgpSbrxxps0dOj1sW+j0aieemqWtm/fJqfTqcmTp8e+bWuEOQAAAACW53Sukc83\nWw7Hp7F3LtcvdfToAwqFvpXwuMuWvai33loul+t4KNy6dYtuueUHuvXWH7b4/apVf1RjY6MWLqxQ\ndfUmlZXN06xZcxPuHw/bLAEAAABYXLBZkJMkh+NT+XyzJQUTHjk7u4dKSubEnrdu/Vjvv79ad999\nh5544jEFAkaT7zdurNLAgYMkSXl5fbVly8cJ9z4dwhwAAAAAS3O7/7dZkDvB4fhULtcvEx57yJCh\ncjhObmi8/PKv6q677tGzzy5WVla2yssXN/neMAx5vb7Ys81mUzgcTrh/PIQ5AAAAAJZms30Wt263\nx6+3xuDB1+iyyy6P/Xvbtq1N6l6vV4FAIPZsmmaTMNiWCHMAAAAALC0aPT9uPRKJX2+NiRPH6a9/\nrZYk/fnPH+rSSy9rUu/bt7/Wrl0jSaqu3qScnD5t1vuLOAAFAAAAgKUFg/8ll+uXLW61DId7qaHh\npjbrdf/9D+rpp5+U3e5Qt27dNGnSVEnSjBkP6Y477tLgwddo3boPNGZMkUzT1JQpD7dZ7y9KMU3T\nbLfRk1RXV9/RUwAAAABgAS2dZhkO90r6NMuOlpmZdsoaYQ4AAADAOSIol+uXsts/UyRy/j9X5JK/\nZ64jEeYAAAAAwILihTkOQAEAAAAACyLMAQAAAIAFEeYAAAAAwIIIcwAAAABgQdwzBwAAAOAc0SC3\n+23ZbAcUjXZVMHi9JFfSo27eXK0FC+arrGyRDh48oNmzZ6q+vl7RaETTpj2m7OwesW+j0aieemqW\ntm/fJqfTqcmTp6tHj55Jz6ElhDkAAAAAlud0bpDPVy6Hozb2zuX6fzp6tEih0NcSHnfZshf11lvL\n5XIdv+Lguefm67rrbtDQoddp/fqP9MknO5uEuVWr/qjGxkYtXFih6upNKiubp1mz5ib+w+JgmyUA\nAAAAi2toFuQkyeGolc9XLqkh4ZGzs3uopGRO7HnTpr+orm6v7rnnLr399u/1ta99o8n3GzdWaeDA\nQZKkvLy+2rLl44R7nw5hDgAAAIClud1vNwtyJzgctXK5ViQ89pAhQ+VwnNzQWFvrV1paup555jld\ncMGFWrbsxSbfG4Yhr9cXe7bZbAqHwwn3j4cwBwAAAMDSbLYDcet2+/4269W5c4by8wdLkr71rW9r\ny5a/Nql7vV4FAoHYs2maTcJgWyLMAQAAALC0aLRr3Hok0q3NevXr11/vv79GklRVtUEXX5zbpN63\nb3+tXXu8Xl29STk5fdqs9xcR5gAAAABYWjB4vcLh7i3WwuHuami4rs16jRt3n9588w2NGVOkDz54\nX7ff/hNJ0owZD2nPnj0aPPgapaamasyYIpWWztWECRPbrPcXpZimabbb6Emqq6vv6CkAAAAAsICW\nTrMMh7snfZplR8vMTDtljTAHAAAA4BzRIJdrhez2/YpEuv1zRa5TR08qKfHCHPfMAQAAADhHuNTQ\n8L2OnsSXhr+ZAwAAAAALIswBAAAAgAUR5gAAAADAgghzAAAAAGBBHIACAAAA4BzRKLf7Q9lsRxSN\npisYvEpSatKjbt5crQUL5qusbJEefvhB7d+/X5K0Z0+tvvrVPD366BOxb6PRqJ56apa2b98mp9Op\nyZOnq0ePnknPoSWEOQAAAACW53T+TT7f/8nh2B9753J9qKNHv6dQ6CsJj7ts2Yt6663lcrnckhQL\nbkeOHNGECWM0fvxPm3y/atUf1djYqIULK1RdvUllZfM0a9bchPvHwzZLAAAAABbX2CzISZLDsV8+\n3/9Jakx45OzsHiopmdPsfXn5Qt10080677zzmrzfuLFKAwcOkiTl5fXVli0fJ9z7dAhzAAAAACzN\n7f6wWZA7weHYL5drXcJjDxkyVA5H0w2NBw8e0EcfrdMNN/x/zb43DENery/2bLPZFA6HE+4fD2EO\nAAAAgKXZbEfi1u32w23a7w9/eEfXXfcd2e32ZjWv16tAIBB7Nk2zWRhsK4Q5AAAAAJYWjabHrUci\nndu030cffahvfvNbLdb69u2vtWvXSJKqqzcpJ6dPm/b+PMIcAAAAAEsLBq9SONytxVo43E0NDVe2\nab9PP/1EWVnZTd7NmPGQ9uzZo8GDr1FqaqrGjClSaelcTZgwsU17f16KaZpmu42epLq6+o6eAgAA\nAAALaOk0y3C4W9KnWXa0zMy0U9YIcwAAAADOEY1yudbJbj+sSKTzP1fkkr9nriPFC3PcMwcAAADg\nHJGqhob/n707D5Oiuvc//qmq7upttmYRZRFZRFARXBF3jaJRiZqocUmMGo1LTPSa3JgQRRI1atBE\nDYqan/Ea45IYjRfjmqhRBEFxQ1G54hoQhoHZp/eq+v0BaWhmGIZhZmq65/16Hp8n53R19bdPinrq\nM9WnTttz2UoRc+YAAAAAoAgR5gAAAACgCBHmAAAAAKAIEeYAAAAAoAjxABQAAAAAJSKrSGSpTDMh\n140qmdxFUnCb97pkyXuaPfs2zZp1tz76aKlmzrxelmVp2LAd9dOfXiXT3HCPzHVd3XzzDVq27CMF\ng0H99KdXaejQYdtcQ1u4MwcAAACg6AWDyxWPz1FZ2euKRpeorOx1xeNzFAwu36b9PvDAfbrxxmuU\nyWQkSX/4w+91zjnnafbse5TNZjV//isF28+d+y9lMhnddde9uvDCH2jWrN9u0+e3hzAHAAAAoMhl\nVVa2UIFAY0FvINCosrKFkrKd3vOQIUN13XUz8+0xY3ZRY2OjPM9TItGiQKDwx46LF7+tSZMmS5J2\n3328Pvzwg05/9pYQ5gAAAAAUtUhkaasg9x+BQKPC4aWd3vdhh32lILANHTpMt9xyk84882TV1tZq\nzz33Lti+paVFsVhZvm2apnK5XKc/vz2EOQAAAABFzTQT7b5uWe2/vjVuvfVm3X777/Xgg4/qmGOO\n06xZtxS8HovFlEhs+DzP81rdvesqhDkAAAAARc11o+2+7jjtv741KioqFIvFJEkDBgxUU1PhHcHx\n4ydowYJ5kqT33ntXI0eO7rLP3hRPswQAAABQ1JLJXRQOt/1Ty1yuQqnU2C77rCuuuEozZkyTZQUU\nCAR0xRVXSpKuuWa6zj//Yh1yyOF6/fWFuvDCc+V5nqZNu7rLPntThud5XrftfRvV1DT5XQIAAACA\nIhAMLm/1EJRcrkLNzZOUzQ71sbJtM3Bg+WZf484cAAAAgKKXzQ5VXd0ghcNLZVkJOU50/R250o08\npfvNAAAAAPQxQaVSu/tdRI/hASgAAAAAUIQIcwAAAABQhAhzAAAAAFCECHMAAAAAUIQIcwAAAABK\nhKNIZIVisU8ViayQ5HTJXpcseU+XXPI9SdLSpR/q/PPP0sUXn6ff/vbXcl23YFvXdTVz5q90wQXn\n6JJLvqfly//dJTW0hTAHAAAAoOgFg3WKx99RWdnnikZXqqzsc8Xj7ygYrNum/T7wwH268cZrlMlk\nJEm//vV1+uEPf6Q77vh/isXK9I9/PFOw/dy5/1Imk9Fdd92rCy/8gWbN+u02fX57CHMAAAAAipyj\nsrJPFQikCnoDgZTKyj7VttyhGzJkqK67bma+XVOzWuPHT5AkjR8/QYsXv12w/eLFb2vSpMmSpN13\nH68PP/yg05+9JYQ5AAAAAEUtElnVKsj9RyCQUji8qtP7PuywrygQ2LA89+DBQ/TWW29IkubNm6tU\nKlmwfUtLi2KxsnzbNE3lcrlOf357CHMAAAAAipppZtp93bLaf31rTJs2Xfff/z+69NKLFI/HVVlZ\nVfB6LBZTIpHItz3PKwiDXYkwBwAAAKCoua7d7uuO0/7rW2P+/Fd09dXX6NZbZ6uxsUH77jup4PXx\n4ydowYJ5kqT33ntXI0eO7rLP3lT3RESgh5lmRp4neV7X/UMFAABAcUgmt1c4XN3mTy1zubBSqe27\n7LOGDt1Rl156scLhsPbcc29NnnyQJOmaa6br/PMv1iGHHK7XX1+oCy88V57nadq0q7vsszdleJ7n\ndXjdkugAACAASURBVNvet1FNTZPfJaDXc1Ve/pHC4bXyPCmVGqTm5pGSDL8LAwAAQA8KButaPQQl\nlwuruXmEstm4j5Vtm4EDyzf7GnfmUNRCoTUKh9dKkgxDikSqlU73VzZbtYV3AgAAoJRks3HV1VUo\nHF4ly8rIcez1d+Qsv0vrNoQ5FLVAINmqz7KShDkAAIA+yVIqNcTvInoMD0BBUUun49r4h8KeZyiT\nIcgBAACg9HFnDkUtl6tQY+MYRaMr5XmmEokhct2I32UBAAAA3Y4wh6KXyQxQJjPA7zIAAACAHsXP\nLAEAAACgCHFnDgAAAECJ8BSJJGSarlzXVDIZ1bYsWZXL5XT99b/QypUrlc1m9J3vfFc77TRS1103\nQ4ZhaOTIUbr88itkmhvukbmuq5tvvkHLln2kYDCon/70Kg0dOqwLvltrhDkAAAAARS8YTKusrEmB\ngJvvC4eTam4uVzYb6tQ+n332KVVUVOmqq65RY2ODzj77DO288xidf/5F2muvfTRz5q80d+5LOvTQ\nw/PvmTv3X8pkMrrrrnv13nvvatas3+qGG36zzd+vLfzMEgAAAECR81oFOUkKBFyVlTVJ8tp+2xYc\nfviROv/8C9d9gufJsgJauvRD7bnn3pKk/fc/QIsWvVbwnsWL39akSZMlSbvvPl4ffvhBpz67Iwhz\nAAAAAIpaJJJoFeT+IxBwFQ63Xpu4I6LRqKLRmBKJFl155RU6//yL5HmeDMNY/3pMLS3NBe9paWlR\nLFaWb5umqVwu16nP3xLCHAAAAICiZpptB7n/sCyn0/uurl6lH/zgQh199LGaMuWYgvlxiUSLysrK\nCraPxWJKJBL5tud5CgS6Z3YbYQ4AAABAUXPd9mON41id2m9t7VpdfvkluuiiH+j440+QJO288y56\n881FkqQFC+ZrwoQ9C94zfvwELVgwT5L03nvvauTI0Z367I4wPM/r3A9Ie0BNTZPfJQAAAADo9TzF\n42vb/KllLmeqrq6/OvNUy1tuuUkvvPAP7bjj8HzfpZf+WLfeepOy2ayGD99JV1xxpSzL0jXXTNf5\n51+s7bbbTjfffIM+/niZPM/TtGlXa/jwnTr9zQYOLN/sa4Q5AAAAAEWvradZ5nLmNj3NsjdoL8yx\nNAEAAACAopfNhlRXZyscTsqyHDmOpVQqom1ZZ663I8wBAAAAKBGGUqmo30X0GB6AAgAAAABFiDAH\nAAAAAEWIMAcAAAAARYgwBwAAAABFiDAHAAAAAEWIMAcAAAAARYgwBwAAAABFiDAHAAAAAEWIMAcA\nAAAARSjQkY1yuZxeeeUV1dfXF/SfeOKJ3VIUAAAAAKB9HQpzP/rRj/Tll19q1KhRMgwj30+YAwAA\nAAB/dCjMLV26VM8880x31wIAAAAA6KAOzZkbNWqUVq9e3d21AAAAAAA6qEN35lKplI455hiNGTNG\ntm3n+//4xz92W2EAAAAAgM3rUJi74IILursOAAAAAMBWaPdnlkuWLJEkGYbR5n8AAAAAAH+0e2fu\n4Ycf1jXXXKPbbrut1WuGYfAzS6APC9S/I8+05VSM87sUAACAPsnwPM/zu4jNqalp8rsEAJvKJVQ5\n/xuy18yTJKUHT1XjpD9KhuVzYQAAAKVn4MDyzb7WoadZrlixQuecc46mTJmimpoanXXWWVq+fHmX\nFQigeIS/eDgf5CQp9OUTslc952NFAAAAfVOHwtz06dP13e9+V9FoVAMGDNDxxx+vK664ortrA9AL\nmcnWf8gxE/xxBwAAoKd1KMzV1dXpoIMOkrRurtypp56q5ubmbi0MQO+UHnKSPGPDdFvPiimzw7E+\nVgQAANA3dWhpgnA4rFWrVuWfYLlo0aKC9eYA9B1O1Xg1HPS/inx8tzzLVnL0JXKjQ/wuCwAAoM/p\n0ANQFi9erKuuukpffPGFdtxxRzU0NOjWW2/VhAkTurU4HoACAAAAoC9r7wEoHQpzDQ0Nikaj+uyz\nz+Q4jkaOHKmamhoNGdK9f40nzAEAAADoyzr9NMuVK1fqyy+/1Jlnnqk1a9YoFoupoqJC1dXV+u53\nv9vlhQIAAAAAOqbdOXO33XabFi5cqNWrV+vMM8/c8KZAQIcddlh31wYAAAAA2IwO/czy7rvv1ve+\n972eqKcAP7MEAAAA0Jdt85y5RCKh22+/Xa+++qocx9H++++vSy+9VNFotEsL3RRhDgAAAEBfts1h\n7mc/+5kikYhOPfVUSdJf/vIXNTU1aebMmV1XZRsIcwAAAAD6svbCXIfWmVuyZInmzJmTb0+fPl3H\nHssiwQAAAADgl3afZvkfnuepsbEx325sbJRlWd1WFAAAAACgfR26M3f22WfrlFNO0eGHHy5JeuGF\nF3x5IAoAAAAAYJ0OzZmrra3VmjVr9Prrr8t1Xe23337aZZddur045swBAAAA6Mu2+QEoX/3qV/X0\n0093aVEdQZgDAAAA0Jdt8wNQxo4dq8cff1x77LGHwuFwvn/w4MHbXh0AAAAAYKt1KMy98847Wrx4\nsTa+iWcYhp5//vluKwwAAAAAsHnthrnq6mpdc801ikaj2muvvfTjH/9YFRUVPVUbAAAAAGAz2l2a\nYNq0aRo5cqR+8pOfKJvN6vrrr++pugAAAAAA7djinbl77rlHkjR58mSdeOKJPVIUAAAAAKB97d6Z\nCwaDBf974zYAAAAAwD/thrlNGYbRXXUAAAAAALZCu+vM7b777ho0aFC+XV1drUGDBsnzvB55miXr\nzAEAAADoyzq9ztyzzz7b5cUAAAAAALZdu2FuyJAhPVUHAAAAAGArbNWcOQAAAABA70CYAwAAAIAi\nRJgDAAAAgCJEmAMAAACAIkSYAwAAAIAiRJgDAAAAgCLUrWFu7dq1OvTQQ/Xxxx/r888/1+mnn64z\nzjhDV199tVzX7c6PBtBFjGSd7Pcel7Vy8YbOXFb2u88q+P6LEv+WAQAAfNFtYS6bzWr69OkKh8OS\npOuvv16XXXaZHnzwQXmep+eff767PhpAFwmseEv9bt5DlQ+fpX63H6TYM1fJSDQofs1BqrztFFX9\n9gRVzTxGymX8LhUAAKDP6bYwd+ONN+q0007TdtttJ0lasmSJ9ttvP0nSIYccovnz53fXRwPoItF/\nzZSZasi3I/NnKfLinQp8+UG+L7hsgey3n/SjPAAAgD4t0B07feyxx9SvXz8dfPDBuvvuuyVJnufJ\nMAxJUiwWU1NT0xb3E49HFQhY3VEigI5wCv+dGq6jmNPQarNKMyUNLO+pqgAAAKBuCnOPPvqoDMPQ\nq6++qg8++EBXXHGFamtr86+3tLSooqJii/upq0t0R3kAOii0x5mq+L+X8u3M8APUvN85ij/7BxmZ\ndf8+3bJ+qt35KHk1W/4DDQAAALbOwHb+YN4tYe6BBx7I/+9vf/vbmjFjhmbOnKmFCxdq0qRJevnl\nl7X//vt3x0cD6ELpiaepIVwp+/2/y+k/UqlJ58sLV6juZ88r8vK98gK2koedJ698gN+lAgAA9DmG\n53led37Af8KcaZq66qqrlM1mNXLkSF177bWyrPZ/QlnDX/oBAAAA9GHt3Znr9jC3LQhzAAAAAPqy\n9sIci4YDAAAAQBHqljlzQE8Khf5X0egD8rygEonvKpM5wu+SAAAAgG7HzyxR1ILBRaqqOi/f9jxL\ndXV/leOM8LEqAAAAoGvwM0uULNsuXHzeMBwFgwt8qgYAAADoOYQ5FLVcbnSrPsdp3QcAAACUGsIc\nilo6fbSSyRPledb6OXPfUTa7r99lAQAAAN2OOXMoCYbRKMmS58X8LgUAAADoMu3NmeNpligJnlfh\ndwkAAABAj+JnlgAAAABQhAhzAAAAAFCECHMAAAAAUIQIcwAAAABQhAhzAAAAAFCECHMAAAAAUIQI\ncwAAAABQhAhzAAAAAFCECHMAAAAAUIQIcwAAAABQhAhzKB5eSmW5y9UvM0ZV2aMVcN+SJIWdu9Qv\nM0HxzL4KOX/2uUgAAACgZxie53l+F7E5NTVNfpeAXiSa+6Vi7k35tqMd1GT9TlXOyfk+T4bqAvPl\nmLv5USIAAADQpQYOLN/sa9yZQ9GwvX8VtC2tVMh9vKDPkCfbe7kHqwIAAAD8QZhD0cgZEwrariqV\nNQ5utV3WmNhTJQEAAAC+IcyhaLRYVypjHCFJcjRYTYG7lbZOU8K8SJ5C8hRTi/Vz5czJPlcKAAAA\ndD/mzKH4eM2SopKx0d8ivJQkUzJsv6oCAAAAulx7c+YCPVgH0DWMsjb6wj1fBwAAAOAjfmYJAAAA\nAEWIO3PbwDQd2XZarmspk7ElGTKMnEKhtfI8U+l0P0mW32UCHRZYuVDB1W8oM+QgOQP2kCSZn38q\n+5/Pyd1phDJHHCUZhoxMvUJfPiHPDCo9+GtSICo5OdnvPC2zsVqZicfJrdrB528DAABQ2pgz10nB\nYEaVlfUyjHXtZDKslpaw4vHFsqyMJCmXi6iubg8R6FAMIm/+RmULZkhat15f0xF3yK0drsrTTpSR\nWXdMJ0/7llpu+IXiLx4qK7lckpSrGKe6w15U5awzZS95XpLkRipUf8Vzcobs6st3AQAAKBWsM9cN\nIpFEPshJUjicUiRSkw9ykhQIJBUK1fpQHbCVXEfRN27ONw15ir4xU5Hbb8kHOUkK//kBRV6fnQ9y\nkhRo/ECRRbflg5wkmclGRZ6f3TO1AwAA9FGEuU4yDG+Tduu+df1uT5UEbANPhpcr6DGcjIxstrDP\n82RkU63ebbbRZ2TTXVsiAAAAChDmOimZjGrjH6im07aSyYFy3Q3TEB3HVjrd34fqgK1kBpTc/fyC\nruSEi5U870J55obTRProY5Xc/2K5djzf50SGKTHpMmVH7J3v8wK2koed1/11AwAA9GHMmdsGgUBW\ntp2W41hKp8OSDJlmWuFwjTzPUCq1nTwv6HeZQMd4nuxP5ii4+i1lhhyk7I5HSpICb70h+5kn5ew0\nUulvnCrZtszEcoW/eEieGVJq+BnyQgOkdIvCrz4ks2GV0vueLGfwWJ+/EAAAQPFrb84cYQ4AAAAA\neikegAIAAAAAJYYwBwAAAABFiEXDOy2l8vLfy7Zfk+MMUnPzecrlxioS+Zui0SfleQElEt9QKnWU\n34UCAAAAKEHcmeukWOwvCodfkmkmFQx+psrKX8u2F6qs7AGZZr0sa43Ky+9SIPCJ36UCAAAAKEGE\nuU4KBj8oaJtmo2x70Ra3AwAAAICuQJjrpGx2TEHbdcuUyUxsY7ude6okAAAAAH0Ic+Y6KZE4VZa1\ndv2cue3U3Pw9ZbN7qKXlC0UiT0paN2culxuzxX0BAAAAwNZinblt5qr1DU5PkuFDLQAAAABKCevM\ndau2hpAgBwAAAKB7EeYAAAAAoAgR5gAAAACgCBHmAAAAAKAIEeYAAAAAoAgR5gAAAACgCBHmAAAA\nAKAIEeYAAAAAoAgR5gAAAACgCBHmAAAAAKAIEea6g+f5XQEAAACAEkeY62LR3C/VPztE/TM7KuLM\n8rscAAAAACWKMNeFbPfvirk3yVSzTNWrzJmmgPu632UBAAAAKEGEuS4UbCO4Bb1FPlQCAAAAoNQR\n5rpQ1pzcus84wIdKAAAAAJQ6wlwXypjHqNmaIVcD5WiomqzblDMn+F0WAAAAgBJkeF7vffRiTU2T\n3yUAAAAAgG8GDizf7GvcmQMAAACAIkSYAwAAAIAiFPC7AAC9W6D6DdmfPim3coRSY74pWbbMmuUK\nP/+QvICt1FFnyqsc4HeZAAAAfQ5z5gBslv3Z06p4+nQZnitJSu90rJr3vUnxSw6U2VQnSXIGDlXd\nHa/Ki1X6WSoAAEBJYs4cgE6JLL4zH+QkKfTZU4o8d0c+yEmSVbNcoXlzfKgOAACgbyPMAdgszwwW\ntmXIC4Rbbxe0e6okAAAArEeYA7BZyT0vk2eF8u3U2DOVPPoiOQOH5vtyw8cpPXmqH+UBAAD0acyZ\nA9Aus+FT2V88J6dypLLDjpQMQ0ZLg0Lz5sgLBJU+4GtSOOp3mQAAACWpvTlzhDkAAAAA6KV4AAoA\nAAAAlBjCHIDOyaSkbMbvKgAAAPoswhyAreN5it35Ew04eagGfHO4og/e6HdFAAAAfRJhDsBWsV95\nXNE5d8rIZWSkWhT703UKLHnV77IAAAD6HMIcgK0SXPZ2h/oAAADQvQhzALZKZsKhBW3PMJTZ4xCf\nqgEAAOi7CHMAtkp2ryPUdNFMOTuMUG7YLmr68e/ljNjN77IAAAD6HNaZAwAAAIBeinXmAAAAAKDE\nEOYAAAAAoAgF/C6gmAUb5sque0JuaISS231HsqKy6pcp/MGf5FlBpXY9W27ZEL/LLHlWdpnCzX+S\np6BS5WfLDTDm3c1asUzh5/4kLxhU6piz5Q5gzAEAAHoac+Y6yV77uCo/OivfzlQerqbBtyj+yMEy\nM42SJCc6SHWnLZQX7udXmSXPzH6q+JcHy/TWj7k1SHWDF8qzGPPuYq78VPEfHCwzsX7M44NUd+dC\neeWMOQAAQFdjzlw3iFT/v4K23fCiIktn54OcJFmJaoU+eaKnS+tTwi1/zgc5SbKcaoUSjHl3Cr/4\n53yQkySrrlqheYw5AABATyPMdZJnxQrbMuUFq1pvF4y16kPX8YyyNvoY8+7khdsY8whjDgAA0NMI\nc52UGHy5PDOab6cGnavkuAvlVIzI92UH7qn0iOP9KK/PSJWdISew0ZjbeyodZcy7U+qoM+TssNGY\nj95T6cmMOQAAQE9jztw2MDOrFKx/Xk54pHIVk9d1ZhMKff6MPNNWZvgUybL9LbIvcBMKJZ+RJ1uZ\n6BTJYMy7XSqh0GvPyAvYyuw7RQoy5gAAAN2hvTlzhDkAAAAA6KV4AAoAAAAAlBjCHEqCkauX4XAn\nFyWuoV5q5jgHAADrEOZQ3DxHZR9/X/0XjVD/RSMU+3y63xUBXc9xpMu+L40dse6/X3KcAwAAwhyK\nXGjto4rU3C9Djgwvo+jKWxRsmOt3WUDXevxR6cH714W6TEaadYs0j+McAIC+jjCHohZIvN+qz0ou\n8aESoBt90Po41wcc5wAA9HWEORS1TNWRBW1PlrKVR/hUDdBNjig8zmVZ0qEc5wAA9HWEORS1bMVB\nahw5W7noeGVje6lxzP1yImP8LgvoWgccJN02W9ptvLTnXtI990s7c5wDANDXsc4cAAAAAPRSrDMH\nAAAAACWGMAcAAAAARSjgdwHFzLb/Ldv+XK5brmRynDzPlmWtUiTyujzPUjI5Sa7b3+8ygS5X+/4S\nfXj/vTKDtnY95zxVjBjpd0kAAAB9DnPmOikU+lgVFS/n25nMIDU376d4fJYMIytJct2oamsvk+fF\n/CoT6HINH3+kv33lYOUSCUlSqF8/nfzKIkUGDPC5MgAAgNLDnLluEA7/X0HbtqsVDi/KBzlJMs2E\nQiHWgkJpWfboI/kgJ0np2lp9/tQTPlYEAADQNxHmOsnz7E3ahjwv2mo71430VElAjwhVVbXqs9vo\nAwAAQPcizHVSIjFBrrsh0CWTuymZ3E+53Hb5vmx2uDKZcX6UB3SbMaedqfjYDcf1oP321/BjjvOx\nIgAAgL6JOXPbwDDSCgZXynHK5Tj/edCJI9teJs8LKJsdIfIySpGbzWrFSy/ItEMafNAhMkyOcwAA\ngO7Q3pw5whwAAAAA9FI8AAUAAAAASgxhDiXBTK6Ukarxu4ySZa79REo3F/Y1rpTRXDjmuYZ6pb/4\nvCdL61NSq1YqXcNxDgAA1iHMobi5WZUvPFv9n95F/Z/aWWVv/ZfUe385XHTMhhWKzzpA/X87Uf1v\nHKPQmw9ITlblD5+t/r/eRf1v3Fllc9aNefWsW/Xu7jtryT7jtXTq0crV1/ldfslws1m9cf7Z+uce\nu+gf43fWuz/5L/XiX8gDAIAeQphDUQv9+y8Kr3hMkmTIVeTTexRc/aLPVZWO2D+vVWDVe5IkM9Os\n8id+pNCi+