analysis-of-nutrition-data.ipynb

{
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  {
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   "source": [
    "# Analyzing the nutrition content of common foods\n",
    "\n",
    "<h1 id=\"tocheading\">Table of Contents</h1>\n",
    "<div id=\"toc\"></div>\n",
    "\n",
    "\n",
    "## Motivation\n",
    "\n",
    "Federal nutrition programs have been a crucial initiative over the years, and a careful, impartial third party analysis to verify the sanctity of their recommendations is long overdue. An analysis by the CDC earlier this year revealed that the obesity rate in our country has hiked up to 42.4%, a dangerous new peak for the United States. Clearly, something in the system is not working. Is the government pushing for the right foods to be consumed? \n",
    "\n",
    "Therefore, some important questions that one might want to answer with data science techniques are:\n",
    "1. What other nutrients is high protein content correlated with?\n",
    "2. What kinds of clusters of food exist? Can we identify some of these clusters as representing groups of \"healthy\" or \"unhealthy\" foods? If so, are there any surprising foods in either cluster?\n",
    "3. What can one do to reduce cholesterol and fat while keeping protein high in ones diet?\n",
    "\n",
    "\n",
    "We can attempt to answer these questions by analyzing nutrition information of foods whose labels have been uploaded by public users to USDA's database  https://data.nal.usda.gov/dataset/usda-branded-food-products-database. For further reading and understanding of the data, refer to the documentation which can be found in the previous link.\n",
    "\n",
    "The specific dataset used in this project is available at https://data.nal.usda.gov/dataset/usda-branded-food-products-database/resource/c929dc84-1516-4ac7-bbb8-c0c191ca8cec. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading and understanding the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
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   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NDB_No</th>\n",
       "      <th>Nutrient_Code</th>\n",
       "      <th>Nutrient_name</th>\n",
       "      <th>Derivation_Code</th>\n",
       "      <th>Output_value</th>\n",
       "      <th>Output_uom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45127487</td>\n",
       "      <td>203</td>\n",
       "      <td>Protein</td>\n",
       "      <td>LCGA</td>\n",
       "      <td>4.3</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45127487</td>\n",
       "      <td>204</td>\n",
       "      <td>Total lipid (fat)</td>\n",
       "      <td>LCGA</td>\n",
       "      <td>18.9</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>45127487</td>\n",
       "      <td>205</td>\n",
       "      <td>Carbohydrate, by difference</td>\n",
       "      <td>LCGA</td>\n",
       "      <td>72.8</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>45127487</td>\n",
       "      <td>207</td>\n",
       "      <td>Ash</td>\n",
       "      <td>LCGA</td>\n",
       "      <td>2.0</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>45127487</td>\n",
       "      <td>255</td>\n",
       "      <td>Water</td>\n",
       "      <td>LCGA</td>\n",
       "      <td>2.0</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     NDB_No  Nutrient_Code                Nutrient_name Derivation_Code  \\\n",
       "0  45127487            203                      Protein            LCGA   \n",
       "1  45127487            204            Total lipid (fat)            LCGA   \n",
       "2  45127487            205  Carbohydrate, by difference            LCGA   \n",
       "3  45127487            207                          Ash            LCGA   \n",
       "4  45127487            255                        Water            LCGA   \n",
       "\n",
       "   Output_value Output_uom  \n",
       "0           4.3          g  \n",
       "1          18.9          g  \n",
       "2          72.8          g  \n",
       "3           2.0          g  \n",
       "4           2.0          g  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas\n",
    "nutrients = pandas.read_csv('branded_data/nutrients.csv')\n",
    "nutrients.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to \"Derivation_Code_Description.csv\", the \"Derivation_Code\" column identifies the method in which the nutrient information was calculated:\n",
    "\n",
    "- LCCD\tCalculated from a daily value percentage per serving size mea\n",
    "- LCCS\tCalculated from value per serving size measure\n",
    "- LCGA\tGiven by information provider as an 'approximate' value per 100 unit measur\n",
    "- LCGE\tGiven by information provider as an 'exact' value per 100 unit measure\n",
    "- LCGL\tGiven by information provider as a 'less than' value per 100 unit measure\n",
    "- LCSA\tCalculated from an 'approximate' value per serving size measure\n",
    "- LCSE\tCalculated from an 'exact' value per serving size measure\n",
    "- LCSG\tCalculated from a 'greater than' value per serving size measure\n",
    "- LCSL\tCalculated from a 'less than' value per serving size measure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2785: DtypeWarning: Columns (3) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NDB_Number</th>\n",
       "      <th>long_name</th>\n",
       "      <th>data_source</th>\n",
       "      <th>gtin_upc</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>date_modified</th>\n",
       "      <th>date_available</th>\n",
       "      <th>ingredients_english</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45001524</td>\n",
       "      <td>MOCHI ICE CREAM BONBONS</td>\n",
       "      <td>LI</td>\n",
       "      <td>19022128593</td>\n",
       "      <td>G. T. Japan, Inc.</td>\n",
       "      <td>2017-11-15 19:19:38</td>\n",
       "      <td>2017-11-15 19:19:38</td>\n",
       "      <td>ICE CREAM INGREDIENTS: MILK, CREAM, SUGAR, STR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45001528</td>\n",
       "      <td>CHIPOTLE BARBECUE SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>5051379043735</td>\n",
       "      <td>FRESH &amp; EASY</td>\n",
       "      <td>2018-04-26 17:23:31</td>\n",
       "      <td>2018-04-26 17:23:31</td>\n",
       "      <td>WATER, SUGAR, TOMATO PASTE, MOLASSES, DISTILLE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>45001529</td>\n",
       "      <td>HOT &amp; SPICY BARBECUE SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>5051379009434</td>\n",
       "      <td>FRESH &amp; EASY</td>\n",
       "      <td>2018-04-26 18:17:37</td>\n",
       "      <td>2018-04-26 18:17:37</td>\n",
       "      <td>SUGAR, WATER, DISTILLED VINEGAR, TOMATO PASTE,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>45001530</td>\n",
       "      <td>BARBECUE SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>5051379019969</td>\n",
       "      <td>FRESH &amp; EASY</td>\n",
       "      <td>2018-04-26 17:24:00</td>\n",
       "      <td>2018-04-26 17:24:00</td>\n",
       "      <td>TOMATO PUREE (WATER, TOMATO PASTE), SUGAR, DIS...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>45001531</td>\n",
       "      <td>BARBECUE SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>5051379009526</td>\n",
       "      <td>FRESH &amp; EASY</td>\n",
       "      <td>2018-04-26 17:47:41</td>\n",
       "      <td>2018-04-26 17:47:41</td>\n",
       "      <td>SUGAR, DISTILLED VINEGAR, WATER, TOMATO PASTE,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   NDB_Number                   long_name data_source       gtin_upc  \\\n",
       "0    45001524     MOCHI ICE CREAM BONBONS          LI    19022128593   \n",
       "1    45001528     CHIPOTLE BARBECUE SAUCE          LI  5051379043735   \n",
       "2    45001529  HOT & SPICY BARBECUE SAUCE          LI  5051379009434   \n",
       "3    45001530              BARBECUE SAUCE          LI  5051379019969   \n",
       "4    45001531              BARBECUE SAUCE          LI  5051379009526   \n",
       "\n",
       "        manufacturer        date_modified       date_available  \\\n",
       "0  G. T. Japan, Inc.  2017-11-15 19:19:38  2017-11-15 19:19:38   \n",
       "1       FRESH & EASY  2018-04-26 17:23:31  2018-04-26 17:23:31   \n",
       "2       FRESH & EASY  2018-04-26 18:17:37  2018-04-26 18:17:37   \n",
       "3       FRESH & EASY  2018-04-26 17:24:00  2018-04-26 17:24:00   \n",
       "4       FRESH & EASY  2018-04-26 17:47:41  2018-04-26 17:47:41   \n",
       "\n",
       "                                 ingredients_english  \n",
       "0  ICE CREAM INGREDIENTS: MILK, CREAM, SUGAR, STR...  \n",
       "1  WATER, SUGAR, TOMATO PASTE, MOLASSES, DISTILLE...  \n",
       "2  SUGAR, WATER, DISTILLED VINEGAR, TOMATO PASTE,...  \n",
       "3  TOMATO PUREE (WATER, TOMATO PASTE), SUGAR, DIS...  \n",
       "4  SUGAR, DISTILLED VINEGAR, WATER, TOMATO PASTE,...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products = pandas.read_csv('branded_data/products.csv')\n",
    "products.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use panda's groupby method to look at how many nutrients are present in each of the foods in our dataset, which shows us that this number varies and will need to be accounted for in later analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NDB_No\n",
       "45376427    15\n",
       "45376428    14\n",
       "45376429    14\n",
       "45376430    15\n",
       "45376431    15\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groups = nutrients.groupby('NDB_No', as_index='False')\n",
    "groups.size().tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sanitizing data\n",
    "This dataset is too large to do any kind of analysis in a reasonable amount of time (the nutrients table has over 3 million rows!), and contains many foods with little nutrition content. Let's isolate the first 100 foods in the dataset for which there is a significant amount of nutrients in the categories we want to analyze:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NDB_Number</th>\n",
       "      <th>long_name</th>\n",
       "      <th>data_source</th>\n",
       "      <th>gtin_upc</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>date_modified</th>\n",
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       "      <th>ingredients_english</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>236669</th>\n",
       "      <td>45373989</td>\n",
       "      <td>LIGHT LOW-MOISTURE PART-SKIM MOZZARELLA STRING...</td>\n",
       "      <td>LI</td>\n",
       "      <td>036800372351</td>\n",
       "      <td>Topco Associates, Inc.</td>\n",
       "      <td>2018-05-05 02:02:23</td>\n",
       "      <td>2018-05-05 02:02:23</td>\n",
       "      <td>PASTEURIZED PART SKIM MILK, CHEESE CULTURES, S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9372</th>\n",
       "      <td>45020203</td>\n",
       "      <td>BASHAS', BULK LONGHORN COLBY CHEESE</td>\n",
       "      <td>LI</td>\n",
       "      <td>206876803442</td>\n",
       "      <td>BASHAS'</td>\n",
       "      <td>2017-07-14 19:31:43</td>\n",
       "      <td>2017-07-14 19:31:43</td>\n",
       "      <td>CULTURED PASTEURIZED MILK, SALT, ENZYMES, ANNA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108445</th>\n",
       "      <td>45197742</td>\n",
       "      <td>WHOLE MILK YOGURT</td>\n",
       "      <td>LI</td>\n",
       "      <td>687652600637</td>\n",
       "      <td>Sierra Nevada Cheese Co.</td>\n",
       "      <td>2018-04-28 19:37:52</td>\n",
       "      <td>2018-04-28 19:37:52</td>\n",
       "      <td>GRADE A PASTURED GRAZIERS WHOLE MILK, CREAM, N...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198710</th>\n",
       "      <td>45327438</td>\n",
       "      <td>MACARONI &amp; CHEESE DINNER</td>\n",
       "      <td>LI</td>\n",
       "      <td>041250963349</td>\n",
       "      <td>Meijer, Inc.</td>\n",
       "      <td>2018-03-11 04:49:55</td>\n",
       "      <td>2018-03-11 04:49:55</td>\n",
       "      <td>ENRICHED MACARONI PRODUCT (WHEAT FLOUR, DURUM ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163361</th>\n",
       "      <td>45268400</td>\n",
       "      <td>PREMIUM TEXAS BEEF CHILI</td>\n",
       "      <td>LI</td>\n",
       "      <td>758940708998</td>\n",
       "      <td>FAIRWAY LIKE NO OTHER MARKET</td>\n",
       "      <td>2017-11-01 19:21:25</td>\n",
       "      <td>2017-11-01 19:21:25</td>\n",
       "      <td>GROUND BEEF, ONIONS, MIXED PEPPERS, DICED TOMA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25550</th>\n",
       "      <td>45056140</td>\n",
       "      <td>DELICATE PETITE BLUE CHEESE, SOFT-RIPENED CHEESE</td>\n",
       "      <td>LI</td>\n",
       "      <td>74310201006</td>\n",
       "      <td>Marin French Cheese Company</td>\n",
       "      <td>2017-10-13 07:32:35</td>\n",
       "      <td>2017-10-13 07:32:35</td>\n",
       "      <td>CULTURED PASTEURIZED MILK, CREAM, SALT AND ENZ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212421</th>\n",
       "      <td>45347944</td>\n",
       "      <td>DANISH STYLE BUTTER COOKIES</td>\n",
       "      <td>LI</td>\n",
       "      <td>035549953470</td>\n",
       "      <td>CAMBRIDGE &amp; THAMES</td>\n",
       "      <td>2018-01-19 21:23:14</td>\n",
       "      <td>2018-01-19 21:23:14</td>\n",
       "      <td>WHEAT FLOUR, SUGAR, VEGETABLE FAT (PALM OIL AN...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137971</th>\n",
       "      <td>45230819</td>\n",
       "      <td>BITE SIZE PEPPERONI STICKS</td>\n",
       "      <td>LI</td>\n",
       "      <td>070411028733</td>\n",
       "      <td>Oberto Sausage Company</td>\n",
       "      <td>2017-07-14 17:27:19</td>\n",
       "      <td>2017-07-14 17:27:19</td>\n",
       "      <td>BEEF AND PORK, WATER, SALT, LESS THAN 2% OF SP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82329</th>\n",
       "      <td>45167293</td>\n",
       "      <td>WHOLE FOODS MARKET, CORN SALAD, HOT &amp; SWEET</td>\n",
       "      <td>LI</td>\n",
       "      <td>36406302660</td>\n",
       "      <td>Bread &amp; Circus Inc.</td>\n",
       "      <td>2018-03-31 04:46:07</td>\n",
       "      <td>2018-03-31 04:46:07</td>\n",
       "      <td>CORN, BELL PEPPER, ZUCCHINI SQUASH, FETA CHEES...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167772</th>\n",
       "      <td>45273450</td>\n",
       "      <td>ORGANIC SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>036200430675</td>\n",
       "      <td>Mizkan Americas, Inc.</td>\n",
       "      <td>2017-11-01 22:40:31</td>\n",
       "      <td>2017-11-01 22:40:31</td>\n",
       "      <td>ORGANIC TOMATO PUREE (WATER, ORGANIC TOMATO PA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61214</th>\n",
       "      <td>45141222</td>\n",
       "      <td>DOBROVA, JETRENA PASTETA LIVER PATE</td>\n",
       "      <td>LI</td>\n",
       "      <td>783963007797</td>\n",
       "      <td>Tvt's International Export &amp; Import Co.</td>\n",
       "      <td>2017-07-14 17:12:54</td>\n",
       "      <td>2017-07-14 17:12:54</td>\n",
       "      <td>PORK, WATER, PORK LIVER, SODIUM CASEINATE (MIL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232076</th>\n",
       "      <td>45369216</td>\n",
       "      <td>Farmland Polish Smoked Sausage Rope</td>\n",
       "      <td>GDSN</td>\n",
       "      <td>00070247175885</td>\n",
       "      <td>SMITHFIELD FOODS INC.</td>\n",
       "      <td>2017-03-13 09:10:58</td>\n",
       "      <td>2018-02-26 15:22:52</td>\n",
       "      <td>Pork, Mechanically Separated Turkey, Water, Sa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236865</th>\n",
       "      <td>45374185</td>\n",
       "      <td>SMALL CURD LOWFAT COTTAGE CHEESE</td>\n",
       "      <td>LI</td>\n",
       "      <td>074175008321</td>\n",
       "      <td>Stater Bros. Markets Inc.</td>\n",
       "      <td>2018-06-02 18:12:37</td>\n",
       "      <td>2018-06-02 18:12:37</td>\n",
       "      <td>CULTURED NONFAT MILK, MILK, CREAM, CONTAINS LE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67364</th>\n",
       "      <td>45148838</td>\n",
       "      <td>STERLING FOODS, OATMEAL RAISIN COOKIE</td>\n",
       "      <td>LI</td>\n",
       "      <td>88026560043</td>\n",
       "      <td>Sterling Foods, Inc.</td>\n",
       "      <td>2017-07-14 17:26:09</td>\n",
       "      <td>2017-07-14 17:26:09</td>\n",
       "      <td>ENRICHED BLEACHED WHEAT FLOUR (WHEAT FLOUR, MA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59798</th>\n",
       "      <td>45138589</td>\n",
       "      <td>CHEESE STUFFED BREAD STICKS</td>\n",
       "      <td>LI</td>\n",
       "      <td>76845250054</td>\n",
       "      <td>Joseph Campione Inc.</td>\n",
       "      <td>2017-10-28 22:50:34</td>\n",
       "      <td>2017-10-28 22:50:34</td>\n",
       "      <td>BREADSTICK: ENRICHED FLOUR (BLEACHED WHEAT FLO...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95448</th>\n",
       "      <td>45182956</td>\n",
       "      <td>DELI SLICED HONEY HAM</td>\n",
       "      <td>LI</td>\n",
       "      <td>43500010988</td>\n",
       "      <td>Plumrose USA, Inc.</td>\n",
       "      <td>2017-07-14 18:27:54</td>\n",
       "      <td>2017-07-14 18:27:54</td>\n",
       "      <td>CURED WITH: WATER, HONEY, MODIFIED CORN STARCH...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22543</th>\n",
       "      <td>45045464</td>\n",
       "      <td>NASTO'S, ICE CREAM CAKE</td>\n",
       "      <td>LI</td>\n",
       "      <td>727908879193</td>\n",
       "      <td>U.S. Gold</td>\n",
       "      <td>2017-06-24 20:05:36</td>\n",
       "      <td>2017-06-24 20:05:36</td>\n",
       "      <td>MILK, CREAM, SUGAR, CORN SYRUP, SKIM MILK, COC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216594</th>\n",
       "      <td>45352145</td>\n",
       "      <td>COLD BREW COFFEE ICE CREAM</td>\n",
       "      <td>LI</td>\n",
       "      <td>076840000722</td>\n",
       "      <td>Ben &amp; Jerry's Homemade Inc.</td>\n",
       "      <td>2018-02-16 19:44:57</td>\n",
       "      <td>2018-02-16 19:44:57</td>\n",
       "      <td>CREAM, SKIM MILK, LIQUID SUGAR (SUGAR, WATER),...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213622</th>\n",
       "      <td>45349146</td>\n",
       "      <td>LEHI PRIDE PANCAKE MIX</td>\n",
       "      <td>LI</td>\n",
       "      <td>022825200335</td>\n",
       "      <td>Lehi Roller Mills Co. Inc.</td>\n",
       "      <td>2018-01-19 21:18:27</td>\n",
       "      <td>2018-01-19 21:18:27</td>\n",
       "      <td>ENRICHED BLEACHED FLOUR (WHEAT FLOUR, NIACIN, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136263</th>\n",
       "      <td>45228756</td>\n",
       "      <td>A CRUNCHY SALTY SWEET CARAMEL PRETZEL TREAT</td>\n",
       "      <td>LI</td>\n",
       "      <td>813085600269</td>\n",
       "      <td>SNAPPERS</td>\n",
       "      <td>2017-07-14 17:24:04</td>\n",
       "      <td>2017-07-14 17:24:04</td>\n",
       "      <td>DARK CHOCOLATE (SUGAR, CHOCOLATE LIQUOR, COCOA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67217</th>\n",
       "      <td>45148667</td>\n",
       "      <td>PUMPKIN SANDWICH COOKIES</td>\n",
       "      <td>LI</td>\n",
       "      <td>78742111261</td>\n",
       "      <td>Wal-Mart Stores, Inc.</td>\n",
       "      <td>2017-07-14 17:25:53</td>\n",
       "      <td>2017-07-14 17:25:53</td>\n",
       "      <td>SUGAR, ENRICHED UNBLEACHED WHEAT FLOUR (FLOUR,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91566</th>\n",
       "      <td>45178326</td>\n",
       "      <td>HALF &amp; HALF</td>\n",
       "      <td>LI</td>\n",
       "      <td>74164345019</td>\n",
       "      <td>Lowe's Food Stores, Inc.</td>\n",
       "      <td>2018-01-20 04:04:18</td>\n",
       "      <td>2018-01-20 04:04:18</td>\n",
       "      <td>MILK, CREAM, DISODIUM PHOSPHATE.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197767</th>\n",
       "      <td>45326437</td>\n",
       "      <td>CARROTS WITH RANCH DIP</td>\n",
       "      <td>LI</td>\n",
       "      <td>077745222929</td>\n",
       "      <td>READY PAC FOODS</td>\n",
       "      <td>2017-10-13 18:06:16</td>\n",
       "      <td>2017-10-13 18:06:16</td>\n",
       "      <td>BABY CARROTS, RANCH DIP (CULTURED BUTTERMILK, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170785</th>\n",
       "      <td>45276889</td>\n",
       "      <td>ROLLED PIE CRUSTS</td>\n",
       "      <td>LI</td>\n",
       "      <td>07078400737</td>\n",
       "      <td>Tops Markets, LLC</td>\n",
       "      <td>2018-01-19 23:26:58</td>\n",
       "      <td>2018-01-19 23:26:58</td>\n",
       "      <td>ENRICHED BLEACHED FLOUR (WHEAT FLOUR, NIACIN, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212832</th>\n",
       "      <td>45348356</td>\n",
       "      <td>LOWFAT YOGURT</td>\n",
       "      <td>LI</td>\n",
       "      <td>742365007125</td>\n",
       "      <td>WWF Operating Company</td>\n",
       "      <td>2018-01-19 21:21:14</td>\n",
       "      <td>2018-01-19 21:21:14</td>\n",
       "      <td>CULTURED GRADE A REDUCED FAT ORGANIC MILK, ORG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124999</th>\n",
       "      <td>45216200</td>\n",
       "      <td>BREAKFAST SAUSAGE</td>\n",
       "      <td>LI</td>\n",
       "      <td>30034030643</td>\n",
       "      <td>Giant Eagle, Inc.</td>\n",
       "      <td>2017-07-14 18:47:26</td>\n",
       "      <td>2017-07-14 18:47:26</td>\n",
       "      <td>PORK, WATER, SEASONINGS (SALT, SPICES, DEXTROS...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47887</th>\n",
       "      <td>45108380</td>\n",
       "      <td>SHARP CHEDDAR CHEESE SNACK SPREAD</td>\n",
       "      <td>LI</td>\n",
       "      <td>48707432243</td>\n",
       "      <td>Old Fashioned Foods, Inc.</td>\n",
       "      <td>2017-07-14 20:29:13</td>\n",
       "      <td>2017-07-14 20:29:13</td>\n",
       "      <td>CHEESE (PASTEURIZED MILK, CHEESE CULTURES, SAL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52221</th>\n",
       "      <td>45121088</td>\n",
       "      <td>CREME PIE</td>\n",
       "      <td>LI</td>\n",
       "      <td>41458105565</td>\n",
       "      <td>The Schwan Food Company</td>\n",
       "      <td>2018-05-19 17:12:18</td>\n",
       "      <td>2018-05-19 17:12:18</td>\n",
       "      <td>WATER, SUGAR, REDUCED FAT SWEETENED CONDENSED ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206982</th>\n",
       "      <td>45342401</td>\n",
       "      <td>HAM STEAKS</td>\n",
       "      <td>LI</td>\n",
       "      <td>050500100823</td>\n",
       "      <td>FARMER JOHN</td>\n",
       "      <td>2018-01-19 22:08:48</td>\n",
       "      <td>2018-01-19 22:08:48</td>\n",
       "      <td>WATER, SALT, SODIUM LACTATE, SUGAR, CORN SYRUP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201184</th>\n",
       "      <td>45330834</td>\n",
       "      <td>FIT MENU ROBUST, SATISFYING MEALS</td>\n",
       "      <td>LI</td>\n",
       "      <td>078742249438</td>\n",
       "      <td>Wal-Mart Stores, Inc.</td>\n",
       "      <td>2017-10-13 18:20:52</td>\n",
       "      <td>2017-10-13 18:20:52</td>\n",
       "      <td>POTATOES, GRILLED SEASONED CHICKEN WHITE MEAT ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170618</th>\n",
       "      <td>45276706</td>\n",
       "      <td>BEEF STICK</td>\n",
       "      <td>LI</td>\n",
       "      <td>852675006142</td>\n",
       "      <td>The New Primal, LLC</td>\n",
       "      <td>2018-01-30 03:20:08</td>\n",
       "      <td>2018-01-30 03:20:08</td>\n",
       "      <td>GRASS-FED AND GRASS-FINISHED BEEF, HONEY, SEA ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213443</th>\n",