xR+b/2Ye64ir90jZ+7DWnHNdHnptCSpZeGrqr7jd77VXWpWPPoXrfzfdWMu19Xn/3OP\n1rzEcQ4AQF9HmENRCzQta9VnNf9fG1uiM6w1HxW0jWxCwS/fbrVd9r3XW90RTX/E/w9dpeXj1sd5\n8zLGFwCAvo4wh6KW3uEYeTLybc8IKjPoKB8rKi3psccWtHP9Ryq115nyjI3G3AoqNPVcWf36FWxb\neUzhe9F5g6YcI2005kYwqO2O4DgHAKCvs2bMmDHD7yI2J5HI+F0Cejk3OlS58rGyUqvklI1S88Sb\n5fTb2++ySkZux/0ky5aRbFB2pwPUfNLtcgZPUG67sbIaV8npP0rNU2+WO2J/VRx6uLLVq2SVl2vQ\nDy/XwLPO8bv8khEZMlRlu4xVatUqxUaO0vgbblbVXhznAAD0BbFYaLOvsc4cAAAAAPRSrDMHAAAA\nACWGMAcAAAAARSjgdwHFLGT/VXbw73LdEUqkLpHn9VegepEiS+6RZ9pK7nGhnH7jZBorFInMkmlU\nK505TZnsFL9LBwAAAFDkmDPXSWH7jyovuyTfzub2VtNnsxV/5GAZzrq1tly7QrVnLFB8h2NlWZ/l\nt21oekSZ7NE9XTIAAACAIsOcuW4QCj1Y0A4G3lB45V35ICdJZqZR0dpZBUFOkkL2Qz1RIgAAAIAS\nRpjrJM/bbpN2QK41tNV2jjm8VZ+7yXsBAAAAYGsR5jqpJXmFXHeAJMnzDCWS/63kqAuUHbhnfpvM\nsCOU2v58JVPn5vscZ0clUz/s8XoBAAAAlBbmzG2TFgWD8+U6I+S4o9d1ea6CK1+VZ9nKDdo3v6Vl\nLZFpVCubO0iS7U+5AAAAAIpKe3PmCHMAAAAA0EvxABQAAAAAKDGEuW5gWStlmqv9LgNAibFWLJNZ\n/bnfZQAAgF6CRcO7VFYVFTMVCr0pSUqlDlFT0yUiMwPYJtm0Kq49U6HXn5MkpY44TU2X3ymZnFsA\nAOjLuBLoQuHwy/kg95+2bb/tY0UASkH4hT/ng9y69sOy3/injxUBAIDegDDXhUyzukN9ALA1zFWf\ndagPAAD0LYS5LpTJ7CfP2zCknmcrk9nbx4oAlILM5OPlbfSTSs8OK7Pf0T5WBAAAegOWJuhitv2m\nIpGn5HkBJRInKJcb53dJAEqA/fqzisy5U14wpMQ3LlVut8l+lwQAAHoA68wBAAAAQBFinTkAAAAA\nKDGEOQAAAAAoQqwzh6IS/vQ+2V/OkRsboZax/y0vPEjBmrmKfHy3PDOo5M4/UC6+p99llrz0vLlq\nvuduGXZQZRf9QPYExhwAAKCnMWcORSP88d0qf+fH+Xaucrwa975T8RcPleHlJEmeFVPtUYvkRof4\nVWbJy773rlZPOVTKrRtzIxrToPmLZA1mzAEAALoac+ZQEsLL/1rQDjS8q/Anv88HOUkynBbZK5/q\n6dL6lOQTf8sHOUnyEi1KPsOYAwAA9DTCHIqGEym88+OZtpyynVtt50aH9lRJfZI1uPX4WkMYcwAA\ngJ5GmEPRSIyblg90nmGpZderlBr5XWUGHJjfJj14qjLbT/GrxD4hcsppsidvGPPwsVMVPpIxBwAA\n6GnMmUNxcTMK1L4hN7pjwby4QN3b6+7UVe7qY3F9S2bx2zKCtoLjGHMAAIDuwqLhAAAAAFCEeAAK\nAAAAAJQYwhyATgksflvWB+/7XUafwpgDAICNEeYAbJ1EQpUnflXxKYeo3+H7q+LcMyXH8buq0saY\nAwCANhDmAGyV8F8flr1gXr4deuoJ2c8/52NFpY8xBwAAbSHMAdgq5pfLW/etaN2HrsOYAwCAthDm\nAGyV9NST5AUC+bYXjSlz9LE+VlT6GHMAANAWliYAsNWC8+Yqcu/v5dlBJS+4RLkJe/pdUsljzAEA\n6JtYZw4AAAAAihDrzAEAAABAiSHMAQAAAEARCmx5E6DnGZl6RT+4XsH6t5QZcJASY38imSFFFt8h\n+5Mn5FaOUMu+0+SWD5O99FlFFtwpz7KVOOgy5XaaLKt2qaKLbpCZWK3ULqcrPe5bfn+l4uR5ijx/\nh+w3n5A7cIRavjZNbv9hsl95VpGH75QXtJU46zLl9pzsd6UAAAB9DnPm0CtVzP+mQquezreTI86V\nY4xW2fxp+b5cfBc1HXynqu76igzPlSR5gbBqvz9X8b8fJzO5Or9t41F/UHrnk3vuC5SIyHOzVPbI\nRmO+wy5q+uadqjr7KzLc9WMeCqv2r6/LHTzcrzIBAABKFnPmUFyctOxVzxR0hVb8r0Kf/G9BX6Bu\nqUJv35cPcpJk5FKKvPX7giAnSaFP5nRfvSUs9OYmY75yqUJP35cPcpJkpFOyX3m2p0sDAADo8whz\n6H1MW25kSEGXE9tJTsVOBX2eFZYzYNdWb3e2Gy9PRmHfJu9FxzgDdypoe8GwnOGtx9wdslOrPgAA\nAHQvwhx6H8NQ88TfyA1USJLc0AA173GDWvadplzlSEmSZ4XUfOB1Su1zjtJjpuTfmpp4mlJ7fFuJ\nfX4iz7AkSdkBE5SY+MOe/x4loOVr05Tbbv2YB0JqPuU6pU44R+kDNxrz405TZvKRfpUIAADQZzFn\nDr1XrlmBpmXKVYyTrNC6Ps+VtXaJ3LLB8sL985taa5bJs4Jy4xvmbRmJapnJtXL6t76ThK3gurJW\nLJEbHyyvbKMx/2KZvECQuXIAAADdiEXDAQAAAKAI8QAUAAAAACgxhLltkWtRcNU/ZDUv29DnuQqu\nmadA7WsFm1qrlii47AUpl+7hIoGu57muml6dp5ZFr215YwAAAF+5CgbfUCCw2O9CuhyLhneS1bBE\nVXOPl5lZK0+GEmOvUGLMD1X18nEK1r8lScpsd7gaDnhUZU/8WJHX/yBJcqp2VP15T8utGuZn+UCn\nOc3N+ujrxynx9rrjvPzQwzX6oUdlBDidAACA3iahqqrzFAy+L0nKZPZXQ8MslUoM4s5cJ8U+vFFm\nZq0kyZCn6NKbFFl2Vz7ISZK9+kWFl/w+H+Qkyar/QpF5v+vxeoGuUvvnB/NBTpKaXnpRDc8+OGKw\ngQAAIABJREFU3c47AAAA/BEOz8kHOUmy7QWy7Zd9rKhrEeY6yUgVLkpteDmZyeWttrMaPm/VZzav\nbtUHFItsTevjt60+AAAAv5lmbRt9a32opHsQ5jopPfyMgnY2vrdSoy6QZ4byfW6wUok9L5ET36nw\nvRNP74kSgW4RP+lkGaENx7lVUamqrx7vY0UAAABtS6ePlufZ+bbrlimdPtzHiroWSxNsg9DyR2Wv\neEJO2UglR39fXqi/ArWLFPnkHnmmreToC+VUjJPZsEKRebNkNlcrPfE0ZTZa5BooRi1vLlLN/9wj\nM2hr4PkXKjJ2nN8lAQAAtCkQeFeRyCPyvKCSydPlOKP9LmmrsM4cAAAAABQh1pkDAAAAgBJDmAMA\nAACAItQtCyxks1lNmzZNK1asUCaT0UUXXaTRo0frpz/9qQzD0M4776yrr75aplkcWdJw1ipWd7WC\n6beUCR+klvhVkhFRtOFm2Ykn5AZGqCU+XU5wtOxFf1P0+dnyLFuJr/6Xsrt9RYGWdxT993Uys9VK\nDTxdqe0v9PsrAdvE/sffFH1otrygrcTZ/6Xs5K/4XRIAAECbbDulaDQpz5MSiaiy2dCW31QkumXO\n3KOPPqoPP/xQP//5z1VfX68TTzxRY8eO1TnnnKNJkyZp+vTpOvjgg3XUUUe1u5/eMmeuctVJslPP\n59vJsm/JCYxWWf2MfJ8TGKHG1J2q+vUxMtYPqWcFVTvjJcWXHyczV5fftnHUnUoPLHwaJlAsAu8s\nVNV3p2w4zgNB1f71NbnDRvlcGQAAQKFAIKuqqjoZxrq250m1tf3kusWzaHiPz5k75phjdOmll0qS\nPM+TZVlasmSJ9ttvP0nSIYccovnz53fHR3c9L10Q5CQplHhSoeRTBX1W7lOF/++B/AWuJBlOVpEP\n/1AQ5CQpVFf4XqCYhOY+U3ic57Ky5/3Dx4oAAADaFgql80FOkgxDsu2MfwV1sW6JpLFYTJLU3Nys\nH/7wh7rssst04403ylg/krFYTE1NW77rFo9HFQhY3VHiViiXVo2Q0p/me8zoOJnhMVL6NW3Uqciw\n/SX9seDd0REHSyvvkbTh4jfUb/d2EzbQq+0+vlVX+YSJKueYBgAAvY4nKVHQU15ervLyqD/ldLFu\nu7+4cuVKff/739cZZ5yhqVOnaubMmfnXWlpaVFFRscV91NUltrhNTwhW3aqKmnNlumvkWEPVWH6D\nXGugKoOLFMi+J9coU3N8ptKDT1X5Pv9UeNFj8gxTqUPPUfOOJyoS/KVi/75WhpdWtnyyGqoukNdL\nfkIKbLUDp6r8qK8r/I/H5JmmUl8/R81jJ0kc0wAAoBcqLw8pHE7L86RUKqLm5pyk4rlu6fF15tas\nWaNvf/vbmj59uiZPnixJuvDCCwvmzO2///469thj291Pb5kzJ0nyMrJyn8sJjJSMDXcLzewncq3t\nJLNsQ1/9SnlmQF7FwHyfkauXkWuQGx7eo2UD3cWsWSnPCsjrN3DLGwMAAPjINB15niHPK44HMG6s\nx8Pctddeq6efflojR47M9/385z/Xtddeq2w2q5EjR+raa6+VZbX/E8peFeYAAAAAoIf1eJjrKoQ5\nAAAAAH1Zjz/Nsq8wUrWyP35cgZp3NnR6Wdnuswq6L0qem+8OBBbKDj4hqbnnCwUAAECv4Gazqv7n\ns6p56UV5rrvlN6ALZGXbcxUMLpBUWmNePAss9DKB1W+pcs5UmZlGSVJi4qVKTP6xqnJTFPA+kCRl\njf1VH/i7yssuVjj0F0mS4w5SfeOzct2Rm903AAAASk+2sUHzj5+ipg/XXSvG99tfkx/7u0zb9rmy\n0mUYTaqqOluBwMeSpGx2ourrfy8p6G9hXYQ7c50UfWNmPshJUuSdWYo035kPcpIU9BYobM7OBzlJ\nssxqRcOzerRWAAAA+O/fDz+QD3KSVPfaAq165kkfKyp94fCcfJCTpGDwbdn2iz5W1LUIc51kpOsL\n254jI13TajvLqG79XqO+VR8AAABKW7a+9TVgW33oOobR2KrPNFv3FSvCXCelxp1V0M7scIBS/S+Q\npw0LELrqp4TzQ+WcMfk+zzOVSn+7x+oEAABA7zDkG6fIim64Vgz266ftj53qY0WlL50+Vp4Xzrdd\nt0rp9BE+VtS1eJrlNrA/e0b2J0/IqRyp1Pjz5dkVstwlirj3ylNISes8ucYIGcYaRcJ3yTSqlc58\nU9ncgX6XDgAAAB80vr9EX9x/r0w7pOHnnKfYTiP8LqnkWdZHikQelefZSiZPlesO9bukrcLSBAAA\nAABQhFiaAAAAAABKDGEOAAAAAIoQYa4DstWr9On3ztZ7++6hzy/7vnIN9ZKXVSw3XfHMnqrMfl2W\n+74kKdT0J8VXHKiqLw+T3fJ3SesWDK8sP07xyn0UDd8kyZNp1qi8/Ar163e8yspmtPmkHQAAAAAd\nlVUsdovi8a+psvL7sqxlkqRQ6HHF46eqqupM2fYLkqRA4G1VVp6nePwkRaP/T1KvnXnWLubMdcD/\nnXScmufNzbfjXz9Fu90+WjHn+nyfo2Fqcu9Q1aoNTyTyZKluyPOqGniCTLMh39/UcptC4Vdk24vy\nfanUV9XUtGF/AAAAADouGr1Tsdid+bbj7KCmphmqqrog3+d5lurq/qiqqgtkms35/qamq5RKfaNH\n6+0o5sxtAzeVKghyktT44j9lu/8s6LP0b4VSfynoM+Qo7N1fEOQkyQ4+VxDkJMm253dh1QAAAEDf\nsun1tGWtVCj0dEGfYTgKhx8vCHJtvbdYEOa2wAyHFRo5qqAvMm435YzdCvpclSkbmNTq/VkdLM+z\nCvpyzu7K5XYs7MuN7qKKAQAAgL5n0+tp140qm53Qartsdp/W1+dFei1OmOuA4bfOlj10mCQptPMY\nDbvhZrVYVyprrAtvrvqp2ZqldOxMJcvOkidLnmwlKi5Txv