       "      <td>45348967</td>\n",
       "      <td>GREEK FETA SALAD</td>\n",
       "      <td>LI</td>\n",
       "      <td>072368393810</td>\n",
       "      <td>George DeLallo Co., Inc.</td>\n",
       "      <td>2018-01-19 21:19:43</td>\n",
       "      <td>2018-01-19 21:19:43</td>\n",
       "      <td>FETA CHEESE (PASTEURIZED MILK, CHEESE CULTURES...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200358</th>\n",
       "      <td>45329988</td>\n",
       "      <td>ORGANIC RAW MILK CHEESE</td>\n",
       "      <td>LI</td>\n",
       "      <td>837152000288</td>\n",
       "      <td>TRICKLING SPRINGS ORGANIC</td>\n",
       "      <td>2017-10-13 18:06:58</td>\n",
       "      <td>2017-10-13 18:06:58</td>\n",
       "      <td>RAW ORGANIC WHOLE MILK, SEA SALT, ENZYMES, PRO...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221282</th>\n",
       "      <td>45356886</td>\n",
       "      <td>ATLANTIC SALMON FILLET PORTIONS</td>\n",
       "      <td>LI</td>\n",
       "      <td>078742250892</td>\n",
       "      <td>MEMBER'S MARK</td>\n",
       "      <td>2018-03-02 22:56:38</td>\n",
       "      <td>2018-03-02 22:56:38</td>\n",
       "      <td>ATLANTIC SALMON, COLOR ADDED IN FEED.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33424</th>\n",
       "      <td>45080613</td>\n",
       "      <td>SOUR CREAM AND CHIVE POTATOES</td>\n",
       "      <td>LI</td>\n",
       "      <td>41250946571</td>\n",
       "      <td>Meijer, Inc.</td>\n",
       "      <td>2017-07-14 20:11:25</td>\n",
       "      <td>2017-07-14 20:11:25</td>\n",
       "      <td>DEHYDRATED POTATO WITH PRESERVATIVE (SODIUM BI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71668</th>\n",
       "      <td>45154170</td>\n",
       "      <td>TARGET, GOURMET MINI BARK, WHITE CHOCOLATE PUM...</td>\n",
       "      <td>LI</td>\n",
       "      <td>845777012746</td>\n",
       "      <td>G. Debbas Chocolatier, Inc.</td>\n",
       "      <td>2017-07-14 17:34:50</td>\n",
       "      <td>2017-07-14 17:34:50</td>\n",
       "      <td>WHITE CHOCOLATE (SUGAR, COCOA BUTTER, WHOLE MI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94258</th>\n",
       "      <td>45181567</td>\n",
       "      <td>VANILLA FLAVORED ICE CREAM WITH COOKIE DOUGH P...</td>\n",
       "      <td>LI</td>\n",
       "      <td>21130098965</td>\n",
       "      <td>Safeway, Inc.</td>\n",
       "      <td>2018-04-16 20:15:24</td>\n",
       "      <td>2018-04-16 20:15:24</td>\n",
       "      <td>SKIM MILK, SUGAR, COOKIE DOUGH (WHEAT FLOUR, D...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178312</th>\n",
       "      <td>45284926</td>\n",
       "      <td>GREEK STYLE SALAD WITH VINAIGRETTE DRESSING</td>\n",
       "      <td>LI</td>\n",
       "      <td>045009854131</td>\n",
       "      <td>Triple 'B' Corporation</td>\n",
       "      <td>2017-07-14 18:54:59</td>\n",
       "      <td>2017-07-14 18:54:59</td>\n",
       "      <td>ROMAINE LETTUCE, VINAIGRETTE DRESSING (SOYBEAN...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12888</th>\n",
       "      <td>45027769</td>\n",
       "      <td>HELUVA GOOD!, BODACIOUS ONION DIP</td>\n",
       "      <td>LI</td>\n",
       "      <td>73570130071</td>\n",
       "      <td>HP Hood LLC</td>\n",
       "      <td>2017-06-25 03:28:57</td>\n",
       "      <td>2017-06-25 03:28:57</td>\n",
       "      <td>CULTURED PASTEURIZED MILK, CREAM AND NONFAT MI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204112</th>\n",
       "      <td>45336653</td>\n",
       "      <td>TEXAS TRADITIONS SMOKED SAUSAGE</td>\n",
       "      <td>LI</td>\n",
       "      <td>070133008440</td>\n",
       "      <td>BLUERIBBON</td>\n",
       "      <td>2018-01-10 16:08:41</td>\n",
       "      <td>2018-01-10 16:08:41</td>\n",
       "      <td>PORK, WATER, BEEF, PASTEURIZED PROCESS CHEDDAR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67738</th>\n",
       "      <td>45149319</td>\n",
       "      <td>LOFTHOUSE COOKIES, FROSTED SUGAR COOKIES</td>\n",
       "      <td>LI</td>\n",
       "      <td>708971925741</td>\n",
       "      <td>Lofthouse Foods</td>\n",
       "      <td>2017-07-14 17:26:58</td>\n",
       "      <td>2017-07-14 17:26:58</td>\n",
       "      <td>SUGAR, ENRICHED BLEACHED WHEAT FLOUR (FLOUR, N...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68955</th>\n",
       "      <td>45150818</td>\n",
       "      <td>MINT CHOCOLATE COOKIES</td>\n",
       "      <td>LI</td>\n",
       "      <td>18169482087</td>\n",
       "      <td>Byerly Foods International</td>\n",
       "      <td>2017-07-14 17:29:18</td>\n",
       "      <td>2017-07-14 17:29:18</td>\n",
       "      <td>DARK KARO SYRUP (DARK CORN SYRUP, REFINERS SYR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134460</th>\n",
       "      <td>45226839</td>\n",
       "      <td>EGG NOG</td>\n",
       "      <td>LI</td>\n",
       "      <td>041483037633</td>\n",
       "      <td>Kemps LLC</td>\n",
       "      <td>2018-03-10 21:59:08</td>\n",
       "      <td>2018-03-10 21:59:08</td>\n",
       "      <td>NONFAT MILK, CREAM, SUGAR, CORN SYRUP, SUGARED...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203085</th>\n",
       "      <td>45333219</td>\n",
       "      <td>THIN CRUST SUPREME PIZZA</td>\n",
       "      <td>LI</td>\n",
       "      <td>078742253824</td>\n",
       "      <td>Wal-Mart Stores, Inc.</td>\n",
       "      <td>2017-11-01 22:10:59</td>\n",
       "      <td>2017-11-01 22:10:59</td>\n",
       "      <td>CRUST (WHEAT FLOUR, WATER, SOYBEAN OIL, SUGAR,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165735</th>\n",
       "      <td>45270973</td>\n",
       "      <td>DRIZZLEND MILK CHOCOLATE PRETZELS</td>\n",
       "      <td>LI</td>\n",
       "      <td>788709800892</td>\n",
       "      <td>Ferris Coffee &amp; Nut Co.</td>\n",
       "      <td>2017-07-14 19:58:54</td>\n",
       "      <td>2017-07-14 19:58:54</td>\n",
       "      <td>MILK CHOCOLATE (SUGAR WHOLE MILK, COCOA BUTTER...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106566</th>\n",
       "      <td>45195714</td>\n",
       "      <td>ROAST BEEF &amp; CHEDDAR ON WHOLE GRAIN BREAD</td>\n",
       "      <td>LI</td>\n",
       "      <td>30223011965</td>\n",
       "      <td>Taylor Fresh Foods, Inc.</td>\n",
       "      <td>2017-07-14 17:57:32</td>\n",
       "      <td>2017-07-14 17:57:32</td>\n",
       "      <td>ROAST BEEF (BEEF WATER, CONTAINS LESS THAN 2% ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48869</th>\n",
       "      <td>45110723</td>\n",
       "      <td>TUNA CREATIONS</td>\n",
       "      <td>LI</td>\n",
       "      <td>80000516046</td>\n",
       "      <td>StarKist Co.</td>\n",
       "      <td>2018-03-11 05:26:42</td>\n",
       "      <td>2018-03-11 05:26:42</td>\n",
       "      <td>LIGHT TUNA, CAYENNE PEPPER SAUCE (AGED CAYENNE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228610</th>\n",
       "      <td>45365399</td>\n",
       "      <td>VENISON PROTEIN BAR</td>\n",
       "      <td>LI</td>\n",
       "      <td>732153029248</td>\n",
       "      <td>EPIC</td>\n",
       "      <td>2017-10-13 18:10:39</td>\n",
       "      <td>2017-10-13 18:10:39</td>\n",
       "      <td>GRASS FED VENISON, LACTIC ACID*, SEA SALT, CEL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171940</th>\n",
       "      <td>45278090</td>\n",
       "      <td>CHOCOLATE TULIP</td>\n",
       "      <td>LI</td>\n",
       "      <td>050428471906</td>\n",
       "      <td>CVS Pharmacy, Inc.</td>\n",
       "      <td>2017-07-14 20:27:10</td>\n",
       "      <td>2017-07-14 20:27:10</td>\n",
       "      <td>SUGAR, COCOA BUTTER, WHOLE MILK POWDER, COCOA ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173522</th>\n",
       "      <td>45279785</td>\n",
       "      <td>MARBLED COLBY JACK CHEESE</td>\n",
       "      <td>LI</td>\n",
       "      <td>07078401600</td>\n",
       "      <td>Tops Markets, LLC</td>\n",
       "      <td>2018-01-19 23:19:08</td>\n",
       "      <td>2018-01-19 23:19:08</td>\n",
       "      <td>PASTEURIZED MILK, CHEESE CULTURE, SALT, ENZYME...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48598</th>\n",
       "      <td>45109919</td>\n",
       "      <td>ICE CREAM</td>\n",
       "      <td>LI</td>\n",
       "      <td>70640011612</td>\n",
       "      <td>Wells Enterprises, Inc.</td>\n",
       "      <td>2018-03-10 20:42:33</td>\n",
       "      <td>2018-03-10 20:42:33</td>\n",
       "      <td>MILK, BUTTERMILK, CREAM, WHEY, CORN SYRUP, HIG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152958</th>\n",
       "      <td>45255017</td>\n",
       "      <td>WILD CAUGHT TUNA STEAKS</td>\n",
       "      <td>LI</td>\n",
       "      <td>041682100503</td>\n",
       "      <td>THE QUEEN 'O' OCEAN</td>\n",
       "      <td>2017-07-14 18:27:20</td>\n",
       "      <td>2017-07-14 18:27:20</td>\n",
       "      <td>TUNA FISH &amp; FILTERED WOOD SMOKE (ADDED PRESERV...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104744</th>\n",
       "      <td>45193757</td>\n",
       "      <td>ITALIA ALFREDO PASTA SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>15229411285</td>\n",
       "      <td>F.Lli Sacla' Spa</td>\n",
       "      <td>2017-07-14 18:48:35</td>\n",
       "      <td>2017-07-14 18:48:35</td>\n",
       "      <td>WATER, WHIPPING CREAM, BUTTER, MODIFIED CORN S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109572</th>\n",
       "      <td>45198979</td>\n",
       "      <td>BBQ SAUCE</td>\n",
       "      <td>LI</td>\n",
       "      <td>77890392676</td>\n",
       "      <td>Wegmans Food Markets, Inc.</td>\n",
       "      <td>2017-07-14 18:04:34</td>\n",
       "      <td>2017-07-14 18:04:34</td>\n",
       "      <td>PORK, BARBECUE SAUCE (TOMATO PUREE [WATER, TOM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133178</th>\n",
       "      <td>45225414</td>\n",
       "      <td>REDUCED FAT ICE CREAM</td>\n",
       "      <td>LI</td>\n",
       "      <td>041900074289</td>\n",
       "      <td>Dean Foods Company</td>\n",
       "      <td>2018-03-11 04:26:18</td>\n",
       "      <td>2018-03-11 04:26:18</td>\n",
       "      <td>NONFAT MILK AND MILKFAT, SUGAR, SWEETCREAM BUT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214900</th>\n",
       "      <td>45350444</td>\n",
       "      <td>SPREADABLE NEW YORK CHEDDAR CHEESE</td>\n",
       "      <td>LI</td>\n",
       "      <td>041711022028</td>\n",
       "      <td>Original Herkimer County Cheese Company Inc</td>\n",
       "      <td>2018-04-09 19:18:03</td>\n",
       "      <td>2018-04-09 19:18:03</td>\n",
       "      <td>NY CHEDDAR CHEESE (CULTURED MILK, SALT, ENZYME...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112073</th>\n",
       "      <td>45201740</td>\n",
       "      <td>FAT FREE MILK</td>\n",
       "      <td>LI</td>\n",
       "      <td>24321908302</td>\n",
       "      <td>Agropur Inc. Division Natrel USA</td>\n",
       "      <td>2018-05-18 15:06:28</td>\n",
       "      <td>2018-05-18 15:06:28</td>\n",
       "      <td>GRADE A UHT FAT FREE MILK, VITAMIN A PALMITATE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119429</th>\n",
       "      <td>45210048</td>\n",
       "      <td>MINIS MILK CHOCOLATE TOFFEE CRISP</td>\n",
       "      <td>LI</td>\n",
       "      <td>747599319785</td>\n",
       "      <td>Ghirardelli Chocolate Company</td>\n",
       "      <td>2017-07-14 18:36:14</td>\n",
       "      <td>2017-07-14 18:36:14</td>\n",
       "      <td>SUGAR, COCOA BUTTER, WHOLE MILK POWDER, UNSWEE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18689</th>\n",
       "      <td>45038433</td>\n",
       "      <td>YOGURT</td>\n",
       "      <td>LI</td>\n",
       "      <td>36632018342</td>\n",
       "      <td>The Dannon Company, Inc.</td>\n",
       "      <td>2018-04-10 23:43:13</td>\n",
       "      <td>2018-04-10 23:43:13</td>\n",
       "      <td>YOGURT (CULTURED GRADE A NON FAT MILK, CREAM, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104844</th>\n",
       "      <td>45193868</td>\n",
       "      <td>LOW FAT YOGURT</td>\n",
       "      <td>LI</td>\n",
       "      <td>21130077441</td>\n",
       "      <td>Safeway, Inc.</td>\n",
       "      <td>2018-01-20 03:41:45</td>\n",
       "      <td>2018-01-20 03:41:45</td>\n",
       "      <td>CULTURED PASTEURIZED GRADE A LOWFAT MILK, SUGA...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       NDB_Number                                          long_name  \\\n",
       "236669   45373989  LIGHT LOW-MOISTURE PART-SKIM MOZZARELLA STRING...   \n",
       "9372     45020203                BASHAS', BULK LONGHORN COLBY CHEESE   \n",
       "108445   45197742                                  WHOLE MILK YOGURT   \n",
       "198710   45327438                           MACARONI & CHEESE DINNER   \n",
       "163361   45268400                           PREMIUM TEXAS BEEF CHILI   \n",
       "25550    45056140   DELICATE PETITE BLUE CHEESE, SOFT-RIPENED CHEESE   \n",
       "212421   45347944                        DANISH STYLE BUTTER COOKIES   \n",
       "137971   45230819                         BITE SIZE PEPPERONI STICKS   \n",
       "82329    45167293        WHOLE FOODS MARKET, CORN SALAD, HOT & SWEET   \n",
       "167772   45273450                                      ORGANIC SAUCE   \n",
       "61214    45141222                DOBROVA, JETRENA PASTETA LIVER PATE   \n",
       "232076   45369216                Farmland Polish Smoked Sausage Rope   \n",
       "236865   45374185                   SMALL CURD LOWFAT COTTAGE CHEESE   \n",
       "67364    45148838              STERLING FOODS, OATMEAL RAISIN COOKIE   \n",
       "59798    45138589                        CHEESE STUFFED BREAD STICKS   \n",
       "95448    45182956                              DELI SLICED HONEY HAM   \n",
       "22543    45045464                            NASTO'S, ICE CREAM CAKE   \n",
       "216594   45352145                         COLD BREW COFFEE ICE CREAM   \n",
       "213622   45349146                             LEHI PRIDE PANCAKE MIX   \n",
       "136263   45228756        A CRUNCHY SALTY SWEET CARAMEL PRETZEL TREAT   \n",
       "67217    45148667                           PUMPKIN SANDWICH COOKIES   \n",
       "91566    45178326                                        HALF & HALF   \n",
       "197767   45326437                             CARROTS WITH RANCH DIP   \n",
       "170785   45276889                                  ROLLED PIE CRUSTS   \n",
       "212832   45348356                                      LOWFAT YOGURT   \n",
       "124999   45216200                                  BREAKFAST SAUSAGE   \n",
       "47887    45108380                  SHARP CHEDDAR CHEESE SNACK SPREAD   \n",
       "52221    45121088                                          CREME PIE   \n",
       "206982   45342401                                         HAM STEAKS   \n",
       "201184   45330834                  FIT MENU ROBUST, SATISFYING MEALS   \n",
       "...           ...                                                ...   \n",
       "170618   45276706                                         BEEF STICK   \n",
       "213443   45348967                                   GREEK FETA SALAD   \n",
       "200358   45329988                            ORGANIC RAW MILK CHEESE   \n",
       "221282   45356886                    ATLANTIC SALMON FILLET PORTIONS   \n",
       "33424    45080613                      SOUR CREAM AND CHIVE POTATOES   \n",
       "71668    45154170  TARGET, GOURMET MINI BARK, WHITE CHOCOLATE PUM...   \n",
       "94258    45181567  VANILLA FLAVORED ICE CREAM WITH COOKIE DOUGH P...   \n",
       "178312   45284926        GREEK STYLE SALAD WITH VINAIGRETTE DRESSING   \n",
       "12888    45027769                  HELUVA GOOD!, BODACIOUS ONION DIP   \n",
       "204112   45336653                    TEXAS TRADITIONS SMOKED SAUSAGE   \n",
       "67738    45149319           LOFTHOUSE COOKIES, FROSTED SUGAR COOKIES   \n",
       "68955    45150818                             MINT CHOCOLATE COOKIES   \n",
       "134460   45226839                                            EGG NOG   \n",
       "203085   45333219                           THIN CRUST SUPREME PIZZA   \n",
       "165735   45270973                  DRIZZLEND MILK CHOCOLATE PRETZELS   \n",
       "106566   45195714          ROAST BEEF & CHEDDAR ON WHOLE GRAIN BREAD   \n",
       "48869    45110723                                     TUNA CREATIONS   \n",
       "228610   45365399                                VENISON PROTEIN BAR   \n",
       "171940   45278090                                    CHOCOLATE TULIP   \n",
       "173522   45279785                          MARBLED COLBY JACK CHEESE   \n",
       "48598    45109919                                          ICE CREAM   \n",
       "152958   45255017                            WILD CAUGHT TUNA STEAKS   \n",
       "104744   45193757                         ITALIA ALFREDO PASTA SAUCE   \n",
       "109572   45198979                                          BBQ SAUCE   \n",
       "133178   45225414                              REDUCED FAT ICE CREAM   \n",
       "214900   45350444                 SPREADABLE NEW YORK CHEDDAR CHEESE   \n",
       "112073   45201740                                      FAT FREE MILK   \n",
       "119429   45210048                  MINIS MILK CHOCOLATE TOFFEE CRISP   \n",
       "18689    45038433                                             YOGURT   \n",
       "104844   45193868                                     LOW FAT YOGURT   \n",
       "\n",
       "       data_source        gtin_upc  \\\n",
       "236669          LI    036800372351   \n",
       "9372            LI    206876803442   \n",
       "108445          LI    687652600637   \n",
       "198710          LI    041250963349   \n",
       "163361          LI    758940708998   \n",
       "25550           LI     74310201006   \n",
       "212421          LI    035549953470   \n",
       "137971          LI    070411028733   \n",
       "82329           LI     36406302660   \n",
       "167772          LI    036200430675   \n",
       "61214           LI    783963007797   \n",
       "232076        GDSN  00070247175885   \n",
       "236865          LI    074175008321   \n",
       "67364           LI     88026560043   \n",
       "59798           LI     76845250054   \n",
       "95448           LI     43500010988   \n",
       "22543           LI    727908879193   \n",
       "216594          LI    076840000722   \n",
       "213622          LI    022825200335   \n",
       "136263          LI    813085600269   \n",
       "67217           LI     78742111261   \n",
       "91566           LI     74164345019   \n",
       "197767          LI    077745222929   \n",
       "170785          LI     07078400737   \n",
       "212832          LI    742365007125   \n",
       "124999          LI     30034030643   \n",
       "47887           LI     48707432243   \n",
       "52221           LI     41458105565   \n",
       "206982          LI    050500100823   \n",
       "201184          LI    078742249438   \n",
       "...            ...             ...   \n",
       "170618          LI    852675006142   \n",
       "213443          LI    072368393810   \n",
       "200358          LI    837152000288   \n",
       "221282          LI    078742250892   \n",
       "33424           LI     41250946571   \n",
       "71668           LI    845777012746   \n",
       "94258           LI     21130098965   \n",
       "178312          LI    045009854131   \n",
       "12888           LI     73570130071   \n",
       "204112          LI    070133008440   \n",
       "67738           LI    708971925741   \n",
       "68955           LI     18169482087   \n",
       "134460          LI    041483037633   \n",
       "203085          LI    078742253824   \n",
       "165735          LI    788709800892   \n",
       "106566          LI     30223011965   \n",
       "48869           LI     80000516046   \n",
       "228610          LI    732153029248   \n",
       "171940          LI    050428471906   \n",
       "173522          LI     07078401600   \n",
       "48598           LI     70640011612   \n",
       "152958          LI    041682100503   \n",
       "104744          LI     15229411285   \n",
       "109572          LI     77890392676   \n",
       "133178          LI    041900074289   \n",
       "214900          LI    041711022028   \n",
       "112073          LI     24321908302   \n",
       "119429          LI    747599319785   \n",
       "18689           LI     36632018342   \n",
       "104844          LI     21130077441   \n",
       "\n",
       "                                       manufacturer        date_modified  \\\n",
       "236669                       Topco Associates, Inc.  2018-05-05 02:02:23   \n",
       "9372                                        BASHAS'  2017-07-14 19:31:43   \n",
       "108445                     Sierra Nevada Cheese Co.  2018-04-28 19:37:52   \n",
       "198710                                 Meijer, Inc.  2018-03-11 04:49:55   \n",
       "163361                 FAIRWAY LIKE NO OTHER MARKET  2017-11-01 19:21:25   \n",
       "25550                   Marin French Cheese Company  2017-10-13 07:32:35   \n",
       "212421                           CAMBRIDGE & THAMES  2018-01-19 21:23:14   \n",
       "137971                       Oberto Sausage Company  2017-07-14 17:27:19   \n",
       "82329                           Bread & Circus Inc.  2018-03-31 04:46:07   \n",
       "167772                        Mizkan Americas, Inc.  2017-11-01 22:40:31   \n",
       "61214       Tvt's International Export & Import Co.  2017-07-14 17:12:54   \n",
       "232076                        SMITHFIELD FOODS INC.  2017-03-13 09:10:58   \n",
       "236865                    Stater Bros. Markets Inc.  2018-06-02 18:12:37   \n",
       "67364                          Sterling Foods, Inc.  2017-07-14 17:26:09   \n",
       "59798                          Joseph Campione Inc.  2017-10-28 22:50:34   \n",
       "95448                            Plumrose USA, Inc.  2017-07-14 18:27:54   \n",
       "22543                                     U.S. Gold  2017-06-24 20:05:36   \n",
       "216594                  Ben & Jerry's Homemade Inc.  2018-02-16 19:44:57   \n",
       "213622                   Lehi Roller Mills Co. Inc.  2018-01-19 21:18:27   \n",
       "136263                                     SNAPPERS  2017-07-14 17:24:04   \n",
       "67217                         Wal-Mart Stores, Inc.  2017-07-14 17:25:53   \n",
       "91566                      Lowe's Food Stores, Inc.  2018-01-20 04:04:18   \n",
       "197767                              READY PAC FOODS  2017-10-13 18:06:16   \n",
       "170785                            Tops Markets, LLC  2018-01-19 23:26:58   \n",
       "212832                        WWF Operating Company  2018-01-19 21:21:14   \n",
       "124999                            Giant Eagle, Inc.  2017-07-14 18:47:26   \n",
       "47887                     Old Fashioned Foods, Inc.  2017-07-14 20:29:13   \n",
       "52221                       The Schwan Food Company  2018-05-19 17:12:18   \n",
       "206982                                  FARMER JOHN  2018-01-19 22:08:48   \n",
       "201184                        Wal-Mart Stores, Inc.  2017-10-13 18:20:52   \n",
       "...                                             ...                  ...   \n",
       "170618                          The New Primal, LLC  2018-01-30 03:20:08   \n",
       "213443                     George DeLallo Co., Inc.  2018-01-19 21:19:43   \n",
       "200358                    TRICKLING SPRINGS ORGANIC  2017-10-13 18:06:58   \n",