66mhO/luutuz2azhylZPIHamr6hRxn\nB0lSLjdCzc0/8+fLAQAAACWgpeX7+fDmulVqbr5a6fTXlEyeJM+z5HlBJRJnK5M5Ws3NP5HrxiRJ\n6fSBSibP8rP0TmPOXAd5jqPcmhoFthskwzDy/Ya3Wp6qJMPe0OfUS4Ylz9z4961JGUZCntd/oz5H\nplkr1x0gyRAAAACAbWMYa+V5FZKCG/U1SrLkebGNtkzJMJLyvHhPl7hVWDQcAAAAAIoQD0ABAAAA\ngBJDmNsGZtMqhd58QMHPNnr6TTah0LLHZH/yd8nJrOtzXQUXvKDQkw/JaKj1p1gAAAD0qFT1Kv37\n4Qe0dsFG14puQqGWx9atR+ytu1b0XFc1/3pBy//ykDJ1XCui4wJ+F1CsAl8sVNW9J8jIJiRJyUnn\nqeWoKxX/6+GyGj+VJGUHTlT9Sc+p4opzFfrXugXE3cq46v/wTzk77exb7QAAAOheda8v1IJTTpCT\nWHetOPyc87THr65UfOXhsnLrrxXtiarf/jktOudcVT+97loxGI/rwCf/qbLRXCtiy7gz10nRl3+T\nD3KSFH7tD4q8NTsf5CQpWPO2Ii/cng9ykmQ21Cny4O09WisAAAB61rLbfpMPcpL0+X1/kLdsdj7I\nSVIw87YSr92eD3KSlK2r0yd3cq2IjiHMdZKRbilse66MVEOr7czm+tbvTTS36gMAAEDpyLUUXivK\ndeW0ca3otLS+VnRauFZExxDmOik56byCdmb0EUrufbFcuyLf50QHKXHMpcqNGZ/v86yAUt84t8fq\nBAAAQM8bfk7hteLAw45QcNeL5RobXStag1R+yKWq2G3DtaIRCGjH73CtiI5haYJtEPz0Fdnvz5HT\nb6RSe58l2VGZDR8r8v798ixbqV3Plls2WEZTvcJ/u0/mmlVKH3OKcrvu5XfpAAAA6GZr57+ilU/O\nUWzESO14xlmyolGZ2Y8Vab5fnmylys+WGxisbEO9vrj/PqWqV2nIN05R1USuFbEB68wBAAAAQBFi\nnTkAAAAAKDGEOQAAAAAoQoQ5AECf5qVSqr/icq0cP0Y1U49W5p23JEnN99ylVftNUPVB+yrx1z9L\nkoKvvKSqow9Vv73GKfarX0iu62fpAHywaO5LOmfKofraxHGafd0v5LquVv77C/3ozFP01V1H6efn\nn636tWuVTqU084rLdfz4Mbpg6tH6cP255ZF77tLJ+03QaQftq2fWn1va2qeZ+EIV809R/ydHqXzh\n2TLSayUnpbK3L1e/p8ao6qWjFah7y8+hQC/AnDkAQJ/W8KtfqvmWm/Jtc/sdVPWb36n2jJM3bGQY\nGjTnGW1/+tdlJDY8brzpVzcpde73erJcAD5qrK/TCRN3VXKj88CPr79Jzz72iN59fWG+74ipJ2rY\nqNG6b6Nzy8Dtd9DPfvM7Xb7RucUwDN055xld9s2vt9rneaMeUbB2wz7TQ05Urmy0Yks37NMJ76Da\nY96TzGCXf1f0HsyZAwBgM9Jz/1XQdletVPKJxws38jwZj/65IMhJkv3KS91cHYDeZMmbiwpClyQt\nfOmFgiAnSYvm/kuLNjm31KxaqRc2Obd4nqdn/vrnVvt8a94LBUFOkoKr/yV7deE+rdRKWU1LO/FN\nUCoIcwCAPs3eY2JB26ioVPigQ1pt5x52pLxAoKAvN35Ct9YGoHcZvevusjY5D4ybuJdG7DK2oG/M\n+Ikau8m5payiUnu3cW6ZdNiRrfY5ave9lCsv3GeuaqJy8cJ9usFKObERW/09UDqsGTNmzPC7iM1J\nJDJ+lwAAKHHBvfdR9r135Xz2qcwdBit+y+2KTD1RbmODsu+9KyMUVvnlP1H0O+fKGTJUwdcWSOm0\n0sefqJYrfykF+XkT0FfEysq1/ZChWvzaAmXSaR0x9URdctUvNXH/yXrr1XlqqK3VLntM1FW/u0MH\nHjlFH733rlZ89qkG7jBYP7/ldh0x9UQ1Nzboo/felR0K69zLf6KTvnNum/vUoMkKrpknM1OrbNVE\nNe9zhzKDpijQ8K6slk/lhAeree/b5VTu6vewoJvFYqHNvsacOQAAJLnNzTKiURnmhh+teKmUZJoy\nbHvDhrmclMlI0agPVQLoDXK5nHKZjMKbnAdampsUKyuc35RoblY4GpW50bklnUrJNE0FNzq3bG6f\nRrZJXnCTOVO5ZsmKSgY/susLWDQcAAAAAIoQD0ABAAAAgBIT2PIm2BpGol6hN+bICwSV3usEKcTP\ncLqb0VSv0PNz5AWDSh9xghRhzLtdQ7309znr5godfwI/N0NJ4twCYGsEPl+g4Io3lRlxkJwd9pAk\nmbWfyl76rNx+I5QZM0UyDBnJeoWWzJFnBZXe7QTJjkpOTvaHT8lsrlZm3PFyK3bY7D7RPjP7qezk\ns3IDI5SJrB9zp16hxBx5RlDp6AmSGZW8nGzvKZletTLm8XKNHfwuvVP4mWUXMhprFL/uUFm1yyVJ\nucHjVDftRQJdNzJqaxT/1qGyqteP+ahxqrvvRS66ulNNjTTlUGnFujHX2HHSMy8S6FBSOLcA2BqR\nl36jsn/MkCR5hqGmk+6QGx+uyv85UYaz7oF+yb2+pZYpv1B89qGyGtafW7Ybp7oLX1TlQ2fK/uh5\nSZIbqlD9956T/eEzrfaZ3uvMHv9uxSSYekWVq06UofVjXvYttcR/ofiXh8py1o95cJzqdnhRlc6Z\nsr31Y64K1Qeek2P2zofJ8DPLHhJ+9cF8kJOkwJcfKPTWEz5WVPrCf38wf7ElSYGPP1DoRca8W/35\nwQ1BTpI+/EB6ijFHaeHcAqDDXEfRl2/ONw3PU/SlmYrMvSUf5CQp/NYDisyfnQ9ykhRY/YEir9yW\nD3KSZKYbFZl3e5v7RPsiDbfkg5wkhZsfUKRxdj7ISVIg+4EiydvyQU6STDUq4s7u0Vq7CmGuCxm5\nNpZScLI9X0gfYmTbGPMcY96t2hrzLGOO0sK5BUCHeZ4MN1fQZeSyMja5BjQ8T4aTavV2I5du3edk\n2twn2md4m4y5PBluG2PutTHmKs4l0QhzXSg1+XS5sXi+7fQbpsyeU32sqPSljjtdbuVGY779MGUO\nZ8y71amnS/ENY66hw6TjGHOUFs4tADrMCig56fyCruQBFyk5+UJ5Gy0dkB57rJKTL5Yb2ejcUjlM\nyYMvVXbo3vk+z7KV3P97be4T7UtWXChvo3iTjhyrZOXFcs2NxtwapmTkUmWNjcZctpLmeT1aa1dh\nzlwXM2uXK/zqQ/ICIaUOOENe+QC/Syp55qrlCj/5kLxgSKmpZ8iLM+bdbsVy6S8PSXZI+uYZ0gDG\nHKWHcwuADvM82e/PUXDFW8qMOEjZnY+UJAWWvyH7gyfl9Bup9IRTpYAts365wm+vv1bc8wx5sQFS\npkXhtx6S2bRK6T1OlrPd2M3uE+0LpN+QnXhSTmCk0mWnSoYtM7dc4eaH5BkhpcrOkGcNkLwWhd2H\nZHqrlLZOlmOM9bv0zWKdOQAAAAAoQjwABQAAAABKDGEOAAAAAIoQYa6LRV66Wf2vH6V+vx6n8Ov3\n+l0OsE2clhZ9dskFenvEYH1w+IFqXvCqJGnVrTdr8a6j9O7EcVrzR45zFLmWFpX/4AL1HzVY8a8c\nqMDCdcd55Lab1X/3Ueq31ziF7+c4B7B52Y8/Us0JX9WXO22vNWecLKd6lZRrUfmiC9R/zmDFnz9Q\ngTXrzy1v3Kz+945Sv/vGKbxk3bnli+ee1iMH7K0/jh6m+dP+W24u1/Y+0T63ReU1F6j/54MVX3Gg\nAqn1Y15/s/p/MUr9/j1O4abSOp8zZ64L2UufUeX9pxb01V08V7nBE3yqCNg2y2dcqdV33JZvBwYM\n0I433apPzi5ctHTs83MVHc9xjuIU+8WVis7ecJy7/Qeoaeatqjy38Div+8dc5TjOAbRh9ZRDlX37\nrXw7fMyx2vG/Ryv60UbnltAANY27VZXPFJ5bvjzyCf3pyFPkpDY8Qn/SL3+lQY890mqf/f/4cDd+\ni+IXq71S0caNxtwcoKb+t6qyZpPz+Q5zlQsVz/mcOXM9JPjZq637Pp/vQyVA12heWHj85tasUf2z\nT7febgHHOYpXcJPj3Fy7RvZzrY/zTbcDAEnyUqmC0CVJ6QXzFVyzybklvUb28tbnlrqX/1YQ5CSp\net4rbe4T7QumNhlzd43sRBvn83TpjCVhrgtlh+3bum/oPj5UAnSN2N6Fx7QVj6vi8NaPRo7txXGO\n4pXd5Dh343Fl2jjOsxznANpghMMK7ja+oM/eax9l+21ybrHjygxufW6JH3CsTNsu6Bu476Q294n2\nZUObjLkZVybSxvk8VDpjac2YMWOG30VsTiJRXCuxOwPHSE5WgZWL5dlRtRw1XZndT/K7LKDTyvbZ\nT+lPPlFq2UcK7TRCw2+7U1XHHCsvl1Xi3cUyY1ENnjZd8a9xnKN45fbZT9Ynn8j6+CM5O41Q0613\nKnv0sVIuq8C7i+XFomr52XRlpnKcA2ibPWmyMm8uklu9SvbkAxW/5Xa5I46S1fyJrKaP5MRGqGmf\nO5UddqzkZhVYs1heMKqW/afLHX+6KkfvrNWLXpeTSmnnb56hfX52lcIHHNRqn2Zlpd9ftVfLhfeT\nlf1E1v9n787DoqzaP4B/Z2cTRAhUFAUXIPel3Bfccs+tNBMz37LM7GeWoWW+mEuYuaRWZmkmmrmU\n6Vsu2WIupalpqaiAG4qyLwLD7Of3BzgyzICiwDDw/VxX19VzfObmzM3hPOeeZxl9LIzyAGR7r4be\ndSAg9JDr/oWQuiC35hzoXB1rPnd1VRX7b7xnrjwIAUgk9u4FUZkRJhMkUssT+UIISDjOqSoxmYAi\n45zzORGVhq3jJYQJkNzf3GLr2GozJpWsFDl3BLxnrqI56EAhKo6tgwgLOapybC2WOM6JqBRsFl1F\niwqg2LnF1rGVhdwDKEXOHR1HBxERERERkQOS27sDROR49CkpyNixDRKFErVGPgWZO6/hJyKi6k0R\n+zMUCaegC+gGQ4OOAICMC+dxbd9uuDcMQMNBQyGVyyHRpMDpxjYIqRLa+k9BKDxg0GhwZed3UCcn\nI2DIk3BvGGDnd1O1SCQpcFJug4ASWt1TEKLqrFt4zxwRlYo+KRHne3WFISUZAKAKCETwL4chc3Oz\nc8+IiIjsw+Xn+XA98IF5O3voMsTlNsS+Z5+CMBgAAIHDRqDPR5Hw/LUrpNr8Y6jBNRDpvQ7hx1FP\nI/HPIwAAmbMzhvxvH7xbtq74N1IFSSWJ8PToCqm0IOfGQGRkHQbgOOsW3jNHRGUmbcvX5kIOALRX\nLiPzh5127BEREZEdGQ1w+eNjiyaXg8txdvUqcyEHAJe//w7avz4xF3IAIM+9jMx9y82FHAAY8/Jw\n7ovPyr/f1YRK9bW5kAMAuewyVMqqs25hMUdEREREROSAWMwRUal4jR4L+SM+5m1VQCBqDn7Sjj0i\nIiKyI5kc6s5TLJrU3aeh+cuvQiK/+3iKwGEjoHr8FZhUd4+hBtdA1HxiGmp36mJuk7u4oNkLL5V/\nv6sJrXYsTKZCOTcGQqurOusW3jNHRKWmT0lBxvfb8x+AMmIUH4BCRETVniL2FygS/rZ6AEr8T3vg\nHhCIBgOHQCqTFTwAZXvBA1BGQSg8YNRqcXnnd8greABKjQYN7ftmqpj8B6BsL3gAyiiHewBKSffM\nsZgjIiIiIiKqpPgAFCIiIiIioiqGxVx5qLwnO6usSnyCmYiIiBxZsWsM63aTyWS9m4224tYttl5/\nv21cCxUibPweisuPrX0dCIu5Muay4z14TfWD1//5w3n/Knt3p1pIWPge/gn0wz9N/ZG0mjknIiKi\nsuGy/z14zfOD1wJ/OB/JX2MolRrUqpUKb+8UuLndBiBw6Xw0nuvTHZ1r18TkJwfg1vV4SHKz4D5/\nHLyH1kKt/7SC4tRvAIBPF76H3oF+6NfUH5sL1i2/7NqBoa1D0L3+I5j/f69Ap9XajJlzOwsznx+H\nrnVrYdTjrfDX7/kxjy98DxsC/RDV1B9nqvFaSKLPgvvRcfDeUQu19rWCIjk/Py7n3oPX//zg9T9/\nOMcW/B7jdqDWVyHw/uwRuP36CmDU2rPrD4z3zJUh5akf4PHJWIu2jFm/wBD4mJ16VPVl7v4BlydY\n5jxozy9wbcecExER0YNTRv8Aj68t1xiZL/8Mj9YNIZHcbcvJccWojv0Qe+6Mua1jrz74PLQJXHZ+\nam4z1fDE988uw4wXJljEXPL1Nsyc8Cz0Op257ZXZc7F/x3armA0aN8GWNXdjunt64uNFS/H7pOct\nYg7d8wt8quFayPWfcLhcKpRzpSeyWy+Dx18TLPbL7LgNHruehcR0N+c5Hecir+3rFdXVUuE9cxVE\ncfm4dduVE3boSfWRe9I657l/M+dERET0cBTXrdcYypvHLAo5AJBJtRZFFwBE/30CiguWr5dmZyDp\nj5+tYh7et8eikAOAM8eP2Yx5tsi653ZGBi7/9otVzORquhZSpBfJuS4DyiTrnKvi91gUcgCgSHLM\nnLGYK0P6Jp1stHW2Q0+qD7eO1jl368icExER0cPRN7ReY2jrd7W69cpockJI6zYWba06doa+ueV6\nxFTzEfj1GGAVs8+TI6BycrJoa9ulq82YrTtYxvT0fgRNnrCOWbuaroX03kVyrnoEutrW+dEGjICQ\nWeZcX9f69+0IZBERERH27kRx1GrdvXeqRIy+jSEUKsgTomFy9UTuqPnQtexv725VaU6NGkOiUiHv\nfDRknp6oFzEfHn2ZcyIiIno4Ru/GEDIV5MnRMDl7Irf/fOiCBsBgkEMuNwAA8vKcoVa7om2XboiL\nPofMtFR06NkLM5esgOKx3pCl3YL01lUYGoQge/pq+HXuDaVKhUvno+Hu6YmpEfPRa8iTaNq8BS6e\n+QcmoxHDxk/AxDfC0b5bD6uYHUN7IyXxFhKuXUVAUAjmrFyNkNDekKlUyDgfDZWnJzpEzId/NV0L\n6b06QJZ3C9LcqzDUCEF2+9XQ+/aGkKogvx0Nk9ITuS3mQ1fvSRi8W0Ce8g8gjMh7dALU7cMBSeU8\nz+Xqqir233jPHBERERERUSXFe+aIiIiIiIiqGBZzREREREREDkhu7w44Mrn2JJTqH2GSB0DjNhqQ\nKCHNvAGn05shZEpo2j4L4eoNiBw4mTZDKpKglY6EURpi764TERER0T1IU27A6ZfNEHIlNH2fhfDw\nBrQ5cDq9GdLsJGhbjITRNwQQAsoju6CIPQVdy67Qt+sDAJDLb0CpjIbJVAsaTWsAcpsx9Tk5iN26\nGXnJSQgcNhKewSEABJTKc1AoEqDTBUKvb5IfM+YklH/+CFOdAGhCRwMKpf0S5CCk6htwit8MIVVC\n0+BZCJW3vbtUZnjP3ANSqvfAPfkZSJD/rfFa54HIUX0Iz4+7QJqXAQAwetRDxtQ/4CEbDoU4CQAQ\nUCJTvhsG6eN26zsRERERlUyacgOer3aBNLtgXfdIPWR8/Ac8Ng6H4kbBuk6mROYLu6H6aRdcvl1h\nfm3OiwthHN0b7u6bIJHkL7W12mDkXAq1ipn+8R/YOWo4Uv7OjylVKjH4+90I6JEGF5fDd2PmDITx\nwG24z3sGElPB+rPjQNye8035J8OBSdU34PlrF0h1BTl3roeMPn9CKDzs3LP7x3vmyoHz7dXmQg4A\nVHm74Xz2E3MhBwCyrBtwubLcXMgBgAQ6OJu+qNC+EhEREVHpOP2y2Vx0AYAs5Qac/7fcXMgBgMSo\ng/PRz+H8w+cWr3X+/hM4O/9pLuQAQKW6AOfjG61iZqxfbi7kAMCk0+H8V1/A2fmYZUznI3Deudpc\nyAGA6uhuSG9defg3W4U5xW82F3IAIMu7AVXCLjv2qGyxmHtAQqKw3IYEQupktZ9JYt0mUPzjRYmI\niIjI/oTcxuWLShvrOpkKQlZkXahQQgiZZZuQQEisY0pU1jGlShWEsFymCyGHUBT5ORIJILdsI0tC\nap1zW22OisXcA8rzmGZRlGncnkVey8kwetQztxl8QpAX+Bp0kt7mNhPckSedXKF9JSIjUhB0AAAg\nAElEQVQiIqLS0fQZC+MjhdZ1DUKgHvQadE0KretU7sjr8grUT083twmJBOrRM5CX1x1C3H08hUbT\nBnmdwqxi1gx7DfVC78ZU1HBHsxcmQ63ucTemkECt7om8UdMgFIXWn32ehalQPLKm8R8Lo3OhnLuH\nQFt3iB17VLZ4z9xDkOqvQJn3E4zyQOid+wASCSSaLKjO7YKQKaB9dCigdAGEAUqxB1KRBJ10MEyS\n2vbuOhERERHdgyQ3C6ojuyDkCmg7DwWcXACjAcqLeyDNToLu0cEw1chf18mjj0ERcxK6lt1gDGwB\nAJBK06FUXoTR6FXwABOJzZgmgwHx+/ZAnZyEhgMHw8W3IKb8WsEDUAJgNNbJj3nrCpQnfoKxTmD+\ng1YkErvkxpFI9FlQJeyCkCqgrTsUkLvYu0ulUtI9cyzmiIiIiIiIKik+AIWIiIiIiKiKYTFHRERE\nRAQAmhyg0NMiAUCr0UCv01m0GQwGaNRqq5dLNNZXlelzciCKxBQaDUSRmMJggMlGzNwc65jqnByY\n7qOfVIheAxiqXn5YzBERERFRtSbJSYPHsmF4ZGpd1Ap/FMp/9kAIgaXvvIU+jeuhX9MGWLdkEQDg\nh282YVDzxugVWBfvvPAcNGo15NdOwfPddvCe6oea87pDlhQHTXoa9jw9DF8F1sXmNo/i2r78mJnv\nvIWbjevhVtMGuF0QM+2bTfi3eWOcDqyLyy88B5NajQv/nMLozu3QO9APz/XpjvjLcchKT8P/PT0M\nvQLr4sk2j+LQvuL7SQWEgOuPb8F7fj14L2wAl9+qVn54zxwRERERVWtum16H84G15m2Tszu291iM\nWZNfstgvcv0mvPPCczAaDOa2STNn443M7ZDfumBu04X0xO7ERji//m5MRQ13DH9/MbJftYzp8eXX\niHlxPFAoZp2ZszF9x3ZcuXg3ZvtuPeHfqBG+KxTTtYY73li4GO9NtYy5etc+tO7YqbRpqJJUZ76D\n+5YJFm0ZL+yDoaHj5If3zBERERERFUN+7R+LbWnebaSdPmS137HffrEo5ADg4j9/WxRy+fFOI/WM\nZUx99m1kHLGOmXvgZ4tCDgAyT/1tUcgBQMyZ07hYJGZu9m38/Yd1zItnTlu1VVfym/9YtSluVZ38\nsJgjIiIiompNF9LTYttYsw78Q4dZtEkkEgx4agycXVwt2h/r3gv6Rh0s2vQhPVG3m2VMl9p18MgQ\ny5iQSOAxagykRWJ69+yFFo9ZxmzfrSfaF4n5SO066D3Uup/tunQv+harLV2jHhbbQiKBLqDq5EcW\nERERYe9OFEetrno3KRIRERFR5aJv3AFSdSakGTdh8G+JnImrUadNV3jUqoXrl+JQy8cXr8+PRJe+\nT6B5u8dwJeYCpFIZRv3nJYRNnQb9o6GQJV2CNO82tK36I2fsUvh0DYUuKxO5N2/Cq0VL9Fi5Gh6d\nu0JaqxYMl+Ig8/GFx/xIOPd9Aq7tHoMm5gIgleGR/7wE36nT8FiPUNy4cgk5t2+ja7/+mLFoKR7v\nEYqcrEwk37yJpi1aYs7K1WjTybqfj/cItXdKKw1TrQCYXGpBnhoHk5svcgdGQt/YsfLj6qoq9t94\nzxwREREREVElxXvmiIiIiIiIqhgWc0RERERERA5Ibu8OEJHjyboch5ivN0KqUCA4bAJc6/rZu0tV\nnuFyHHK/3giJQgHXsAmQMedEVAbiL8fhh683QqFQ4MmwCfCpxnOLQnEZSmU0TKZayMtrD0AJWXwc\nnHZuhFAooBk+ASZfP0iyM+H03XpI05KgfWIUDM3aAUYjVLu/gSL6b+jadYOuT/5DSRTHD0J54AeY\n6gUgb9hzgLMLZElxcDqyEUKmgKbbBJhqFRMTRqiU30Ah/xs6fTfo9AUxFcehVP4Kk6k+8vKGA3CG\nLDUOTn8XxGw/ASaP6vt7tEWWEwenqxshpApoGk6AyaXq5If3zBFRqdy+egU7enWFPif/79PZxxcj\nDx2Dk2ctO/es6jJcvYLkXl0hCnIu9fGF76FjkDLnRPQQEq5eQVivrlAXzC1ePr74+tAxeFTDuUWp\nPAsPj83mbZ2uMbLP9YTn2K6Q5ubnx+jli4wtR1Fz8hDIY88CAIRMhqzVP0C1/zs4b/3c/PrcKXNg\n8G8Mj/Dxd2N2CEX23OXwfK8rpJqCmB6+yPjvn6j54lDrmF2/g7NToZjqOTCYWsHDY0ahfnZE9pVw\neH7cFVJtQUw3X2S8dgzCpfr9Hm2R5l6B5y9dITUU5Efli4y+xyCUjpMf3jNHRGUmbvsWcyEHAHnJ\nSbj64//s2KOqT719i7mQAwBTchLymHMiekh7t28xF3IAkJachAPVdG5xdj5msa1UxsH5z83mQg4A\nZGlJcNmw3Fx0AYDEaITT9rVw+n6Dxeudtn0B521fWMY89hucf/zUXMgBgCwrCS7ffmQd8/u1cFIV\nien0BZydtxbp51E4/7PGXMgBgCwnCaro6vl7tMUpfou5kAMAmTYJqoSqkx8Wc0RUKgpXNxttrjb2\npLIisZFzCXNORA/J2cbc4lJN5xYhlEW2JRBy61yYatS0fq2LG4TK2bLN2RWiyHfHCakUws369SYb\nbcLZDUIUiSlcIYRLkTYphMrd+vXK6vl7tEXIrce5rd+to2IxR0Sl0mTMWLgHBJq3vVu1QYMBg+3Y\no6rPdcxYyArlXNGqDZyZcyJ6SIPGjEW9QnNLcKs26F5N5xa1ugeEUJi3NZrHkdcrDIb6d/OjD2mD\nvGenQBs6xNxm8vBE3ripUE+aaW4TUinUL82C+vnpEE53iy/NyInIG/AyDD6FYjZog7wnbcR8ZirU\neYViCinUebOgVk+EEE6F+jkKea1fgsGrUMy6baANqZ6/R1s0DcbC4FooPzXbQFu36uSH98wRUakZ\n1GrE798LmVKF+n36QapQ3PtF9FBMajU0+/dColTBqU8/SJhzIioDGrUah/fvhVKpQuc+/SCvxnOL\nVHobCkUcjMZaMBga5jfmqaE6tBdCqYKuSz9AoQCEgOKvA5CmJkLX9QkIj/x7r2SxZ6GIPgV9m04w\n+jfOj5mSCMWfv8BYPxCGNp3yY2rVUP27F0Khgq55P0BeQkzZWShkp6A3dILRVBBTmgKF4g8Yjf4w\nGNrkx9Spobq4F0Kugq5pP0BWfX+PNhnUUCXuhZCqoKvdD5A6Vn5KumeOxRwREREREVElxQegEBER\nERERVTEs5sqBNisTuuzb9u4GERGRw5GoMyHJ4zG0ImmyMqHluuXhmYyQZt4Cilz0pk9Ohkmns2gz\nZGXCaJXzPEgkqfcVk0pPkpMJibrqjXMWc2XIZDTi4LQp2BgcgI0hgTg29117d4mIiMgxmIxwWz8F\nXq8HwGt6IFy38xha3kxGI3ZNm4LFwQH4MCQQ+7lueWDyuKOoNasFvGYEwXNOe8gSzkOflISLA/vg\nTPPGONOiCdK//xbCaMS1aVPwb3AA/g0JxI2CnDup1sDLsxG8PQPh4TYCEmTbjEkPwGiE2/Ip8BoT\nAK8xgXBdW7XGOe+ZK0Nx327FgckvWLQN3PEj6nbpZqceEREROQbVsa1w/8LyGJr55o/QB/EYWl7O\nfLsVO4qsW8bv+BENuW4pNc932kCefMm8rWvaFf8mNkZa1Hpzm9TVDfXmRyL+9VctXhu8Zz38+0yE\nRGIyt+XmzYRq+jarmFkzdpffm6iiVL9thfviInNL5I/Qt3Sccc575ipIxvloG23n7NATIiIixyJP\nsD6Gym7wGFqekm2sW5K5bik9vcai6AIAecI5aKItc2nKzUHOccsvJwcAkXHIopADALnxjM2YVHry\nqzbmlqtVJ5cs5spQvV59LLYlMhn8evSyU2+IiIgch66Z5TFUSGXQP8pjaHlqZGPdEsh1S+kpnKAr\ncgZZ16wP3IvkV1mvPmqNfNrytTIZ5IFhMJk8LF8vecJmTCo9XXsbc0ubqjPOZRERERH27kRx1Grd\nvXeqRGrU94dbfX9kx8fDrX59dFq4GLU7drJ3t4iIiCo9k7c/jF7+kKXGw+hVHznPLIahCY+h5alm\nfX941PdHZnw8POrXx4CFi+HPdcsD0T/aG9LMBEj0GmjbDkXumEVw7dITwmCAISUZrm3bo8GKT+HW\n7jEo6/tDFx8PZf36qL9wMdwe7wG9oQtk0msQUEGteRUa7WSbMaFwundnyILJ1x9GH3/IkuNhfKQ+\ncl5eDENzxxrnrq6qYv+N98wRERERERFVUrxnjoiIiIiIqIphMUdEREREROSA5PbuABEREREAyGLP\nwXnHlxByJfKeegGm+oH27hLRQ1Gq90Cp/gEmeQDy3CdBSN0h052Dc/aXEBIl8mq8AJOC45weHO+Z\nIyIiIruTXYuF59hukGjUAACTRy2kf3sCwtPbzj0jejCqnG/gnjrJvK1TdUaO90p43uwGiSgY59Ja\nSPc7ASHjOKfi8Z45IiIiqtRUe7eZCzkAkGalQ/Xb/+zYI6KH45S9wWJbqf0DTlmfmQs5AJCa0qFS\nc5zTg2MxR0RERHYnatS0ajPZaCNyFEJmOX4FZBDyR6z2M0k5zunBsZgjIiIiu9MMeRaGRiHmbX3r\nTtD1HGTHHhE9HLXHDJgkd78MPM/9VeS5vwyDotA4V3WCzoXjnB4c75kjIiKiykGvh/LYrxBKFfTt\nuwNSfuZMjk1izIBC8zuM8kAYVS3zG4UeyrxfISQq6J26AxKOcypZSffMsZgjIiIiIiKqpPgAFCIi\nIiIioiqGxVw5kObegkSdYu9uEFEVk5t4C3kpnFsqkjHxFozMecVKvAUw50RE94XFXFky6lFj3wR4\nfRUEr6+awO3314HKexUrETkIk16PX16cgM0tg/B1iyY48tbrqMRXyFcJQq9H+osTkNgyCIktmiCT\nOS9/ej3w4gSgZRDQognwFo+hRET3wmKuDKlit8Lp0ncAAIkwwfncWihu/GbnXhGRo4v7diuu7Myf\nW4TJhPPr1yLhd84t5Un97VbkFeQcJhNy16+FljkvX99uBQrlHOvXAsw5EVGJWMyVIXlmnFWbLCPG\nDj0hoqok65L13JIVx7mlPBls5NzAnJcvGzkHc05EVCIWc2VI27A/BCTmbSFVQNegrx17RERVgX+/\n/oDk7twiVShQrxfnlvLkVCTnUCjgxJyXLxs5B3NORFQiWURERIS9O1EctVpn7y6UismtHgyewZDl\nJsLo0Qg53ZfA6NvO3t0iIgfn5lcPNYOCoU5MhEdgI3SOXAKftpxbypPcrx4UQcEwJiZCHtgINSOX\nQMmcly+/ekBQMJCYCAQ2AiKXAMw5ERFcXVXF/hu/Z46IiIiIiKiS4vfMERERERERVTEs5oiIiIiI\niByQ3N4dcGRnd2zHhR//B8+GAej0ylS41PLCjZPHcXL9WsiUSjz+4mT4BIfYu5tERERERNVWzMnj\n2LN+LeRKJYa8OBn+VWh9znvmHtCpTRvwv9dfNW/XbdsOT370Kdb07gqjLv/BLaoa7pjyx0m4+fra\nq5tERERERNXW9YsX8HrvrjAUrM9darjj4z9OwtOB1ue8Z64c/LPla4vtm3+fxF9rPzMXcgCgzb6N\nC3t+qOiuERERERERgEM7tpsLOQBQZ9/GsSq0Pmcx94BcH/Gx2JbK5fDwq2e1n1uR/YiIiIiIqGLU\ntLEWt9XmqFjMPaDub4TDxds7f0MiQbfXZ+Dx/7yEuq3bmPcJ7NkLTZ8YYKceEhERERFVb6Gjx6Jx\nofV565698FgVWp/znrmHoMvNRfyxP+DZMABegY0BAMJkQvyxPyFTKlGv3WN27iERERERUfVmMplw\n/tifUCiVaOqA6/OS7pljMUdERERERFRJ8QEoREREREREVQyLOSIiqvZMRiOun/kXOelpFu05l2Kh\njr9mp14RlS2j0YiYM/8iq8g4j78Ui5sc51RFFDfOEy7FIqnIOM9ISsLV6HMV2b0yx2KOiIiqtdSr\nVzC3czu837sr3m4VjN/XroFRq8WxZ0biQKd2+LV9C5yaMgnCZLJ3V4keWMLVKxjduR3G9+6KIa2C\nsX3tGui0Wrz+zEg83akdRrRvgblTJsHEcU4OzNY412u1eO+ZkZjSqR1eat8CywvG+eZFC/Cf1sGY\n1rMTpvfuhqzUVHt3/4HIIiIiIuzdieKo1bp770RERPQQtr79FmL/OAwg/wxdzJGDaORRE9fXfmbe\nJzv6LDzbtYdrYCN7dZPooSx9+y38XTDOjUYjTh45iBoeNbGt0DiPiz6LZu3aoz7HOTkoW+Pc26Mm\n9hQa51ejz8Lbzw/rI2abP6TLSE6CRCJB6x6hdun3vbi6qor9N56ZIyKiai312lWLbb1Gg9SL5632\nU1+9atVG5CgSioxzrUaDSzbG+U2Oc3Jgtsb5VRvj/MqZMyj6DMikIq91FCzmiIioWmsz5EmL7dpN\ng/DouOcA6d1DpNTJCT59n6jorhGVmV5FxnnDpkEYNu45SAuNc5WTEzpznJMDszXOBxYZ50onJwyY\n+KLVF4d3LvJaR8HLLImIqFoLaPcYXGrWhC4vD0Hde2Lc0pWoFRQMj9ZtoM/IQI2gYLT8YDncmzW3\nd1eJHljzdo/BvWZNaPPy8Fj3nnh76UoEBAUjpHUbZGVkICAoGG99sBxNOM7Jgdka5w2CgtGodRvk\nZGSgflAwXv5gORq3ao12fZ9ATmYGPLy8MfrNmeg5arS9u1+ski6z5PfMERERERERVVL8njkiIiIi\nIqIqhsUcERERERGRA5LbuwNEREREVP52bvwKB37cBb+GAXh+2gx4+fri5JFD2L52DRRKBcZOnorg\nVm3s3U2ih3K/4zzh6hV8tWIp0pKTMPDpZ9B76HB7d/2B8J45IiIioipu+9o1+HDWm+btJs1aYM7K\n1ZjQrweMBgMAwNnFFVv+OAGfun726ibRQ7nfcb7xwB+YPGwgkm8mmPeN/HITeg4aUuF9vh+8Z46I\niIioGvtpx3aL7dhzZ/Dt+s/NC1wAyFPn4uDe3RXdNaIyc7/j/JvPPrEo5ABgf5HXOgoWc0RERERV\nnK+f5dk2hVIJ/8AmNvarV1FdIipz9zvOGwYFW7U56hlpFnNEREREVdwLM942L1ZlMhlenjUHIyb8\nB206dTHv02PgEHTu089eXSR6aPc7zoeFTcDYyVMhkUgAAA2aNMWzU16zS58fFu+ZIyIiIqoG9Dod\nok/9jTr+/vCpU9fcfvHMP1AolAgMDrFj74jKRmnG+c1rV5GekoyQNu0gk8ns0d37UtI9cyzmiIiI\niIiIKik+AIWIiIiIiKiKYTFHRERUjFv/nkby+Wh7d6NKEjodtEf/hLHIE+Xk105DlmCZ89yrV5Bx\n/BiE0ViRXaxy9DodTh/90+opfhf+PY1LHOcPTZKdDsWZI5CoC11ZptdBfu5PSFOLjPO405Bdtcy5\n9NYVyM8fAwqNc5sxqUTVbZzzS8OJiIiK0KvV2PTMSMT/eQQAEDxwCEat3QBpJb6nwpHo42KRNmpo\nfiEnk8H9nQjUePFFeKwYCWVMfs61bYbg9ssbED13Di6vXgUIAdfGTdBpx49w8q1t53fgeK7FxWLq\nqKFIvpkAmUyGye9EYNTEF/H6MyNxqmCc9xg4BAvXbqjU9w5VVsrD38P9w0mQ6DQwubjj9pzNMNWq\nDY+3h0KWmgAhlSF3QgTyBr8IjzkjoTxbMM47D8HtWRvg+uUcOO9YBYkQMNRrgqzIHyGPPmoVU9+y\nm53faeVWHce5LCIiIsLenSiOWq2zdxeIiKgaOv11FE6s+9y8nRobgzqt28K7sfUjrqn0sma9Cd3x\nY/kbQkD75xF4hdSA6x9fmfeRJ8YgQ+qLk+/OM7fp09MBIfBIaO+K7rLDWzLrTZwpyLkQAqf+PALX\nGjWwc+PdnF+LjUFI67ZowHFeOkLAY/YwSHMyAQASvRayq9GQXz0H5fn8nEuEgOLMEQiXGnDeV2ic\nX4+BqZYv3DbMg6SgTXo7HTCZ4PLdSquYmgHPV+hbczRVdZy7uqqK/TeemSMiIioi6+YNq7bbCdZt\n9GCMCZaXP0Gngyk+zmo/zeWLVm15RS6dovuTVCTnep0O1y9b5zyJ47z0DHpIM5IsmmQpNwClk0Wb\nxKCDNME657J463EuTb5hOyaVqDqOc94zR0REVMSjQ4ZDKr/7eafCxRVB/QfasUdVi/OIpyy2Fc1b\nAkNfhJDdzblQucJ99CtwKvJFvn5FXkv3p1+RvDVt3hIjJ7wIWaFx7uziiu4c56WnUELb+UmLJk3P\np6DpaZlzfWBLaAYXGedOrsgb9gqM3pbjXNtrtM2YVLLqOM55mSUREVERbj6+8O/YGTq1GrWbt8Dg\nJR/Bu0lTe3erylC2aQdZXT8IowFOvfui5uLlQN1A6Jt0hkSrhqF+C+SM/wiiXgh8+w+CSaOBU506\nCJr1LuoMfvLeP4CsPNqmHXzq+sFoNKBT774IX7wc9QID0bpjZ2jUajRp3gKzlnyEBhznD0T3WD9A\nIgVUzsjrPwHqsTNhCH4MJm8/wGSArn1f5Ly6HKa6gdA37wyJRg1DYAvkTP0IxgYh0HYclH9vnFcd\n5I5/F7quT9qMCWnVuM+rvFTVcV7SZZb8njkiIiIiIqJKit8zR0REREREVMWwmCMiIiIiInJALObK\nWOzP+7Bp9HB8EzYa8Uf/tHd3iIjoHoQQ+Oazj/Hy0P6Y99pkJN64DgA4+/M+rBo9HJ+GjUYc5/MK\nwZxXvD9+3odpo4fjzbDROF1Ncp6dlYlls8MxaXA/rH7/PWg1mmLngayf9yFu9HBcChuNnIL8yGIu\nosbLz8NjxCCoNm8EAEiyMuH6bjhqDu0Hl8j3AI0GEALOaz6Gx7D+qPF/kyEtiKn8eR88nhkO9/Gj\nIT+WHzMv5iKuvPQ8YoYPQlpBTENWJq7PDsfFwf1w8/33YCroZ/JnHyNmaH9cfW0ydCXEvBJzEe++\n9DxeGT4IP5QQkxwb75krQwmnTmLdgN4QJhMAQKZSYcqRE6jp38DOPSMiouJ8/ekqrPjv2+bthk2D\n8P6KT/HhwD7m+VyuUuG/R07Ai/N5ubl66iQWFzqGMuflL/rUSbwwoDdMBTlXqlT45sgJ1K3iOX8z\nbDQO79tj3h4+fiLqN2psNQ98seJTxAzsAxTkR6JS4dFfDqPuyEGQpiSb9729eh1U322D6qe7MfPG\nT4QxsDHcIu7GNDQJQvZHn6Lm4D6QFMQUKhVS9x/Gv8MHwVAoZsPP1iHju23IKtRP7/EToWrUGAmF\n+unUNAgtVn4Kz0GWMW/uP4xhwwchvVDMeZ+tQ6CNmP4fLn+ALFJFKumeOT7Nsgyd+PILxBd8uzwA\nCKMRtQIawa9tOzv2ioiISrIi4h0kF/russy0NHhKJLj1zylzm8lohE9AIzTkfF5ufv/yC8QVOoYy\n5+Vv+5df4HShnBuNRtQPaIRHq3DOdVot3nv1JYu2xBvxSE9JsZoH2kgkkBeaB2A0wkUiwSNHDloG\nNZmg3Lfb/KXfACC7Hg9pagpkhWJK09MgJBIoC8WUGI1IhwRJhy1jCpMJWft2W/b9RjwMKSnQF4pp\nSEuDv1QCpyIxj0KC7UViykwmBNqI6fvqNFDlVtLTLHmZZRnybNDQqq1mQ+s2IiKqPPyKzN0qJyc0\nCH7Uaj9vzuflytvGMZQ5L19Fxz4A1K3iOVcolfAp8t2FdRs0tDkP1LExDyibt4CQSCzajAGBMBWJ\naWzQEMYiMYWTE4zFxESRmKqAQCiKxFQ2aAhVkZgSJyeI4BCrmHWat4CkSMzaxcQkx8Zirgy1GDUa\njfv0M2+3fGoMGof2sWOPiIjoXl58623UCwgEkH+Z2dSIBeg5/nk0KzSfP/7UGIRwPi9Xj48azZxX\nsP6jRqNzoZwPeGoMOlbxnEskErz1wVK41nAHAHh6e+P1eZE25wH/8c/DvVB+aj01Bm7PhEH9+lsQ\nsvzve9O3aAX15P9DTuRSmApimry8kTMvErkz3oahIKZQqZDz3wXQhD0Pbe+7MTWjxkD6TBhqT38L\nKIjp3KIVfKf8H/w/WAppQUy5tzfqzYtEnbfehqogpkSlQr2IBdCHTbSKWfuZMEyc/hZkBTGbtmiF\nZ4uJSY6N98yVg7TLcZDJFbxXjojIQZhMJlyKPgefunXhUcvL3J5cMJ/zvq2Kw5xXvPjLcZDLFVX+\nXrnC1Dk5iL8ch8CgEChV+ZewFTcPaC7HQSJXQFUoP5LkJEjT0mAMKXSmLTcH8ktxMASFAAUxYTJB\ndv4cTHXqQhSKKbscByFXwFQopj4pCYb0NDgXimnMyYH2chycgkIgLYgpTCbkRZ+Dsm5dyO8RMy0p\nCZnpaWh0j5hUuZV0zxyLOSIiIiIiokqKXxpORERERERUxfBplkRERDaYTCacPvoH0pISrR6YQPQg\nsjLS8cm8/yL69N9o3u4xyORyAEBK4i38c/QP1PDwhJOLCwAgLzcXJw7/DiEEPDxrASh+TMZFn0Ps\nubPwqVO3ysT8PupLXI29iMCgEEgL7vuyh8qan6IxqWor6WmWFXqZpclkQkREBC5evAilUon58+ej\nQYPir8/mZZZERGQP6pwcTBkxCOdP5z/u+/EeoVi6+VvICxZYRKV17MCv+L+nh5m35QoFth87jVN/\nHMb8aVNgNBigcnZG5Jcb8Ujtunh15GBkpqVBIpFg4hvhePaV12yOySUz38SODesAALXr+2P1zj0O\nH/P5fj2g1+V/oO/u6YnNh47Dy8enYn5RhRQ3D9g7P0VjvvjW27bfAFUZleZ75vbv34+4uDh89tln\nCAwMxEcffYTBgwcXuz/PzBERkT3sjFqPXZs2mLcTrl1F0+Yt0bBpkB17RY5syvBByM2+bd42mUxI\nTLiBXRs3QJ2TAwAwGgy4FB2NyxfOmxf7APDvX0fh7OKCPdu+MbclXLsKD89a+HLZYnNbzu0sGI1G\nbF79sR1juj5UzFN/HsGNK5fN+2o1GhgNBnTqVfFP2bQ1D1TGnA8fPxHOrq5ln0WMNI0AAB8KSURB\nVACqNEo6M1ehHzGePHkS3bp1AwC0bt0aZ8+eLXF/T08XyOX2O7VORETVk0adZdWm19wu8dNRopKo\nc3Os2tKSbiE7M8OiLTMtBZ5enhZtRoMBt9OTrV6fkXrLqi0nK/2hYmam3LSOmZlWiphJDxUTMFnt\nezs92S5/e7bmgcqYc7lUx7mpGqvQYi4nJwdubm7mbZlMBoPBUOxlKxkZ6orqGhERkVmXfkOw5oMP\noNNqAQBu7h5o27UPL/+nB9Z/xNPYtm6NRVvY1On4ddf32Lt9y939nnoG/o0a4/ihQ+a2R9u2w+Cx\nz2PbunUWY3L4c5Owf8f3SLh21bxv3+FPQwjpA8cc9txL+On7nZYxR4yGgKxCYtap74/F4dMt8jQ0\n7D92+duzNQ9Uxpy7e/lxbqriSirWK7SYc3NzQ25urnnbZDLx/gMiIqp0AoKC8enOPfhu/VooFEqM\nnjQZXr6+9u4WObA3Ij+ECQJ7tm6GXKHASzNno3v/QegY2geBwY/i/Om/0a5LNwyf8B/IZDI4u7ri\nwI//Q72AQIyd/Co8PGtZjUlfv3r4dNdebP50FdKSE9H/qTHo3Lsf2nfr+eAx69k/ptFoxNbPV0Op\nUuKlme+iTacudvmd2ZoHKmPOqXqr0Aeg7Nu3D7/99hsiIyNx+vRprFq1Cl988UWx+/NTBiIiIiIi\nqs4qzZm5vn374siRIxgzZgyEEFi4cGFF/ngiIiIiIqIqo0LPzJUWz8wREREREVF1VtKZOWkF9oOI\niIiIiIjKCIs5IiIiIiIiB8RijoiIiIiIyAGxmCMiIiIiInJALOaIiIiIiIgcEIs5IiIiIiIiB8Ri\njoiIiIiIyAGxmCMiIiIiInJALOaIiIiIiIgcEIs5IiIiIiIiB8RijoiIiIiIyAGxmCMiIiIiInJA\nLOaIiIiIiIgcEIs5IiIiIiIiB8RijoiIiIiIyAGxmCMiIiIiInJALOaIiIiIiIgcEIs5IiIiIiIi\nB8RijoiIiIiIyAGxmCMiIiIiInJALOaIiIiIiIgcEIs5IiIiIiIiB8RijoiIiIiIyAGxmCMiIiIi\nInJALOaIiIiIiIgcEIs5IiIiIiIiB8RijoiIiIiIyAGxmCMiIiIiInJALOaIiIiIiIgcEIs5IiIi\nIiIiB8RijoiIiIiIyAGxmCMiIiIiInJALOaIiIiIiIgcEIs5IiIiIiIiByQRQgh7d4KIiIiIiIhK\nh2fmiIiIiIiIHBCLOSIiIiIiIgfEYo6IiIiIiMgBsZgjIiIiIiJyQCzmiIiIiIiIHBCLOSIiIiIi\nIgfEYo6IiIiIiMgBsZgDcOzYMXTq1AlhYWEYN24cnn76aURHRz9UvNdff92qffr06Rg5ciQuXbp0\n37Fu3ryJX3/99YH7Ym9lldt//vkHffv2xZIlSyzaU1NTERYWhqFDh2LlypU2Xztz5kwMGTIEYWFh\nCAsLw7PPPovY2Nj7+rk3btzA008/Xer+VoTY2FhMmjQJYWFhGDlyJFasWAEhRLHjb8GCBbh586bN\nWCtXrsTmzZvLrG8bN27EsGHDMHLkSFy/ft3mPs2bNzf/TsLCwhAREYGUlBREREQUGzcsLKxUfz+V\n2Zo1azBhwgSMGzcOYWFhOHv2rM39SjsGu3TpUlZdtLv7zVFpPeh4v59xvWPHDowfPx5hYWEYM2YM\nDh8+DCD/vfz7778W+2q1WvTq1av0b6CSKjrfjxkzBrt3766Qn+3ox8r7VdbrFbJU3HG1ONevX0f/\n/v0RHh5e7DqlNO61pklPTzcfM9u3b49Ro0YhLCwM27Zte+Cf+aDKa34uasuWLdDr9Q+0trkf97OO\nTE9Px9SpUzFx4kSMGTMG77zzDjQaTeU5PgsSR48eFdOmTTNvHzp0SEyaNKnM4t3RoUOHUsf69ttv\nxeLFix+4L/ZWVrlduXKl2LBhg1X7pk2bRGRkpNBqteLxxx+3+drw8HDx+++/m7cPHDggpkyZcl8/\n9/r16+Kpp54qdX/LW1ZWlhg8eLC4cuWKEEIIg8EgpkyZIr7++utix19JVqxYIb7++usy61+XLl1E\ndna2WLFihVi7dq3NfTp37lzquOPGjRNxcXEP2z27i42NFaNHjxYmk0kIIUR0dLQYMmSIzX1LOwYf\nJK+VUWlyVFoPOt7vNa5v374t+vTpI7RarRBCiMTERNGtWzdhNBptxtNoNCI0NLTU/aisis49OTk5\nYvjw4SI6Orrcf7ajHyvvV1mvV+iuko6rxdmxY4d4//33hRDFr1NK437WNHfY83hYnvNzUaGhoUKj\n0TzQ2uZ+3E/OFy1aZDEO5s+fL7788stKc3yWl0+J6Nhu376NWrVqISwsDLVq1UJWVhbWrFmDiIgI\nXLt2DSaTCdOmTUOHDh2wd+9ebNq0CQaDARKJBKtWrTLHycvLw9SpUzF06FD8/fffyMnJweTJk7F4\n8WK88847yM7ORnJyMsaOHYuxY8di06ZN+P777yGVStGiRQvMmjULa9asgUajQZs2bdC7d287ZqVs\n3MktAFy8eBHz588HANSsWRMLFy5EjRo1sGTJEpw4cQImkwkTJkyAn58fvvvuOygUCtSuXRt9+/Y1\nx+vWrRuef/55ZGZmYuLEiffVh6ysLLi4uAAA1q1bhx9//BFyuRzt27fHjBkzsHLlSpw6dQpqtRoL\nFiwAABiNRsycORNNmjTBpEmTyjIlD+SXX35Bhw4d0LBhQwCATCbDokWLoFAocOrUKVy7dg0vvPAC\n0tPTERoaiqlTp5rPfnl6eiI8PBzZ2dkQQmDRokXmuNeuXcMbb7yB+fPnw8/PD++88w4yMjIAALNn\nz0ZQUBD69euHtm3b4sqVK/Dy8sLKlSshk8ks+te/f3/Mnj0baWlpWLx48X2/rxs3bmD69OnYunUr\nli1bhmPHjsFgMKBfv37mvH/88cdITU1FXl4eli5divr16z9kNitejRo1cPPmTWzfvh3du3dHSEgI\ntm/fjr/++gurVq2CEAK5ublYsmQJFAqF+XW25hsPDw+8++67iIuLQ/369aHT6QAAP/30Ez7//HPI\n5XL4+Phg2bJlkEod52KM4nIE5J+hDQ4ORmxsLHJycvDRRx/Bz88PS5YswdmzZ5GZmYng4GC8//77\nSE9Pv6/xnpubi0WLFkEul8PZ2RkfffQR3NzcLPp0r3GtVCqh1+uxefNmhIaGwt/fHz///DOkUilm\nzpyJgQMHol27dnjzzTdx+/Zt+Pv7m19raz7U6/WYNm0ahBDQarWYO3cuQkJCyiPd5cLV1RWjR4/G\n3r17sXv3bot5fcCAAVbHvNmzZ9sct7m5uTbnotDQUAQGBqJRo0Y4ePCg+ViZmJhoFbequnNMtTV+\nVq1aheDgYAwfPhwpKSl46aWX8N1331kdYwcMGGCx3lm5ciVmz55ttUb5999/MXfuXLi6usLLywsq\nlQqRkZGIiorCDz/8AIlEgoEDB2L8+PEOOf+UdFwFgMjISJw8eRIAMHjwYPTt2xerV6+GRqOBm5ub\nxTrFw8MDy5Ytg0wmQ/369fHee+8BAP773/9arSMLe5A1zR0JCQmYM2cOdDodnJycMH/+fPj6+uKD\nDz7AhQsXkJ6ejmbNmpnXNQ/jXvNzUFAQYmNj4eLigvbt2+Pw4cO4ffs21q1bBxcXF8yaNQs3btyA\n0WjE888/j4EDByI6Ohrz5s2DTCaDSqXCvHnzcOTIEaSkpOD111/Hc889V+LaxsfHx+Y8MWvWLFy7\ndg0ajQbjx4/HsGHDSp1zb29v7Nu3Dw0aNEDbtm0RHh4OiUSCW7duIT09Ha+88gpSUlIQFBSE+fPn\nIyYmBpGRkTAajcjIyEBERATatm1rjrd06VJkZ2djzpw52Lt3L9avXw+pVGo+Ppw8efKexyML5VIi\nOpijR4+Kjh07inHjxomnn35atGzZUhw6dEiMGzdO/PTTT0KI/Mr9gw8+EEIIkZ6eLgYOHCiEEOLT\nTz8VarVaCCHEu+++K3bu3CmOHj0qJk2aJMaPHy9+/vln88+5U5GfPXtW7Nu3TwiR/8lt3759hRBC\njBgxQvzzzz/mn6fX6x3+08biciuEEE899ZSIjY0VQgixdetWsXTpUnHgwAHzJy8ajUYMHTpUZGVl\nFftJ+tq1a0VYWJgIDQ0VaWlpIi4uTuj1eot9wsPDxeDBg8W4cePE+PHjxZtvvimSkpLEhQsXxKhR\no4ROpxMmk0lMmTJF/Prrr2LFihVi3rx5Qoj8syLDhw8X06ZNExs3bizPVJXK6tWrxfr1623+29Gj\nR8XAgQOFVqsVarXa/EnTnU/x5s2bZ87lyZMnxc6dO8WKFSvEggULxMiRI82fSn7wwQdi06ZNQggh\nrly5IsaMGSOEECI4OFjcvHlTCCHE6NGjxalTpyx+/vXr18WECRPEkCFDxOrVq0VGRoa4deuWVT+b\nNWsmxo0bZ/7vzJkzFp9yhYaGiuvXrwutVis2b95sfg/ff/+9ECL/7MqaNWseOIf2dvbsWTFz5kzR\no0cP8cQTT4i9e/eKjRs3isTERCFE/tzyySefWOTE1nyzZ88eMX36dCGEEAkJCaJZs2ZCCCGmTp0q\n9uzZI4TI//Q4Kyurot/iQ7OVIyHyx8GuXbuEEEIsXbpUfPbZZyI7O9s8HoxGo+jfv79ITEy87/Ee\nGRkp1q1bJ4xGo9i/f79ISEiw6Mv9juurV6+KuXPnir59+4qePXua/4buXCHwxRdfiKVLlwohhDh9\n+rT5zJyt+fC3334TU6dOFXl5eeLMmTPixIkTZZneMmfrk/P9+/eLfv362ZzXbR3zbI3b4uaioKAg\nkZ6eLoSwPDNnK25VUdwx1db4iY2NFWFhYUIIIT7//HMRFRVV7DG28HqnuDXKsGHDRExMjBAi/+8u\nPDxcxMbGijFjxgiDwSAMBoMICwsTly5dcsj5