       "221282                                MEMBER'S MARK  2018-03-02 22:56:38   \n",
       "33424                                  Meijer, Inc.  2017-07-14 20:11:25   \n",
       "71668                   G. Debbas Chocolatier, Inc.  2017-07-14 17:34:50   \n",
       "94258                                 Safeway, Inc.  2018-04-16 20:15:24   \n",
       "178312                       Triple 'B' Corporation  2017-07-14 18:54:59   \n",
       "12888                                   HP Hood LLC  2017-06-25 03:28:57   \n",
       "204112                                   BLUERIBBON  2018-01-10 16:08:41   \n",
       "67738                               Lofthouse Foods  2017-07-14 17:26:58   \n",
       "68955                    Byerly Foods International  2017-07-14 17:29:18   \n",
       "134460                                    Kemps LLC  2018-03-10 21:59:08   \n",
       "203085                        Wal-Mart Stores, Inc.  2017-11-01 22:10:59   \n",
       "165735                      Ferris Coffee & Nut Co.  2017-07-14 19:58:54   \n",
       "106566                     Taylor Fresh Foods, Inc.  2017-07-14 17:57:32   \n",
       "48869                                  StarKist Co.  2018-03-11 05:26:42   \n",
       "228610                                         EPIC  2017-10-13 18:10:39   \n",
       "171940                           CVS Pharmacy, Inc.  2017-07-14 20:27:10   \n",
       "173522                            Tops Markets, LLC  2018-01-19 23:19:08   \n",
       "48598                       Wells Enterprises, Inc.  2018-03-10 20:42:33   \n",
       "152958                          THE QUEEN 'O' OCEAN  2017-07-14 18:27:20   \n",
       "104744                             F.Lli Sacla' Spa  2017-07-14 18:48:35   \n",
       "109572                   Wegmans Food Markets, Inc.  2017-07-14 18:04:34   \n",
       "133178                           Dean Foods Company  2018-03-11 04:26:18   \n",
       "214900  Original Herkimer County Cheese Company Inc  2018-04-09 19:18:03   \n",
       "112073             Agropur Inc. Division Natrel USA  2018-05-18 15:06:28   \n",
       "119429                Ghirardelli Chocolate Company  2017-07-14 18:36:14   \n",
       "18689                      The Dannon Company, Inc.  2018-04-10 23:43:13   \n",
       "104844                                Safeway, Inc.  2018-01-20 03:41:45   \n",
       "\n",
       "             date_available                                ingredients_english  \n",
       "236669  2018-05-05 02:02:23  PASTEURIZED PART SKIM MILK, CHEESE CULTURES, S...  \n",
       "9372    2017-07-14 19:31:43  CULTURED PASTEURIZED MILK, SALT, ENZYMES, ANNA...  \n",
       "108445  2018-04-28 19:37:52  GRADE A PASTURED GRAZIERS WHOLE MILK, CREAM, N...  \n",
       "198710  2018-03-11 04:49:55  ENRICHED MACARONI PRODUCT (WHEAT FLOUR, DURUM ...  \n",
       "163361  2017-11-01 19:21:25  GROUND BEEF, ONIONS, MIXED PEPPERS, DICED TOMA...  \n",
       "25550   2017-10-13 07:32:35  CULTURED PASTEURIZED MILK, CREAM, SALT AND ENZ...  \n",
       "212421  2018-01-19 21:23:14  WHEAT FLOUR, SUGAR, VEGETABLE FAT (PALM OIL AN...  \n",
       "137971  2017-07-14 17:27:19  BEEF AND PORK, WATER, SALT, LESS THAN 2% OF SP...  \n",
       "82329   2018-03-31 04:46:07  CORN, BELL PEPPER, ZUCCHINI SQUASH, FETA CHEES...  \n",
       "167772  2017-11-01 22:40:31  ORGANIC TOMATO PUREE (WATER, ORGANIC TOMATO PA...  \n",
       "61214   2017-07-14 17:12:54  PORK, WATER, PORK LIVER, SODIUM CASEINATE (MIL...  \n",
       "232076  2018-02-26 15:22:52  Pork, Mechanically Separated Turkey, Water, Sa...  \n",
       "236865  2018-06-02 18:12:37  CULTURED NONFAT MILK, MILK, CREAM, CONTAINS LE...  \n",
       "67364   2017-07-14 17:26:09  ENRICHED BLEACHED WHEAT FLOUR (WHEAT FLOUR, MA...  \n",
       "59798   2017-10-28 22:50:34  BREADSTICK: ENRICHED FLOUR (BLEACHED WHEAT FLO...  \n",
       "95448   2017-07-14 18:27:54  CURED WITH: WATER, HONEY, MODIFIED CORN STARCH...  \n",
       "22543   2017-06-24 20:05:36  MILK, CREAM, SUGAR, CORN SYRUP, SKIM MILK, COC...  \n",
       "216594  2018-02-16 19:44:57  CREAM, SKIM MILK, LIQUID SUGAR (SUGAR, WATER),...  \n",
       "213622  2018-01-19 21:18:27  ENRICHED BLEACHED FLOUR (WHEAT FLOUR, NIACIN, ...  \n",
       "136263  2017-07-14 17:24:04  DARK CHOCOLATE (SUGAR, CHOCOLATE LIQUOR, COCOA...  \n",
       "67217   2017-07-14 17:25:53  SUGAR, ENRICHED UNBLEACHED WHEAT FLOUR (FLOUR,...  \n",
       "91566   2018-01-20 04:04:18                   MILK, CREAM, DISODIUM PHOSPHATE.  \n",
       "197767  2017-10-13 18:06:16  BABY CARROTS, RANCH DIP (CULTURED BUTTERMILK, ...  \n",
       "170785  2018-01-19 23:26:58  ENRICHED BLEACHED FLOUR (WHEAT FLOUR, NIACIN, ...  \n",
       "212832  2018-01-19 21:21:14  CULTURED GRADE A REDUCED FAT ORGANIC MILK, ORG...  \n",
       "124999  2017-07-14 18:47:26  PORK, WATER, SEASONINGS (SALT, SPICES, DEXTROS...  \n",
       "47887   2017-07-14 20:29:13  CHEESE (PASTEURIZED MILK, CHEESE CULTURES, SAL...  \n",
       "52221   2018-05-19 17:12:18  WATER, SUGAR, REDUCED FAT SWEETENED CONDENSED ...  \n",
       "206982  2018-01-19 22:08:48  WATER, SALT, SODIUM LACTATE, SUGAR, CORN SYRUP...  \n",
       "201184  2017-10-13 18:20:52  POTATOES, GRILLED SEASONED CHICKEN WHITE MEAT ...  \n",
       "...                     ...                                                ...  \n",
       "170618  2018-01-30 03:20:08  GRASS-FED AND GRASS-FINISHED BEEF, HONEY, SEA ...  \n",
       "213443  2018-01-19 21:19:43  FETA CHEESE (PASTEURIZED MILK, CHEESE CULTURES...  \n",
       "200358  2017-10-13 18:06:58  RAW ORGANIC WHOLE MILK, SEA SALT, ENZYMES, PRO...  \n",
       "221282  2018-03-02 22:56:38              ATLANTIC SALMON, COLOR ADDED IN FEED.  \n",
       "33424   2017-07-14 20:11:25  DEHYDRATED POTATO WITH PRESERVATIVE (SODIUM BI...  \n",
       "71668   2017-07-14 17:34:50  WHITE CHOCOLATE (SUGAR, COCOA BUTTER, WHOLE MI...  \n",
       "94258   2018-04-16 20:15:24  SKIM MILK, SUGAR, COOKIE DOUGH (WHEAT FLOUR, D...  \n",
       "178312  2017-07-14 18:54:59  ROMAINE LETTUCE, VINAIGRETTE DRESSING (SOYBEAN...  \n",
       "12888   2017-06-25 03:28:57  CULTURED PASTEURIZED MILK, CREAM AND NONFAT MI...  \n",
       "204112  2018-01-10 16:08:41  PORK, WATER, BEEF, PASTEURIZED PROCESS CHEDDAR...  \n",
       "67738   2017-07-14 17:26:58  SUGAR, ENRICHED BLEACHED WHEAT FLOUR (FLOUR, N...  \n",
       "68955   2017-07-14 17:29:18  DARK KARO SYRUP (DARK CORN SYRUP, REFINERS SYR...  \n",
       "134460  2018-03-10 21:59:08  NONFAT MILK, CREAM, SUGAR, CORN SYRUP, SUGARED...  \n",
       "203085  2017-11-01 22:10:59  CRUST (WHEAT FLOUR, WATER, SOYBEAN OIL, SUGAR,...  \n",
       "165735  2017-07-14 19:58:54  MILK CHOCOLATE (SUGAR WHOLE MILK, COCOA BUTTER...  \n",
       "106566  2017-07-14 17:57:32  ROAST BEEF (BEEF WATER, CONTAINS LESS THAN 2% ...  \n",
       "48869   2018-03-11 05:26:42  LIGHT TUNA, CAYENNE PEPPER SAUCE (AGED CAYENNE...  \n",
       "228610  2017-10-13 18:10:39  GRASS FED VENISON, LACTIC ACID*, SEA SALT, CEL...  \n",
       "171940  2017-07-14 20:27:10  SUGAR, COCOA BUTTER, WHOLE MILK POWDER, COCOA ...  \n",
       "173522  2018-01-19 23:19:08  PASTEURIZED MILK, CHEESE CULTURE, SALT, ENZYME...  \n",
       "48598   2018-03-10 20:42:33  MILK, BUTTERMILK, CREAM, WHEY, CORN SYRUP, HIG...  \n",
       "152958  2017-07-14 18:27:20  TUNA FISH & FILTERED WOOD SMOKE (ADDED PRESERV...  \n",
       "104744  2017-07-14 18:48:35  WATER, WHIPPING CREAM, BUTTER, MODIFIED CORN S...  \n",
       "109572  2017-07-14 18:04:34  PORK, BARBECUE SAUCE (TOMATO PUREE [WATER, TOM...  \n",
       "133178  2018-03-11 04:26:18  NONFAT MILK AND MILKFAT, SUGAR, SWEETCREAM BUT...  \n",
       "214900  2018-04-09 19:18:03  NY CHEDDAR CHEESE (CULTURED MILK, SALT, ENZYME...  \n",
       "112073  2018-05-18 15:06:28  GRADE A UHT FAT FREE MILK, VITAMIN A PALMITATE...  \n",
       "119429  2017-07-14 18:36:14  SUGAR, COCOA BUTTER, WHOLE MILK POWDER, UNSWEE...  \n",
       "18689   2018-04-10 23:43:13  YOGURT (CULTURED GRADE A NON FAT MILK, CREAM, ...  \n",
       "104844  2018-01-20 03:41:45  CULTURED PASTEURIZED GRADE A LOWFAT MILK, SUGA...  \n",
       "\n",
       "[200 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "seed = 10\n",
    "np.random.seed(seed)\n",
    "\n",
    "# Make a random choice which has not already been made\n",
    "def make_random_choice(size, choices_already_made):\n",
    "    \n",
    "    # If we've already made all possible choices, we would get stuck in an infinite while loop so we must abort\n",
    "    if len(choices_already_made) == size:\n",
    "        print(\"No more choices left!\")\n",
    "        exit()\n",
    "    \n",
    "    # Keep picking until we hit something fresh\n",
    "    attempts = 1\n",
    "    choice = np.random.randint(low = 0, high = size)\n",
    "    while choice in choices_already_made:\n",
    "        choice = np.random.randint(low = 0, high = size)\n",
    "        attempts = attempts + 1\n",
    "    choices_already_made.append(choice)\n",
    "    return choice, choices_already_made, attempts\n",
    "    \n",
    "n = 200\n",
    "nutrients_to_analyze = ['Energy', 'Protein', 'Cholesterol']\n",
    "\n",
    "counter = 0\n",
    "small_products = pandas.DataFrame(columns=products.columns)\n",
    "choices = []\n",
    "n_products = products.shape[0]\n",
    "\n",
    "while counter < n:\n",
    "    # Choose a random product from the database\n",
    "    index, choices, attempts = make_random_choice(n_products, choices)\n",
    "    product = products.iloc[index]\n",
    "    \n",
    "    # Check if all desired nutrients are present in this product\n",
    "    for nutrient in nutrients_to_analyze:\n",
    "        good = True\n",
    "        nutrient_search = nutrients[(nutrients.NDB_No == product.NDB_Number) & (nutrients.Nutrient_name == nutrient)]\n",
    "        if nutrient_search.empty or nutrient_search.Output_value.iloc[0] == 0:\n",
    "            good = False\n",
    "            break\n",
    "        #else:\n",
    "         #   print(nutrient_search.Output_value.iloc[0])\n",
    "            # WE SHOULD JUST BUILD THE SMALL_NUTRIENTS TABLE HERE!!\n",
    "\n",
    "    # If so, add it to our smaller database\n",
    "    if good:\n",
    "        small_products = small_products.append(product)\n",
    "        counter = counter + 1\n",
    "\n",
    "    # Once we get to the specified size, return \n",
    "    if (counter > n):\n",
    "        break\n",
    "\n",
    "small_products"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For later use, we can save this dataframe as a CSV and read from it later. This is useful because it takes a long time to search for 100 products with non-zero nutrition content, as the nutrition database is so large that simple queries can take up to minutes. In the future, we might want to speed up this process by using panda's .apply() method to apply a search function to each row of the database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "small_products.to_csv('small_products,n=' + repr(n) + ', seed=' + repr(seed) + '.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NDB_No</th>\n",
       "      <th>Nutrient_Code</th>\n",
       "      <th>Nutrient_name</th>\n",
       "      <th>Derivation_Code</th>\n",
       "      <th>Output_value</th>\n",
       "      <th>Output_uom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3150504</th>\n",
       "      <td>45373989</td>\n",
       "      <td>203</td>\n",
       "      <td>Protein</td>\n",
       "      <td>LCCS</td>\n",
       "      <td>29.17</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3150505</th>\n",
       "      <td>45373989</td>\n",
       "      <td>204</td>\n",
       "      <td>Total lipid (fat)</td>\n",
       "      <td>LCCS</td>\n",
       "      <td>10.42</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3150506</th>\n",
       "      <td>45373989</td>\n",
       "      <td>205</td>\n",
       "      <td>Carbohydrate, by difference</td>\n",
       "      <td>LCSL</td>\n",
       "      <td>4.17</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3150507</th>\n",
       "      <td>45373989</td>\n",
       "      <td>208</td>\n",
       "      <td>Energy</td>\n",
       "      <td>LCCS</td>\n",
       "      <td>208.00</td>\n",
       "      <td>kcal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3150508</th>\n",
       "      <td>45373989</td>\n",
       "      <td>269</td>\n",
       "      <td>Sugars, total</td>\n",
       "      <td>LCCS</td>\n",
       "      <td>0.00</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           NDB_No Nutrient_Code                Nutrient_name Derivation_Code  \\\n",
       "3150504  45373989           203                      Protein            LCCS   \n",
       "3150505  45373989           204            Total lipid (fat)            LCCS   \n",
       "3150506  45373989           205  Carbohydrate, by difference            LCSL   \n",
       "3150507  45373989           208                       Energy            LCCS   \n",
       "3150508  45373989           269                Sugars, total            LCCS   \n",
       "\n",
       "         Output_value Output_uom  \n",
       "3150504         29.17          g  \n",
       "3150505         10.42          g  \n",
       "3150506          4.17          g  \n",
       "3150507        208.00       kcal  \n",
       "3150508          0.00          g  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "small_nutrients = pandas.DataFrame(columns = nutrients.columns)\n",
    "\n",
    "for index, row in small_products.iterrows():\n",
    "    small_nutrients = small_nutrients.append(nutrients[nutrients.NDB_No == row.NDB_Number])\n",
    "\n",
    "small_nutrients.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing Data\n",
    "Let's visualize the data by creating a word cloud of the names of the products which make it through sanitization:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot\n",
    "\n",
    "# Taken from https://www.geeksforgeeks.org/generating-word-cloud-python/\n",
    "from wordcloud import WordCloud, STOPWORDS\n",
    "words = '' \n",
    "stopwords = set(STOPWORDS) \n",
    "# iterate through the csv file \n",
    "for val in small_products['long_name']: \n",
    "      \n",
    "    # typecaste each val to string \n",
    "    val = str(val) \n",
    "  \n",
    "    # split the value \n",
    "    tokens = val.split() \n",
    "      \n",
    "    # Converts each token into lowercase \n",
    "    for i in range(len(tokens)): \n",
    "        tokens[i] = tokens[i].lower() \n",
    "      \n",
    "    words += \" \".join(tokens)+\" \"\n",
    "  \n",
    "wordcloud = WordCloud(width = 800, height = 800, \n",
    "                background_color ='white', \n",
    "                stopwords = stopwords, \n",
    "                min_font_size = 10).generate(words) \n",
    "  \n",
    "# plot the WordCloud image                        \n",
    "pyplot.figure(figsize = (8, 8), facecolor = None) \n",
    "pyplot.imshow(wordcloud) \n",
    "pyplot.axis(\"off\") \n",
    "pyplot.tight_layout(pad = 0) \n",
    "  \n",
    "pyplot.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Process Data\n",
    "In order to analyze the nutrition content of these foods and compare them against each other, we will need to create a new database which organizes the data into one row for each food, with all of its nutrition information alongside it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "%%timeit\n",
    "\n",
    "processed_data = pandas.DataFrame(columns=nutrients.Nutrient_name.unique())\n",
    "processed_data['Identifier'] = small_products['NDB_Number']\n",
    "processed_data['Name'] = small_products['long_name']\n",
    "for row in processed_data.iterrows():\n",
    "    index, data = row  # data is a Series object containing the row (could hae just done for index, row in..)\n",
    "    for col in data.keys()[:-2]: # omit the last two rows (Identifier and Name)\n",
    "        nutrient_data = small_nutrients[(small_nutrients.NDB_No == data.Identifier) & (small_nutrients.Nutrient_name == col)]\n",
    "        if nutrient_data.empty:\n",
    "            data[col] = float('NaN')\n",
    "        else:\n",
    "            data[col] = nutrient_data.Output_value.iloc[0]\n",
    "    processed_data.iloc[index] = data\n",
    "    break #Don't run the full loop, takes too long!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Speeding up our processing\n",
    "\n",
    "This is very slow! Let's try to speed it up. Pandas comes with a built-in apply() method which works much faster than iteration using iterrows(), which is incidentally already about twice as fast as manual iteration using iloc[i++]\n",
    "\n",
    "### Further Reading\n",
    "\n",
    "This resource https://towardsdatascience.com/how-to-make-your-pandas-loop-71-803-times-faster-805030df4f06 explains how this speedup takes place and suggests even faster methods such as Numpy vectorization. However, it's not clear how to extend the Numpy vectorization method to work on two tables instead of just one. So for now, we'll stick with this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Energy\n",
      "Protein\n",
      "Cholesterol\n"
     ]
    }
   ],
   "source": [
    "desired_columns = nutrients_to_analyze\n",
    "\n",
    "processed_data = pandas.DataFrame(columns=desired_columns)\n",
    "processed_data['Identifier'] = small_products['NDB_Number']\n",
    "processed_data['Name'] = small_products['long_name']\n",
    "\n",
    "def process(identifier,col_name):\n",
    "    nutrient_data = small_nutrients[(small_nutrients.NDB_No == identifier) & (small_nutrients.Nutrient_name == col_name)]\n",
    "    if nutrient_data.empty:\n",
    "        return float('NaN')\n",
    "    return nutrient_data.Output_value.iloc[0]\n",
    "            \n",
    "for col_name in desired_columns:\n",
    "    processed_data[col_name] = processed_data.apply(lambda row:process(row.Identifier,col_name), axis=1)\n",
    "    print(col_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Energy</th>\n",
       "      <th>Protein</th>\n",
       "      <th>Cholesterol</th>\n",
       "      <th>Identifier</th>\n",
       "      <th>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>236669</th>\n",
       "      <td>208.0</td>\n",
       "      <td>29.17</td>\n",
       "      <td>42.0</td>\n",
       "      <td>45373989</td>\n",
       "      <td>LIGHT LOW-MOISTURE PART-SKIM MOZZARELLA STRING...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9372</th>\n",
       "      <td>393.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>107.0</td>\n",
       "      <td>45020203</td>\n",
       "      <td>BASHAS', BULK LONGHORN COLBY CHEESE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108445</th>\n",
       "      <td>82.0</td>\n",
       "      <td>3.53</td>\n",
       "      <td>12.0</td>\n",
       "      <td>45197742</td>\n",
       "      <td>WHOLE MILK YOGURT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198710</th>\n",
       "      <td>371.0</td>\n",
       "      <td>12.86</td>\n",
       "      <td>7.0</td>\n",
       "      <td>45327438</td>\n",
       "      <td>MACARONI &amp; CHEESE DINNER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163361</th>\n",
       "      <td>115.0</td>\n",
       "      <td>8.33</td>\n",
       "      <td>16.0</td>\n",
       "      <td>45268400</td>\n",
       "      <td>PREMIUM TEXAS BEEF CHILI</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Energy  Protein  Cholesterol Identifier  \\\n",
       "236669   208.0    29.17         42.0   45373989   \n",
       "9372     393.0    25.00        107.0   45020203   \n",
       "108445    82.0     3.53         12.0   45197742   \n",
       "198710   371.0    12.86          7.0   45327438   \n",
       "163361   115.0     8.33         16.0   45268400   \n",
       "\n",
       "                                                     Name  \n",
       "236669  LIGHT LOW-MOISTURE PART-SKIM MOZZARELLA STRING...  \n",
       "9372                  BASHAS', BULK LONGHORN COLBY CHEESE  \n",
       "108445                                  WHOLE MILK YOGURT  \n",
       "198710                           MACARONI & CHEESE DINNER  \n",
       "163361                           PREMIUM TEXAS BEEF CHILI  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "processed_data = processed_data.dropna()\n",
    "processed_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot this data to find trends:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20c09d1fa20>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "processed_data.plot(kind='scatter', x='Cholesterol', y='Energy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20c097cca58>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "processed_data.plot(kind='scatter', x='Protein', y='Energy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standardizing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Energy</th>\n",
       "      <th>Protein</th>\n",
       "      <th>Cholesterol</th>\n",
       "      <th>Identifier</th>\n",
       "      <th>Name</th>\n",
       "      <th>Standardized Energy</th>\n",
       "      <th>Standardized Protein</th>\n",
       "      <th>Standardized Cholesterol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>236669</th>\n",
       "      <td>208.0</td>\n",
       "      <td>29.17</td>\n",
       "      <td>42.0</td>\n",
       "      <td>45373989</td>\n",
       "      <td>LIGHT LOW-MOISTURE PART-SKIM MOZZARELLA STRING...</td>\n",
       "      <td>-0.437636</td>\n",
       "      <td>1.639114</td>\n",
       "      <td>0.000281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9372</th>\n",
       "      <td>393.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>107.0</td>\n",
       "      <td>45020203</td>\n",
       "      <td>BASHAS', BULK LONGHORN COLBY CHEESE</td>\n",
       "      <td>0.861716</td>\n",
       "      <td>1.250792</td>\n",
       "      <td>1.824023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108445</th>\n",
       "      <td>82.0</td>\n",
       "      <td>3.53</td>\n",
       "      <td>12.0</td>\n",
       "      <td>45197742</td>\n",
       "      <td>WHOLE MILK YOGURT</td>\n",
       "      <td>-1.322600</td>\n",
       "      <td>-0.748553</td>\n",
       "      <td>-0.841447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198710</th>\n",
       "      <td>371.0</td>\n",
       "      <td>12.86</td>\n",
       "      <td>7.0</td>\n",
       "      <td>45327438</td>\n",
       "      <td>MACARONI &amp; CHEESE DINNER</td>\n",
       "      <td>0.707199</td>\n",
       "      <td>0.120282</td>\n",
       "      <td>-0.981734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163361</th>\n",
       "      <td>115.0</td>\n",
       "      <td>8.33</td>\n",
       "      <td>16.0</td>\n",
       "      <td>45268400</td>\n",
       "      <td>PREMIUM TEXAS BEEF CHILI</td>\n",
       "      <td>-1.090824</td>\n",
       "      <td>-0.301564</td>\n",
       "      <td>-0.729216</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Energy  Protein  Cholesterol Identifier  \\\n",
       "236669   208.0    29.17         42.0   45373989   \n",
       "9372     393.0    25.00        107.0   45020203   \n",
       "108445    82.0     3.53         12.0   45197742   \n",
       "198710   371.0    12.86          7.0   45327438   \n",
       "163361   115.0     8.33         16.0   45268400   \n",
       "\n",
       "                                                     Name  \\\n",
       "236669  LIGHT LOW-MOISTURE PART-SKIM MOZZARELLA STRING...   \n",
       "9372                  BASHAS', BULK LONGHORN COLBY CHEESE   \n",
       "108445                                  WHOLE MILK YOGURT   \n",