p6Tj6q+//iqmTJkiTCaT0Ol0YtSoUeLChQsW4+7O\nOsVkMol+/fqJ1NRUIYQQy5YtE1u2bCl2HVnY/axp7ih6Zu7VV18Vhw8fFkIIcfDgQfHWW2+JrKws\n81UERqNR9OvXT6SkpDxghiyVND/v3LlTCCHExIkTzWunt956S+zfv19ERUWJBQsWCCGEyM7OFn37\n9hVpaWkWZ/H3798vpk6dKoSwPDNX0trG1jyRnZ0tevfuLdLS0kRaWpr5uFHY/eTcaDSKbdu2iYkT\nJ4r27duLl156Sdy8eVNcv35ddOjQQWRmZgqj0Sh69eolUlNTxY8//iguXLgghBBi165d4p133hFC\n5NcBkZGRYtGiRUIIITIyMsSAAQPMx/U333xTHD58+J7Ho6J4Zq5Ax44dsWzZMgDA5cuXMWbMGDRo\n0AABAQEAgJiYGJw8edJ8z4PBYEB6ejq8vLwQHh4OV1dXXL58Ga1btwYA/PXXXwgKCjJ/Sl6Yt7c3\nvvrqK/z0009wc3ODwWAAALz//vtYt24dPvjgA7Ru3brE67Qdia3cHjx4EJcuXcLcuXMBAHq9Hg0b\nNkRMTAzOnTuHsLAwAPl5TkhIsBn3xIkT+OWXXxAVFYVt27Zh8uTJuHXrFvbv3w+53HJoz5gxA927\nd7doO3nyJFq1amX+1K19+/bme+nu/N6B/E/M3dzcoFaryyAbZaNu3bpW90lcv34diYmJAIAmTZpA\nqVQCgFUurly5glGjRgEA2rZti7Zt22LlypU4ePAg5HK5+SxbTEwMjh49ij179gDIP6MJAJ6enqhT\npw4AoE6dOtBqtRbxZ8+ejUmTJqF58+YYO3YsDh8+jG7dulmd0fTw8EBUVJRF240bN8z/v3jxYixZ\nsgSpqano1q2bub158+YA8v+OUlNT7ytflc21a9fg5uaG999/HwBw5swZvPjiiwgPD8eCBQvg4uKC\npKQki0/yANicb27evImWLVsCyB8Xd343s2bNwmeffYaNGzciMDAQffr0qdg3+ZCKy9GdT7IfffRR\nAEDt2rWRmpoKlUqF9PR0TJ8+HS4uLlCr1dDr9fc93l9++WWsXr0azz33HHx9fc05veN+xnVSUhI0\nGg3mzJkDIP9v7YUXXkC7du3M+1y9ehU9evQAALRq1cr892lrPuzevTuuXr2KV155BXK5HJMnTy7b\nJFeAmzdvYsiQIdi1a5fVvG7rmGdr3JY0F3l6elr9zKp6LL3D1jFVrVZbjZ/GjRvDaDQiISEBu3fv\nxvr167Fly5Zij7F3jnvFrVGSk5PRpEkTAEC7du2we/duxMTE4ObNm5gwYQKA/N/NtWvXHHL+Kem4\neunSJbRv3x4SiQQKhQKtWrUq9v7t9PR0JCcnY9q0aQAAjUaDzp07Iysry+Y68s7VSqVZ09gSExOD\nTz75BKtXr4bJZIKTkxOcnJyQlJSEN954wzwv3vl9Pox7zc/NmjUDALi7u6Nx48bm/9dqtbh06RI6\nd+4MAHBzc0OjRo1w/fp1JCcnm688eOyxx2zee1jS2sbWPOHm5oa3334b7777LnJycjB06FCL19xv\nzo8ePYphw4Zh1KhR0Ol0+Pzzz7Fw4UKEh4ejfv368PDwAJB/jM7Ly4OPjw8++eQTODk5ITc313xW\nLTU1FRcvXjRflREfH4/09HTzcSQ3Nxfx8fH3PB4VVbnPeduJt7e3+f8lEgkAIDAwEIMGDUJUVBQ+\n//xz9O/fHwqFAitWrMCyZcswf/58qFQq80GjZ8+eWLVqFZYvX46kpCSL+OvWrUPr1q3x4Ycfon//\n/ubXbN26FXPnzsXGjRtx/vx5nDp1ClKpFCaTqYLeefkrnNuAgAAsWrQIUVFRmDFjBnr27InAwEB0\n6NABUVFR+OqrrzBgwIBiL6PT6/Xm38+IESOQk5OD2rVrm9vuJTAwEP/++y8MBgOEEDh+/Lj5YFb4\ncpBmzZphzZo12LVrFy5cuPCgb71MhYaG4tChQ4iPjweQn4vIyEjExMQAQIk5aNSoEc6cOQMAOH78\nuPlyseeeew6zZs1CeHg4jEYjAgMDMWHCBERFRWH58uXmSfBe+b3zAYa7uzsmTZqEv/76C4GBgaV6\nfzqdDnv37sXSpUuxYcMG7Nixo9ii3hFdvHgR7733njlXAQEBcHd3x8KFC7Fw4UJERkbCx8fHYhGa\nnZ1tc75p3LgxTp8+DSC/mLgz32zZsgVTp07Fxo0bAQD79++v4Hf5cIrLUdFLeu84ePAgbt26haVL\nl2L69OnQaDQQQtz3eN+1axeGDx+OqKgoNGnSBFu3brWIfz/jOjU1FTNmzEBOTg4AwM/PD56enhaX\nyjZq1Mj8+4qOjjYvrGzNh8eOHYOPjw/WrVuHyZMnY+nSpQ+V04qWk5ODbdu2oUaNGjbndVvHPFvj\ntri5qPA8XfhYaStuVXXnmBoUFGQ1fgBg1KhRWLx4MRo3bgx3d/cSj7F35vbi1ii1a9dGXFwcgPyH\nkgH5x9HGjRtjw4YNiIqKwogRIxAUFOSQ809Jx9VGjRqZL7HU6/U4deoUGjRoYDOOp6cnateujU8+\n+QRRUVF4+eWX0bFjR5vryJo1a5pf97BrmoCAAISHhyMqKgoRERF44okncODAAaSmpmLJkiWYNm0a\ntFptmXy4Udr5ubBGjRrhxIkTAPLniJiYGNSrVw8+Pj7mNdbx48fNl7tKJBLz33ZJubA1TyQnJ+Pc\nuXP4+OOPsWbNGixevNiimL3fnG/YsAE//PADgPzL6QsXlbb6tGDBArz22mtYtGgRmjZtas65t7c3\n1q5di7i4OBw8eBD16tVDnTp1sG7dOkRFRWHcuHFo3br1PY9HRfHMXIGjR48iLCwMUqkUubm5mDlz\nJnbs2GH+9zFjxmD27NkYN24ccnJyMHbsWLi5uaFt27YYPXo05HI53N3dkZycjHr16gHI/6VNnToV\nb7/9Nr744gtzrNDQUMyfPx+7d+9GjRo1IJPJoNPpEBQUhLFjx8LV1RW+vr5o1aoV3Nzc8Omnn6JZ\ns2YYNGhQheelLNjKrZOTEyIiIhAeHm6+/2fBggVo2LAh/vrrL4wdOxZqtRp9+vQp9jrhTp064ciR\nIxgzZgyEEBg9ejQuX76Mbdu24dlnn71nv4KCgjBgwAA888wzMJlMaNeuHfr0+f/27i02pq6P4/h3\npmYyRmlppdLqBQmRYIhDqDNFVFCqByUVadpqolSE6lHb9Ji2uCglngg3dWgTGiIoN4jE4QYJSSVa\nEYkYp0Ra0cPMvBdih6dF3/fB8874fS4ne+2uruxZa//nvw6L+wzYbDYbhYWF7N69m8bGRuNL/G/x\n9/ensrKS/Px8Y33VwoULWb9+PXfu3Plu2fT0dHJzczl37hwA5eXlNDU1AZ92Wrp8+TJ//fUX6enp\n5OXl0dDQQHt7OxkZGf2q2549eygpKeHAgQP4+/tz8OBBDh06xLx58/rdblarlYCAAOLj47HZbMye\nPZvQ0NB+lfUGS5cu5cmTJ8TGxmK32/F4PGRlZXH37l02bNjAwIEDCQ4Oxul0GmW+1d/ExMRw8+ZN\n4uLiCA0NNTIVDoeDzZs3M2jQIOx2u/Fy5y2+1UaDBw/u83qHw0FdXR0bNmzAZDIRHh6O0+ns9/Me\nERFBfn4+AwcOxGw2G2tcPuvPcz1+/Hhjl0GbzYbL5SIuLu6roC8xMZGsrCwSExMZPXq0Eej11R8G\nBgayY8cOTp48SU9PD1u2bPnp7fyzfdnfu1wutm7dypIlS6isrOzVr/c15rW3t/d6bhcsWPDDvmjs\n2LHGWNnXfX1JX2Pq2LFjez0/8GmdZ1lZGYcOHQJg0aJFPxxjv/WOUlhYSG5uLna7HYvFQkhICOPG\njSMiIoLExES6urpwOBxGJsHb+p/vjasmk4k7d+6QkJBAd3c3y5YtY/z48bS0tPS6j9lsJi8vj7S0\nNDweD4MGDaKqqoqpU6f2eo/88geJf/pOk5OTQ3FxMZ2dnXR1dVFQUEBISAiHDx82+sWRI0fidDqN\nGRz/q/+2f/5SfHw8BQUFJCYm0tnZSUZGBkFBQZSWllJSUoLH48HPz4/y8nLg06yptLS0H/Z/fb2z\nDB8+nFevXrFu3TrMZjPJyclfZdz62+bFxcUUFxdz/PhxbDYbQ4cOpaioiO7u7j7rsmrVKjIzMxky\nZAgjRoww1vEBxvczJSWFhoYGNm3aRFJSEi6Xi7CwMKKioujq6vruePR3Jo+vzT8QERERkZ+qvr6e\nqKgohg0bxv79+7FYLP3+kU9Efh1l5kRERETku4KCgkhOTsZutzN48GAqKyv/7SqJCMrMiYiIiIiI\neCVtgCIiIiIiIuKFFMyJiIiIiIh4IQVzIiIiIiIiXkjBnIiI+Iz29naKi4tZsWIF0dHRJCUl8fDh\nw++W+XyAsoiIiLfRbpYiIuIT3G43qampzJgxg6amJgYMGMCtW7dITU3lwoULxhl8f/ejsxlFRET+\nXykzJyIiPuH27ds4nU62bdtmHAw7c+ZMKioqcLvd5Ofnk5CQQGRkJCkpKXz8+JHS0lIA4uLiALh+\n/TqxsbGsXr2ajIwM47DX27dvs3LlSlavXk1RUZGRzWtrayMpKYmVK1eSkJDAgwcPAMjOziY9PZ2o\nqCiuXr3KunXrjHqePXuWwsLC39YuIiLiuxTMiYiIT3j06BETJ07EbP56aJs/fz6tra1YLBZOnz7N\nlStX6Ozs5Nq1a+Tn5wPQ2NjI27dv2bt3L0ePHqWpqYk5c+ZQU1NDd3c3WVlZVFdXGxm/z3bt2kVS\nUhLnz58nJyeHzMxMurq6AAgMDOTixYtERkby6tUrnj17BnwK5mJiYn5Tq4iIiC/TNEsREfEJZrOZ\nbx2dOn36dAIDA6mvr6e1tZWnT5/y4cOHr665f/8+L168YOPGjcCnaZsBAQE8fvyYoKAgxo0bB0Bs\nbCxlZWV0dHTw7Nkzli5dCsDkyZMJCAigtbUVAIfDAYDJZGLNmjWcO3eOmJgY3rx5w6RJk35JG4iI\nyJ9FwZyIiPiECRMmcOLECTweDyaTyfh83759OBwOamtr2bhxIzExMbx7965X4OdyuZgyZQqHDx8G\noLOzk46ODpxOJ263u9ff83g8ve7h8XhwuVwA2Gw24/M1a9aQkpKC1WolOjr6p/3PIiLyZ9M0SxER\n8QnTpk0jKCiIAwcOGAHVjRs3OHPmDDdu3CAqKoq1a9cSHBzM3bt3jWv8/Pzo6elh0qRJ3Lt3j7a2\nNgDq6uqoqqpi9OjRvH//npaWFgDOnz8PgL+/P+Hh4TQ3NwNw7949Xr9+zZgxY3rVLSwsjBEjRnDq\n1CkFcyIi8tMoMyciIj7BZDJRV1dHRUUFK1asYMCAAQwdOpQjR47g5+fHzp07uXTpElarlcmTJ/P8\n+XMAIiMjiY6O5syZM5SXl7N9+3bcbjchISFUV1djtVqpqqpi9+7dmM1mRo0aZWTdqqurKSoqora2\nFovFQm1tLVartc/6LV++nObmZkJCQn5bm4iIiG8zeb61wEBERERwu93U1NSQkZGB3W7n2LFjvHz5\nkuzs7H7fo6enh6ysLJYtW2assRMREfmnlJkTERH5DrPZTGBgILGxsVgsFsLCwigrK+t3eY/Hw9y5\nc5k1axaLFy/+hTUVEZE/jTJzIiIiIiIiXkgboIiIiIiIiHghBXMiIiIiIiJeSMGciIiIiIiIF1Iw\nJyIiIiIi4oUUzImIiIiIiHih/wAUiUnk6NVthgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8a151a2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,15))\n",
    "sns.swarmplot(x='Category',y='Protein',data=mcdonalds, hue='Saturated Fat',palette='hot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}