       "198710                           MACARONI & CHEESE DINNER   \n",
       "163361                           PREMIUM TEXAS BEEF CHILI   \n",
       "\n",
       "        Standardized Energy  Standardized Protein  Standardized Cholesterol  \n",
       "236669            -0.437636              1.639114                  0.000281  \n",
       "9372               0.861716              1.250792                  1.824023  \n",
       "108445            -1.322600             -0.748553                 -0.841447  \n",
       "198710             0.707199              0.120282                 -0.981734  \n",
       "163361            -1.090824             -0.301564                 -0.729216  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stds =  processed_data.std()\n",
    "means = processed_data.mean()\n",
    "standardized_columns = []\n",
    "for col_name in desired_columns:\n",
    "    std = stds[col_name]\n",
    "    mean = means[col_name]\n",
    "    processed_data[\"Standardized \" + col_name] = (processed_data[col_name] - mean)/std\n",
    "    standardized_columns.append(\"Standardized \" + col_name)\n",
    "processed_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering data with k-means\n",
    "In order to answer our questions from earlier, we use k-means to cluster the data into groups. This algorithm works by choosing k random points and organizing data based on their distance to those points, then resetting the k means to be the centroids of the groups and iterating this process until convergence. \n",
    "\n",
    "To implement k-means on our data, we will make use of sklearn's built in unsupervised learning methods.\n",
    "\n",
    "### Futher Reading\n",
    "For more information about this topic, see https://www.techopedia.com/definition/32057/k-means-clustering. Documentation of sklearn's other Kmeans methods can be found here: https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model converged: True\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
    "from sklearn.mixture import GaussianMixture\n",
    "\n",
    "# k - means\n",
    "k = 5\n",
    "model = GaussianMixture(n_components=k,\n",
    "                        covariance_type=\"full\",\n",
    "                        random_state=1,\n",
    "                        n_init=1,\n",
    "                        max_iter=200,\n",
    "                        init_params=\"kmeans\")\n",
    "X_train = processed_data[standardized_columns].values\n",
    "model.fit(X_train)\n",
    "print(\"Model converged: \" + str(model.converged_))\n",
    "processed_data[\"cluster\"] = model.predict(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x20c18b7ca58>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 257.625x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn\n",
    "from  matplotlib import pyplot\n",
    "seaborn.set(style='ticks')\n",
    "fg = seaborn.FacetGrid(data=processed_data, hue='cluster') #hue_order=_genders, aspect=1.61)\n",
    "fg.map(pyplot.scatter, 'Protein', 'Energy').add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x20c192a65c0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 257.625x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fg = seaborn.FacetGrid(data=processed_data, hue='cluster') #hue_order=_genders, aspect=1.61)\n",
    "fg.map(pyplot.scatter, 'Cholesterol', 'Protein').add_legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that our data is clustered, we can look at the data in each cluster to determine what patterns our unsupervised learning method has found in the data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MuzOZsLyXlTvW1TfuSQVOjtCKJZ8VYublcRO+PnGwt5ugJmYAILbuA1+fOJTz/gAAiI6tDKmUnquAnOtvPqjdq+njAQCYd/wiYZ1X8eSJhktz93202r2yvCcd9vmBsU1QIA8N/iVTeoSWW5xHKmZV7CoaXcwAjgpabJxs5OPivBFmZtSSbAgElvB0vwIAiI5lJjHHuD3q04+1g7prrDNx37+0+qw9jzgjOJcgW+fSlNhYTmpBOtPmGBVtC+/GpFypEdrwO8QbWY2d62BJrRBDmKQVzglacXHJ0RuxdR+d6pqblwRWLJYk6W2DlbnZf22oD5e8He0V19XmrEZuQUnS3cn7if2wiNg3dhAAqPiwjWrRAMUSCarPXq34x0VauTUhvB+Z/Ulr3Zuf7zFtjs6UdoSlQ2Nn46crJEM5L6smPzo6/nlMwzlBS04lPyemUzspY/Wue392id9N6Ov3as/r+pb8stVftAHV5qxGtTmrcS6ixNv+8TzN0Srq+Hrh+eIpMBOV/C8K6RwMCzPVTYKedYl3DU2ZSrbl9a5L5g9myHhgdwiiZOiLv9i01kmJMEbUDH0xyU0BTRQUPGKoHf3Xa0RCIW78OJY0zv++MYMwcd+/uPD8LeHzOz+Pg6WZfn/6x/Pp7xIaGz+xt951P2YTu2wE2Pjr3SYZAggIAw68y/6EZq4NGenD3kQDS8rRdsKB7WNhusK5EZqVVTtm2rFsS6u+tqQl6wb3wItFU1DD20Nxb3L75nixaArsrXVLxlvWsKGx4J5TTLyhY2fO/CI+WZtlbR2PjJF3NQcWkLPsxUaWLaEO50ZoLk6bEJ0rm15ExXjp5PGvfALBxXkz47YRcXic7mcUyzpkokQFS5ElYfDFHJqH3InIKSLOhWpnxr7bjylANXDAg9RniEh/jRoOVVi2SDucG6EJBKq7QjKR0uzLUFDwUO04lUBg2gfEqS76t19JHm3CVEmjMcJxNifeIU0rzNC7TTKKpEWE95k4jcBFfgwkn37Oj1jN6GaJvnBuhAbIHG+VBSoqRrc1GSbOcZoKsWnMf5HZhspuJhm1HAMRF5+odv9lxjs6JulEdXvdj7xxGXOhOf4OWgegJNM8EYNu/WD09TTOjdDk6CtKZUnMuMqD1HDC+5ZCC611g1zqEd5nY4RGRhW7Cgbry9g0d22oEDM5ms5pGjvyLmcFDZCJk6vLX5TKujhvYk3MbkdGodb8tQr3jGpzVmPtxTBW+ioLPE17QXi/JYUAhbUctCdp5mGOyVW+UbsnFAjxS60ZpHU0heBmG05OOZWxtuqgIlTFks+QSFIgFDhCJHJnvX9dItcql9UWPogKU/afot2GKdHHp5OxTeChSGW7Cgh2a4xQgsCQUkgx69lyLNEgemzBeUErjUjoCpHQlfV+uq3bhcikFJ3qvFg0RSFqMWkZ8FE6VQAANeasVjurqW1jQH5qwRDsfH8II1nIWSnH3Yre/7d7KU/QiCHPezJXBBcLJ0baLwtMqDwKwW5BWPx8ndqz15nvMfT2ROwNUn/GJmVO0AxBSnauipj92q8zetaReexTHbEN3LwPN35SPa0QoTRqkwvZ+qE9Ces7ia1R319/B1V9OBV3mbagHY0+Q9uOBTWnYl64emKV5S83M7Yo/SD1GeH93+rOYaT9sgJZfDtAFjNt5astmF51jMHs4QVND5ovK/Fh03fqmJydo/H5gEa1cPDeM7SrFqBX+6bKvk8nCO/rcqaR7V3GdA0bDGRx0pgiuNcKVA3wwJ+rhrPaD5No2vm8k8zMyR6qcHpTQJmCwnCkZ6xAatoMpKYZZu7euSZ7joTTOwez1jYdpjxeqHfdpHzyKbquB5zJRI2JXbZv7/1IeN+YWZVMHU0jY0PufHJe0KJifBEV44WExA7IyFyFrOzdyMreTVhWLnYFBdpzOVJh9cBuOtcRCallR7G1tDC53JwAEJ0TR5johArjH8xizI4FNcmP5RwgyS5FhWkk0XAB4+e9NHXW1JtH+owsmxbTcFbQiotj/nOuJfbmJkIudglJ9ENJ64uAaronE0ZTMlkyNP1K7wnSL8YbmcAcjjqFc/HXdG5vyfP1+ESSr4DIfYEtBBR/9EwNH2tPdPMiPiNdLC3Gwgj2Y/lxVNCkiI3XPdqBjdj45yqV45txmf5h4/BvLHFUXqKymqDiUEtEsFtjCED85d8auV+nUUH/sHF4nPac9HlzhqJrUMHe1hrjftyL4F4rENxrBfYfU48BN+C7LYrnwb1WYMe+m2plgnutAAC06r1CpSybjKzQH47m9oTPnqW/xOM04oTTTMFJQVM+6mRuHghfnzjFP004O/2muC4q+kjbjoP3iXfCqEB3oCYxcCzunj4d1O799eEI+oeNw4KINYjJjVd5Fp7+CoNvTdAqZgtrTqNl18Fm5JEeiqXF6B82DgPCxuNGqcCQUkhxPj4U/cPGabXR0Md57j56j+aNAhB6PAShx0OwcedVRLyKVSkjEEDxfO607tixPwzFBD+Wv2+/gmWz+yL0eAiuHJ2G9b8MZt3+Pxv9SvpsyfMNpGdkmYBzu5zFxQmKa0/3izA3r6FXO6lpIXBzPahXXYFAFtt/3vGL6N+gFmVxUnbpeL5Q8/rY138exMOPMWrraKX90izNzPBovuZgkUxgKxKT7maFp7/C5Ee6x5Pf2mg5HBiIB6Zplw2Qidfa19ux9vV2vdo2Bl/3C1JcN28UgHEz9iL0eEmY6wNbSlwh2gdXw8LfTuKP3aEYP7K1SjvRcWn4YXQbAIBIJESdGuXYNfw/DjXbhJF3pxJG7Bh8awJW1JmF8jbM28K5EVpqWskOlL5iBgCFhS/1rqssRtXnrkZmnno4G2VyCgpVxEw5Ci0ZDz+qr+V0Wb0DADCwcW08XzwFfi6OyC9i79dOmWfprwAw9wXf3nglI2Im51CzTbBgMD6/SCA0mpiV93VRed2prfrnfMe+m2rTSKJB+4Behpsql2ZnY3VfQTkhT5aw0ifnRmh5+TcYaUcipXeYedXAbph6QHb0qPES9WnP5mt3sPnaHcK6z+ZPotRH6VMAH5PTAADzesqCXJ6dMspgeQVeZJRE3z3UbBOG3ZmMPIK4ZFRgSyj2Bq1DUn4yxj+YTaudDfUXwkMpnr6hyc4pUH2drfq644A1yMsvVBmxka2NUd1VZwtNo2c2ot1yboQmFDDj2GhhXptW/S41q+gVvFEXR9x6fiVrhfJw3puHGycnZOl1j91N1uBQs02ki/JEbG30K+ujHjdLFxxqtkkvj/4N9RfiULNNRhUzAEhKzlR5vXqL6uZLXn4hvvu6pSFNooWmfKlM+6hxboRmLe6FrCz6QQ3t7ej7eNXw9lA5n6mJDUN66uz1/0Bp2jnpb1n6u+AqphW6Rr4on5SfjKPRZ/EoNQIpBWlwtXRCgG159PLpQCspir74ib0V4plckIrTsVfwOO05EvKSYCmygLulK5q7NkAHz2C9d1l1QVch37jzqmI9rKCgCFtLnRz4c891DOsvW2frOJBepvKJlUdhIos+dn3KdWY0q70mOCdoTg6LFYKWm3ce1lYdKdeNiinJsGNl1YYxm5RHXe8/p+JVfBJEQiHq+HrC3U6/cM1mIiEKiooBlGSWqupp3JGDMkHnZgIAbndaCkA2MhobMNSYJpHiYuGEYeW/wjB8ZWxTKHHuwCSELDiimEb+75s2qBJQkpsi9HiIytrZjrUjsXQd/TOyZQGBVMq9XNzK0Wp9faKgrMvyZ6VdOFLTQpCVvUepnukHeiy9PkZ0cqD67NWMnyggmwYojzJKCxoPjynAuTU0ACjnXRJuOSrGF6lpMzWUliAqxotzYgbIBMzSzAwV3ZwJRavtiq1GsIqHx3Th3JQTAAQCsUpegazsncjK3qlSpnRSFDlcETM5mnzMLod8a0BLeHhMH06O0OT4+sTBwrwWpbKWFo05J2Y8PDy6wckRmjIe7ucBANk5B5GWPhcSSUmKNIHAHA72c2Bn+x2jfVabsxq1fDxwYOwQ2keYyhrxuWnoHSo7+lJ6fS3o3Excab8A1iILxRqcnFqO/viziWoIoSJpMVqcV/cpu9xuPsRm6mkIn6V9wnd3NO8mlrbp+7t/4HHqB5V7YjNLXG43X63uuHtb8CjlPW53WooT0ffwS8RRjW3zGB7OC5ocG/EA2IgHGKy/ZzEJqD53NSO5ATQxavth3ImM0ljGVMIMRecko9/1lQDIv9zn455gacRROJiLsaPp/+BmaYdhYevVxEwilSrE7GK7ebA1s8Ld5DeYeH872l6arxBGZeRipty3XDivtl8IK5HqSYKOlxchozAHkwO7Y5B/cwBAn9DliMtNRdC5maTv4Xl6FH6JOIq+fkH4oXJnPEiJRMgjasl6yFg/5yhO77+NM2+W61W/S+UZetdlwx5jwekpp7Ep58Ruwtnqs1drFTNT4X1WolYxA4ClEUexodG3ONd2DrytnWAuNMP+FuqC3Oz8z4q2bM2sAACNXSor2m5zUTX21vBb6wn7lr8uLWZF0mJkFOagip2XQswA4FjwDFgIZb/zGYXEUYVH396I252WIqRaL4jNLNHSvZrRR2cWVswd++IyZWaEZgxW9O/CWttyl42vGtTA4j7Ufe2MweuMWAy/tR4CCHCr0y9ayzd0phdW3M7cGpmFuZBCqjip8DojVmOdzMJc2JmXnDJpe3E+AOCvZhPVyh5uOR09ry3D12HrcKLVT2rPO3sT5wY1JsefsXM2kmt8kYImleZBILCi3U5dX+KdVCYxdTEDZKMjC6EZQjssYqS9lxmyExJtPGoSPv+pem/MerIPf7y5gO8ry/4+Ld2r4XriC2QW5cHOrOT/rXyUpSxmAFAgkR3lKr2Wp0xiXjrh/ZBq5Ed59MXU1mI12bNu00UMG9QUTk42GtvYvvsG/vq7JD9tcPMqWDib3aN7nBS0uIQW8PLQ75B6Tu4JJKeMZWTHMzUnF05i9pJmNKnoy1rbTCEXBLlAaMPWTPsPiXy0VdmO+Aejir3sjGtEesl0fEW94Qg6NxMdLi3A4jqD0d6zNq4mROCnx3tgLhRRso0qNgQbErrSpbJq3otxc9W/6PJ1MeWyXn4u2H6pJOLM0GaLkZIkC7RAtt5Vui+islTskXP0xEMcPfEQAHD1DHH+jnbdV6rFZwu9+RqtuywnrcMEnBS0oqJ3iIrx0lmUyHzT9KXHur/UUtExCRfWz7YFjUclW0+0ujhX40K6LtRw9ANQMlIrzYt02f0aDqqCf7vTUgSdm4mlEUcx9+l+1HDwI9wMKF3H0HzdQjY9VBYVItGR39e0ML83bLbG+iFDNmPE1M4YNK4kNHavmj+rtNul8gy06VEPM1aVBH8ka0+Zcd+2Jrzff9gmFTGrWtkTr96UBABlU9Q4vSlAVaCk0jxGxUwuYtpS0dEhfNFkAMDe249Z64MJajj4wlJkjjUNZIebNU3hqBJgKzu3GJpIHBL71+fHAABjKqlG0Q06NxNCgRCX2s1HWMdf8GeT70nFTCSQffRziwsIn7NJckI66jVTzVpVIZD48/ntT91p9RV+L1JFzABgzCz1XK/KYqbJnktXXyiuB/YlzoKV9LkkWsjVMzPwx7rhuHpmBuxs6S/zaIOTIzSRyAvFxbLRGZWRWnSscoQKAXx9NC8ga8PFRozhTevhr1uPUG0OO64bQoEAm4f3xvd//YMlJ6+gsocLfJ0dCctuIElGbEiCXKughVsgbiS9RPerv+Bk659Z6yu7SBaHTUiw0GNBcXp5tf1CtLwwG20uzjPKKK1mI9WoKYF1/fD+pfrnOLCOH+2+qIy21PolsefYvw811vtxzmHFdekR3L+HJqJ1F9mo8OatN2jelPn8qpwUNG/Ph4iNr68QtfSMZXCwV9+NKi5ORGx8SQJbC4s68HA7y4gNM7u2RrfagRj4xz5Um7Ma20Z+hWYB/oy0DagfTH+TkIw3CcmMtc8GK+uPQJuL8/A5PxPrX53GhKpd9W5LPn0MOjcT59vOgb25GA9SIvHDvT8BAKfbqKfEk+9+Eo0Sb3RcDDNBidiZC0XwFbsiKuczWpyfjb3NJ8HPxhXP06Ox4dUZPEp9z6rQvXj8SeV11Lsk1vrSx5eMzJ6oaPLcqgBw536k4poOmqt+AAAgAElEQVRsBAcAB47e4wVNGWVRy8hcC5HQDba2JanGMjLXID2jJFmDi9PvEIuZCR8zcd+/uPTinUqikm92HtVQgxhNIztjOsvSCcJ4pf0CBJ2bib0frqO3b2P4il31bksuah0vq+6enmr9M5wtVMMy3fr8CpmFsvj1IoEQwv+mlIX/bVa0OD9bTaAOtZyGre8uYevbixh4gzxcNNM4utji/jXVEPDh9yJJStOjeoPymD54I1buG6+x3OqZhzBlaX+t9uTlFZK2kZdf8szdTXN49ddvEjQ+1xdOhg9SJja+AYqLZVNIF+fNEFv3Uhm9AUA57zcQCPSLS0YElYCOVGD7lIGcfjdDkKsULntuje/QxIXaGVguUCApQvCFORheoTXGV+lE+ryPbxP8WN0wEX+7har7twHAqeB1AEqmgV9P7IA96y6g77etcGTrNbWNgpX7xqNGw/Kk/UilUrx49AnTBv6O3w78AP/KHrCxU12rkvfVuHU1ZKbn4MWjj6haxw9rDsvS/F0+/hArpu+Hp68zWnevi/2bLhPaAwA/TN2DiBey71vphX35dJLoWekyIpEQl05OJ31f+sLpTQEA8PZ8oLhOTvkeUTFeKmLm7nqYUTHjGhveHFARMwBYGPEn3mcT7yBykckPZMljiMQMgMLzP7Ugy2A2aePMm+UIalcdR7aF4t8XS/Htj910bmPfxkvoWuVHTBv4OwBg2sDf0a/+XLU1szNvlmPE1M54/ugDEmNSMWVpf4WYAUDbXvVx9IksY/zNc+Ea7RnwVSOd7STC1YWd7yTnR2hyiHYxSwd/LIvMP34J83u1I31ONlIASkYLXOe3F//i0KcwHGo5jXCK2+7SfGQX5eNSu/mM+JBRQdsIjcvIR1ke7vY4sOt7lXsA8Me64aha2VNj3Q5ta2BWiO4iro0y82339YlDYlJP5BfIEspaWjRGGXp7pBy891SjoH0JTKvWA0ejbqP/9d9Iy+xqOsFgYlbWqV2zHJ6GRyMhMUNFyABAbG1BKmbpGSU5Oif/oJ64mgk4P+VUxt3tBBwd5gIA8gvuGtkaHkNys+MS3O60FD3LNYSDuRjmQhFqOPhiad2huN1pKarae2tvhIcS61aQZzs7fXQy6bOBIzYrrm3E7CSmMckhDF0nWIHAElJpvsZ2TC3YY1Z+AWwt2c8+JMfVktinjev8XKMvfq7R19hmlHmunpmBqJgUfD9pNyCVYvWyQahCMjKTo2mHlClMUtDoIpXqlwDXWLRZ/icSMrLg7WiPi9NlridMJRA+1uI39LkxTe3+riYLGWmf58vF18cZpw5TS5oNkO98MkmZmnJylaV9ZbtzS75iPrKGhdAc+5stg7/YC9YiS0yoPKhMLEzz8BBhkiM0U5sOsk1QgB+pI602B1sqIzk7MzE2NqR/xpKHx9ThR2g8PDxlBpMcofEAP7QNgrON2Nhm8PBwijLjWMvDY0qUZcdaU4afcvLw8OhE6y7L1RxqqTJm4l8YM5FehixNlJkpZ1b2X0hLnwOptCRgn0Bg8V9eTj7DOA+PKfD6v8i1iUmZWiNy6APnBS0xqRfpqQCptABp6XOQlj4HZmbl4eVxyyA2fciOxT8xV/Ek7TVS8tNhZ26DQLvyaOPREM1d6xrEBq6RWpCBw1GXcD/1ORLykmEhNIeLhQOauNTCyAo9jGbX84xIbH13DLG5SSiQFMHfxgtt3Ruhh0+w0Wwi4mNOHC7E30ZE+jvE5SUjqzAHtmbWcLNyQiPnGmjr3gjlxB7GNlPB3wdvs3L8idNraPqcKKDqEkK0BqJp/WPfp7PY8+G0Trb0KdcG31bso1MdZeaH/4F7KRF61V1f/0dUtPXRu28yriTew8qXu1Xuras/AwG25dTKFkmL0eu6biGU/mg4i/Uv5rbIf3A0+jKlsjZm1jjY7Fe1+4ZYQxt2ew5SCogzU2nD3coZGxvMhLVI9/Ot8ummPo6yRAfbmYSzI7TSYiYSusLBYQ6srTpAKHRCsSQJeXkXkZa+CBJJqko9pv3cNEW00MSx6CvILc7HhMqDGLXH1Nge+Q+W1P6fyj19/2Zj78sSjLCxuB6e/g4/PlmrU53solx0C52IVfWmoaodcxGLNaHv306ZxLwU9LsZAgBo69EI06oOo92mLiQlZWovpAec3BRQzhEgFDrA1ycO3l7PYCMeAKHQCQAgErrBRjwYPl7P4esTB6HQXlEnKoaZkUlWUQ7tD1dZFzMAeJz2WnFdLJUw8oXsFjoRH7Lp5YZQZuSdeTqLmTJTH/2GsfcWM2YPEXs/nmHkb1eaywn3kJCnObQ207ixsH4GcFTQpNI8ALJFfx+vl1pKy/DxeqWUXFiisSwZEmlJvZSCDAwMU89jwKOZntfJozHoyg8PlqkFr9SHfjdDkJSfqr2gFqJzE/H17dm02yFifvhm/P3xDCttA4CHlTNrbctRzjfQqxs7a8mcm3Kmpc9VXJfz/qhT3XLe7xVT1bT0uXB00O2A9r+xoejl0xrHY65iyzvyHAI2ZtZo4FQNrpaOSC/MwqUE4k2LYLf6OvVfmvk1iXOCvsuKQkR6JJ5nROJOcjgKJOxHOaAC2ehCLLLCj9VGoqFzdcW9Akkhdrw/gRMx1zS22e9mCK3p5+m4G1pFsYlLLUyuMgT25iWZwm8kPcLyl7tQLFX9cUwtyGB8FPXri524l0Kc0k9OJ8+m6OfbHt7Wbir3Y3OTsOntYTxMfUFSE5hbYwzpM03uGfq6bgDAkAFBetfVBOcELTtH92QkROTkHNNZ0G4kPUYvn9aEYvZ301/gYE4cVnhq1a8V1++zY/C/B7JF5B+rjdSpf6oE2PoiwNYXPX1aYdbTDSpTPmNB9CX3F3uRnjG1EJpjbEBfjA3oi8NRF7Hj/QnStmNzk9S+yFT5/c1B0mflbbzxewPiUXgLt3po4VYPANA9dBKkYG9vLTSJPHXc8ZarVbJZlcbb2g2Lao1Tubf85S5cSywJXd/EpSZ9I3Vg5nTmI9XK4dyUk6nQQBKp7vHln2dEqn0xK9r64FTwOlIxK00FG1n5L91jfHfQIsoH5vv5tse+puQp5b67t4j0mSY07bDOCBxBKmalORm8Fm3cmYm1rwungtdpFDMyZgSOUHwGq2jZyLh6ZgYWzdF/J740e7Z+h07tajDWXmk4N0KzsmyB3Dz6uTWtLOn7EU0PHGaUDzLX2dVkIZwtHHSqY29ugyYuNXEnOZwxO4qkxYT3q9j5o5V7A53amh44DOHpbxlZi6PCUP8ujLSzup56rLzStGxWWeGi8TEqGSPGbANgmPhmusK5EZqTY8kvtVSarVNdiSRDce3sRC+AYiv3BryY6YG/2EvvaLma1np0Re7+QQSVLzkRO5ss0NccUuLziJNLD2FI0HTF39fFKP1ShXOCJhKVhPmNjq2kU92YuKqKa6GQ3q7OjMARtOp/qbAVl23fJ91G7dE5xIlu6Tg6A9B5ZKeNfEkB4f28YuL7XzqcEzQAKmczo2K8IJVq3sXLzt6r4ojr4rSBVv+7g9j1Nyqr2JrRD4f0TUXiRME3kx7TbhuQnd6gA9M/dP5i4tMw32sYYX7JcG4NDQAcHRYhM2ur4nV0rB/luiKhG8Riekk0nC3stRfiUWN3kH6L98p0926JbZH/qN1/r4OT7Z6Puh1RM0WS8lORW5yv19ElulhZmRsk4Yk+cFLQANmZzGJJEmLjautQJxaAgFa/9Z0CadX/krEQmptEG/s+Ek9PyUZ/umJvboOMQt3Wd/VBfnTJ0DvmZ4/pdv7WkHByyilHJHSDr08c7O00OzKW83773/lNemIGAGMr9aPdBo9p8lW5toy009+X2SgSk6qQ58EEZD5+RJm9vkQ4LWhyHOxnwtcnjvSfQGCjvRGKlLN2Z6wtnrJJG/eGjLbX0TMIAi0/xgWSQnQLnYhuoRNxKvYGo/1ziTIhaFyg0zXmzjBykQBbX2ObYDCcWFhjPRm8FuZCaitEG98eVIhbWgE7US1MFV7QeAyCrwkFF+Qq/7RYhfk1dYshNvT2LHQLnYj7Ws6CGgo64bupwAsaj0GwM+czWDFBI+fqOBW8DvWdqulUb174ZnQLnUi4Q1yW4OwupzJp6YuRmfU76XMPt1OwsKAX2YKHHkL+t5NR5AfON7w5gDNxNynXOxp9GUejL2Nuje/QxKUWW+YZDU4LmlSapxLskYyEJNnpfm/PRyonDdji39gb2PDmsOL1zGrD1cqEfX6GBRHbVO6da7VGcX096QkWP98BV0tHfM5PU9wfWaEbBvuV7KIRrc2dCV4FoYAXkC+B/1UeiP9VHojtkcdxJPoS5XoLI/4EUPbS6nFW0KJjKygCPaojBFEQx9h4WbgXpkNwKyORSrDhzWEVcVryfJdKmRcZH7AgYptKmbjcz+h0bbLKPQBYWXcCvKxk5+eSC9Ix5NY8FUErXf6be7+gS+hUtfs8ZZvRFXthdMVeAGSH7ntfn0oppFG30IllStQ4+TOembVZRczUXTViVF67ufytUj81nZ2oogCw4uVetXuzqqseh5n8SF1svKxdAQDP0t+p3rcqOQzsQiFCRbMyOI3g0Q0zgQgng9fiVPA6dPNuobU8Uay6dZsuYvos4lhxxcUSvf+xDSdHaGnpJVENqIy2rKzawNcnTnGeMytrG5wc2DmP+TorilI5Mo/3p2lvUcshgHJ/fW/ORFZRLgBAAAGsRBaU6/KwQ6KB4/NrYnylARhfaQD63QzRGJk3rTATjuayOP/Tfj6AB49k0aBbd1muFiaoXfeV7BlME86N0IqL4xXX5bwjNZRUp5z3B6V22Jl2ViJI10YEWVjs2o7UI4js+nAaWUW5ONdqDc61WoOzrVajpRuf91Nf3mfHMNLOaR0W6Q3F4eYr8FcT8rO0Q2/NUly/fZdoCJNYgXOClpoWorgWCKx1qisQlBzkTU37kTGblJkR+LXavU1vVUN2b288S61MbO5nANBpdHYt8ZHavfPxdyjX/1Ih2zDRFI5bFw5HXWSkHaZxsXSgFL7p+IEJiuuvB7ET+58tODflzMtn5lhHXj47v6Ki/74sna5NRjevZiiQFOFW8jOVMj7WbrAUWqDTtcno6NkErzM/4UN2HL6r2FOnvtbUm4z+YbNwPCYUFkILrHm9HyMrdMPO96cYez9lkZDA4fj1xU61+y8y3jPSPpv5BehCFo6oNFSi0dJJNMwWnBuhKefXpIOuoztdONdqDaZVHYxLifeRLynAkebq8fBPtFyOnY1n42naW9iYWeFcqzXo56vb4Wh7cxv80+JXbIv8F8djruFsq9UqO6A8xNDNtsV1DJGyzlhwboQmtu6DzKw/aLdjI+7PgDXkdPRsgo6eTRSvidwovKxdsavJHML6Ld3qENYpfc9aZIkTLVdoLMNDnUkPV2Bt/RDtBUmYH07/s8k2hZIiY5vAGpwboTk6zFdc6xLYEQCiYkoW7B0d5jFlEg8HIYv//zYrSu9YZhKpBPdSIuiYZRBSCjK0F+IonBM0GTKzpdJCRMdWpFRDJn6yLD9CoRNbhvFwBDdL8s/A4Fv65T3owWBWeDn6pugj47dXu2m3cfXMDJPM+ARwVNB8fUq216XSXETFeCE61g8ZmRtQWPgcxcUJKCgMR0bmGkTFlFPLO+DjZRqRB3iMyx8N1Xeb5XQLnUia5q40EqmE8WzpcmJzkxShgKJIErtQZdrj1biccI/w2fbGhpmxsC2GnFtDk6PsKAvIRmvpGUuQnqE5eQSbx554uEU5sQcEEJDuSva6PgUCCHAyeC1pG+PvL8XHHMN8ppQTo9RxrIIJlQcpTpho4pu7C0jT4cnxsDLt9HRU4aygATJxik9si8LCF1rL2ogHw9lplQGsYp+ht2YhrZBe4L4JD3+lXNbDysVgv+CG5mTwWo2jKymkOo++TgWvY23EJudJ2mt8e28hI23xZzlNCE/3y/D1iYOL80aYiVS99M3NKsPN9QB8feLKjJgBoC1mupKg5ded6zCZeu54S1kC63YejRlrk02au5atkyWcHqEpI7buA7E1vSSxPF8mrdwboLyNN8Y/UPcX1AXlkc43FXvjUsJduqaxyu8NfkJ5G29jm8EonB+h8fAwgb+NF04Fr1Oc9NAFZwt7tWmbg7ktI3axMR1s4VoXp4LXMS5mmVl5uHnrDc6cf4awO2+Rk2v47O4CqVRquuc0OEJy3l28Sd2I9PxwCARmcLCoBl/7AfC26WJs03hosPb1PpyPv0X4rJy1O9bWn2GU6CaXEu7iUNQFyrueA/06Ynj57ozbkZqajT5DyCNFl+bk4UmwtWE3MTIvaDQokKTh4kfN8aa6Vghn3Y5r0d2RXfiBMRtOv6/JWFtlkdPva8LBsjqae2s+zK78dyxrf7cxE3bh9Vvd3Ujq1PTF2hWDWbBIBifX0KJivODosAB2tmN0qiePWAsI4O35kLYd2sSMhx2kkOBy9Bik5EfAUxyEll6rNZa/m7gInzLPwsbcB8Fea2Bjrn2q9TBpJSIzjsHG3Btd/A7pZadcxDT9QHCRDX9cUhOz8n4uGDIgCPXr+sPOzgopKdl48PgD9uy/jfiEdEW5J+FR2LIjFGNGBbNiGydHaMr+Z7r4lcXGN0RxcYzO9Yg4+6E+JFLZGkGA47eo6mRaeTeZHB2YwkjjwNtGAAAHiwCkF7xTez6wkrrDaEFxBo69b0fYXuny8vb7VLhEWKe8XVc08ZAdl6I6QpNz+n3NMjVCU46Y0a1zbYRM6qy1zuLlJ3HxSolDO1vOtZzbFCiWJCmunR11i5zp4VYSVkf55IA+yMUMgMmJWVkmveAdBgTcxsBK9xT/gBJBUkYuTMpl2/psIS0vr1PLZbxa+x8yT6uUE4A44nBZ58atN4rrfr0bUhIzAJg9ozv69W5A2A6TcG7KmZlZsghpYzNUp7oiUUmy24zMtXCwn86YXTyGobv/CQgEIq3ljka2BgD0qnBO5b6bdT14ipsiPucWPuc9hatVbZXnAoEI1Z1GqdzzEjdFXM4tpBe8hYOFLKKwlZmb2lRS11GYFBKceV9b7b5yO6ff10Q7vyu49KmNxr7uJ/yAxJxrKveszDzR1lcWbPLSpzbIL05CaXS1edPWq4rr/43VLdzV/8a2w+F/HgAANv55BS2aVtapPhU4J2i5eeeZaSf3OC9oHMTGnFqAwkKJLGKGlUg99lcr73U48LYRLkV/ozb1JFovC3Doh7icW0jOC1cIWnz2RTXhuRM3Gk28tlN+LwII0aXCUwiUJkqn39dEWv4TOFrWUdy79KmNWl/K09hPmQeRmHMN7fyuwlJEfBSqnd8VtXtEfWkjMZGZSB2JSexE/ODclLOoiFoSEq3tFEcz0g5P2cLO3FftnlAgm15KNRxWdxe3RnKe7o60AoKvYHz2BZXXjTw2qrz2EKuO1sI/L4S1mQ+pmGmidF/aqF2LWs4MbdStrVvoL6pwboRmblYRhUWvabcjFFKP2nn+YxCKJFmkz8l2sYiG88plO5d/AKFAs1+OKSzI64M+dl/81BIFxakAgEDnaajoMEpLDeNhb1FN5bWf3QAk5lzVuR3lv5NIYAUAakfl3cSqO4IioY1aOzVd52rsJz77Ah4mTtHalzZ++2UgI2G0Vy4ZQLsNIjg3QrOxYcaHRWzdi3JZTWLGQwzRyEMbcjEDYNJiBgCZBa9UXqfmPdC5jdPva0IosEDXCuHoWiEcncrf19sebWL6MHEKgn3+YaQvOX2HbtReSIkOPX+j3ac2ODdCs7P9XpGXMzo2AOW81bfwyYiLLwmJ7ehAHPqaiDa+59TuXYnqpPH5l06XCk9w+r0s6fGnjAPwsx+osXxeEb1YX7oQm30dAOBvR22HjggpVJPmvkvfppeIV3LUzZeSCAuREz5m7EMNF/L4bgBga0E9RaImrp6ZgdZdliM5JQsde63C+eNTtdZRHtXx8dBIkEpzUFBwHxYWDbWWLS5OQFHxJ6U7Asr9WJv50Hr+ZVLy9w1PXqRV0C5Hlfh+tfenn9mrf8BNHHrXHAfeNlJb+L8eJ/sCBnnoHw3Wy6YTTr+viYoOIxGZvhMA0KXCU5UyUkiQVfAWAJCW/wS25pVgpjRdNBPa4nXqBthZVEFS7k18yjigly3t/a4rNgpsLSpBbOaDxJxrsBS5oJ1fyc7n6fc10cBjnda+uvUjjv8mEgpgY2MJd1d7dO1YC6fPP0NBQZGKWAkEgFhsiexs4qTGl06yuxHHuSknALi57ldcJyT1QG7eWY3lPyePQGx8SZgUR4fZrNnGU0I1F/1yn1oIHWn3LRRYoLxdNwAyn7OL0aNxJLKVwv+soy+9UNT13H9D1wrPkJh7Ay7WTdTWCR8kTMSZ97VxPeYrAEBY7FCc/9hEZc2so/9t1HCZjYcJkyGR5KNrhXD42+u3pNK1QjgaemyERJKL5Nw78LHtoSJmXSuEw13cilJf2dn5hP8yMvMQF5+OJ+FROH3+GWFdqRSkYgbIsq6zmcqOkyM0K8tWEAgsIZXK/nCfk1XXW4QCO0ik5DHD7Gx/YNU+HhkV7IfhRbIskOSFj83QwT+MsFxs1knFtS4uBNpo4jEfdVwn4vj7TkjOK/kCEp0q0IUS8RIg2OcfwjINPKhFyfC3HwR/+0GK16WnjUQbKnXdlqGu2zK1++7iYLiLyY8UNfRQPUiubYrKRTgpaABQzvsDYuKqQSJJU3tGLmZClXwEPOxjJrRBkSQbhRJyv6PHST8prpt57yUso0mEND2zEjlTEjBNZbzETWmLIJfYv3OssU3QG84KGgD4eL2AVJqP6NjyWst6ez6ESETNKZOHOTr631FMs+Kzz8PTpqORLeLRhqeHg7FN0BtOCxoACASWfOITjvAwcaraFEr5TCwTrgS6sPtNEABgWOXbjLZ7KWYSYnPuoIf/XjhaBDDaNo9mOLkpwMMtLEUlGYXyihNVnp3/WOJKI3f25Dq+tq0BAI4W1HLG8jAHL2g8rKO823b5k+qBZsl/UU/crA0fW25Y5duMj84AoIpDn//ape4axMMMvKAZEbJ8kF8K6fkl8bEaeW42oiU8ZQXOr6FRoeIazSnsIidr93RmCjOhreIoVUb+CzhZ1SMtK6EZs82UaOy5BXfjZV7xr1LXoqrTJNyMJT/Pp7y+Jb+W09N/PxwsyquVLU1dl+9Ry3mkyr30go848VHVyVfTKO1m/AJEZp5Ru29r7oM+5Y8Q2qytXXm5bn67cOqTagq9hm6TUM1RP1+08MQEfH3kMDLyyf3AyHC2tsb8Nm3RvUpVvfo2Fb4IQTMlfGx74mPG3wCAR4nT0NbvMmlZ5fUlruNq3Uxx/S7tT1R1mqR43cBjPWm93W+C0Nb7N/jYNAcAhKfsVBEzOc085iDAvtt/r6TY/aYpHidvVhM0Bwt/hdCQCaGcAkkmIjPPqAnomahv0cV3q1p5ebvPUnbicbL2EeepTyPQ1ns1fGyaKuy5n7RWZ0HT9oNNhZTcXEw8fQoTT8uCoG7t1RttK3BvDZCfchqYGi4/K65LL5Ark1nwRmUHsCygfJawWJqruC4dDkeZ6k5DFGIGADVLCRQgE5ISMQMAAQYGyMLivEk/rre9txNkzqulBZRIzJSxIIiGQURzz3kKMQOAIZVCAQBPU7ZRqr/5/j1GxIwILooZwAua0Tn9vqaKsBVL83HuQwNcj9E/aXKhhL3M6oWSdO2FSFD2qr8T9w2lOg1cJ+rVl4XQDgCQVhCpV31AJqZ029BERTvVNIcigSwlXmy29o2KwPVrsfzGdVbs4jL8lNMIdK0QrnKmr/TOn3K5u/Fj8DmX+MgQIPOyVz46RARRvLbW5U5DbK4eZE9bhqILH5sT3qca80y+hpiWLzvIzUS0CQA4F/09EnMfM9KWHFerGujpf0Blza2N90qUs2F3R1bb2ilbozI5c1uTj5hNHX6EZiS6VghHS59jhM+aeG5TCEQ15xBDmsU6Hf1VRx9VnPQbgSmz+00QEnMfo7bzNwpXDKbcMeRrboGO/QEAV2Kna117Y5N6m3SLQaYPI+uSb1SZOvwITU+YiB5rZ1FZazvaypAdVNYXLkXFBYDQONmaJBv+ZMo0cpuGRm7T8C7jJMISFmPv2xYYWol+mCNdSc/P06l8j6qBGNeoEaq4uEIoECC7oACJ2dm4ExONK+8jceEd9XiCXIAXNB6Dojy9lmckosPHLOJd4phs8mk6HQLsuyMsYTEk0iJW2tdE4HriOGWlWdS2PYbWVs8mBQA2FhaoYGGBCk5OGFSzlsozKYBl10PpmmlUeEHjMSjKGyBWZp602ytn0wLR2eojpcux9H0LnyRvQR0X4jU+kcDweTkLismTtMih41MpADCzJfWM5teTnmJ++E69+rrUhp11QF7QeAxGRPJixbW3bTcNJanTxnsldr8JUlvXauv9Gy7HTlMrT7T+pXxPeer6NGU7nqYQp6UbUkl1h1GXdvUht0j7iPDumO9p9aEL7a4YzhldFwRSqbTMn78xpZMCXyrFkhyc+9hY8ZrptbrTUaORkv8KvjYt0cqLuTXFmOww3En8FTlFSbC38EdTj5/hZlVLe0WG6X9wPx7ExmosY6jPMRNixo/QeDjF1ahOcLFuCjOhGO/T/1J51txbv9j5mujqSz3Bry742DTDVxX0d85lCm1iNrGJcXZeu3s3xZSq/Y3SNxEm77bRpfrPej3jMS45RTGIyjysJmZdKjyFg2UNI1lVdpnctJn2QgywOKIkF8PFNr+ZlJgBHBA0Hm5Sy3UB7C0CIRJYwcGyBlqVO4muFcL1SvXGYzrcTXmhuBaYYHgkzk45C/LKTiSKsoivXV/42vU1thk8DGOKIqaMyQqa8nSSbGoptrU0lDk8PDwAmrnWwPl4w4ZK1wWTFbQzz38BAPSsOxcnHi80sjU8PDwAMCNwsEkLmskvaIye2snYJvDw8PyHQFAy5ex/c54RLSHG5AWt93Di6A48PFz6V8YAACAASURBVDzGQe5DllKQiW/uspcFXR9MXtB4eHhMD7mofciOR7srU/Ht3RW4+Tkc6YXZKJAUaf3HFpw4KXBy3238vugEAGDUlE4Y8F0rRL6Mw7r5/2DN/nFa69M5KXAwIhw/XTivk70eNra49R0zcb6Y5n5sDAYc1M+xdUTdephnorGypACa/bkFCdlZOtf1sbfH9dHfMm+UHuQUFuLCu7c4/+4dLrx7iyKJxGB9Uz1pwJ8UoMnvi06gadvquHW5JEtQxUAvvHoaxVqf08+dxdEXz7UXJCAhO0shoqZyrKrb3t14kZREq41djx9h1+NHAEznfRVLpai8djWtNmIyMhT/v3b16YuW/v5MmEbI9ocPcP7dO9yNiWatjy8Zkxe01bOO4O/QmXBytTPIyQApgAAGI4JWXLMKZ74ejqquroy1qQuZ+fmos+l3xtutuGYVxObmCP9hAuNtU6XS2tWQMDzBGHFMlsnp7aQpEAqY97laHHpNeyET50wr01o3U8bk19Au//sYTq52BunrYVwso2Imp8uevzD0yCHG29VGm53bWREzOTmFhayHgybi1efPqLhmFeNipkyltasx+exp1trnMhZCM9r/2MLkBS24Sy0UFWqPA0WXh3Gx6HdgP2vt34qKQvB2zdmCmKTimlX4mJZmsL4MxfiT/6LLnr+0F2SAEy9foubv5Cn2eEwPkxe0kF8HoEedOcjJUk2eyuT0s1giYVXM5ERnZGDUP0dZ78cYoyZD9Nlt726cffuG9X6UySksxDkD98mjP5zY5Vz50yFcOvFI7b78NIE2mPiytfT3R7/qNdHU1xeuYjGyCwrwKD4Om+7dw62oTzq1dWXkaPg7OtK2iQh93uv8Nm3RqVIleNjYAgDiMjNx6vVrrLtzC1kFuuUGZWuzYNzJEzj39q1OdToEBKBv9RpoXb4CLEQipOXl4eanT/j72RPcitJtQ+nB2HFwsrbWqQ4RxvixoYqpbPTQgROCRhd9P0QBzs64MHwkpbL5RUWotmEd5bbZ+PBU27AO+RQim1qameHF/6hnW0rPz6OcbUgA4B3D7y0iMRE9/t5DqeyxQUNQx5N6aO/N9+9Rzm9pzC+8KQcp3fLuJA58Is7tAAAbGkxCNXv2do6V4YygpadkIztLPeONt5+L1rq6CtqgmrXwS/sOOtXRpz8mP4T1N29EWp7mjECNfHxwoP9AjWW0QeW9uYrFjIaDptIn3b9l731/42lCPOv96IspCtqYeyvxLktz4EllHM1tcaQFu+eyTd5t43V4NCYNIB8dUJ12UmVK02aYQDP6Z+TkqZS+hG+Sk1HZRbsgayOvqEirmM1r3QYjGMi3SOW9fc7Jod2PnJYUNlKY+DL/M3gIRh47itCPHzSWG/vvcfzRoxft/rhO12s/Il9CHMJLIBCAaJyUVpiFdlemsuZUC3BA0KYN+YNx0SLDysyMtpjJCf9hgtYdsk67dzHyZayuZapb38uLETGTQ0XUKq5Zxch7i8nI0Pj89cTJtPuQs7PPV1rfV1nLY6kPh6KuqoiZNoG6l/ISPz3Zoni94c0x/K9yH1ZsM/ldziN35+Lgn4ZxRnyuw7qSNsTm5nCwtGKsPTocHjiY8TaH1q7DeJul0XYCoG2FijATMvsRpiLCa26xk/OTK2x+e0JxTWW01cg5UKXcsWhqa5b6YPKCZmFljh2rz6FL9Z8J/zGFr70DY23JeTRuvNYyrbZvo9XHlgeaY1PZW7ITBHNR23Zay9B1TC3Wsry7tVdvWu3ry7o77GZpZ5POtWdrLTO880oM77yS8FlyfsmI+XSwbtm1lE8YJOWz4yNp8lPOr9ssQ8MWVbBoy0hW+7k2+htW2hUKBBo92qMy0mm1ry3T9eNxP9BqXxMigUCj6Jx4+RJrOnfVq+1JZzSLYc/AQL3apcK9Md+j0ZbNrLVv6mRn5BFuwAHAqlcHFdeWIgud2lU+IbDm1WEsqc18QACTH6H1HtacdTFjk/tjtUcD4SpsTGXl/Pvqpcbn+golFVzEYq1ltj98wFr/xqZSdW/SZ49SmXEyfpymm08hVUx+hNauZ13F1NLT1xmWluYqzzefmES7D7G5ufZCeuJoxd46mrawRqPq1WetbwCU/L0+pafDz4H56byxWRx6DaPrNzC2Gazw4U0C6TMbMyvkF9BPUGQl1G10RxWTFzQnVzvWdznPDBvOavvaCIv6hGa+fjrXOxihOfv4nFat9bSIOYYeOaRzrLEJp09qfD68Tl06JlHCy84OcZmZrPdjCC4cf6jxtZziYgk2/3oaebkFEImIJ28/VO6DRRH0z9JOqspORjCTFzRDwMaGgC6svHkTRwfpLmhcQJvbBRGnXr/W+HxGi5b6mkOZln7+Wn8wuMJvc45qfE3EqUfEDrCt3esqBK3T1RCca72Csh0drk5XXAe7sbNLbvKC9uLxJxQXFaNmwwrGNoU1HsfHGdsETsHmEoGcQDc31vswFGefLgYA3LryAgsm7cXcNUMJy5mZCdGgeWXS0ZkcueNskbQYXUN/orTb2elqCCRSWfRde3MbHd8BdUxe0JZN24/t56drL2jCdKpUmfGIDUee6xdNl4caLtbaNwa4RtM21QAAzdpWo9XOxda/KcJw5xcXoN2VqTATiDCqYhc0dg6Eg4UtUgsycfvzc+z6cE4hZHKOtVhEq39NmLygaZrPc4VuVaqwIGgRWsuYcmQHOpTV98UlLrVZpZJboEhajD/fncSf7zSvf7J57AnggNvGyj1jcPfaK2ObQYvaHtSjP1DldjR7+RSMSbaO4Yp4dEM+/WSCS21WoYKNF6WyXbyasC5mAAdGaL4V3TGm+xrsvvIjXD24uf1fFt0W2OJeTIyxTeDRga2NQwAAlxMeYmvkKSTkpSqe+Yk9MKFKH9R3qmIwe0xe0OQ+aMPa/Er43FAH13kMQ2RqirFN4NGDth710daDXb9HKpi8oPGC9WWRmJ1tbBPKPGGXX2DN/GPISNMc5onJ6amhMHlB4+HhYQ4qh9O5DC9oZZROlSphU/eexjZDZ+woRAcpC7HvjUFWZsmB8zNPFkEgEKBnowU4cW8eAOBzQga+7rAcfgHu2HKMuVBahsTkBU1biCAuTEkz8/O1F2KYyNRU7YVMkIpOTsY2ocyyNOQAANWppIu7HTLScmDvKIarhz3OPl2MzrVn4/w/D9GxN/GaWLsrUzGuUi/0822lU/8DwxYAAAQQYH+zuXq+C82YvKC16a56bi8/rxC3Lj+HVCLFyj1jjGSVboQnkh/2ZYvIFG4urtfzIo/0wEOP548/qt3z9HHCu5dxqBcUoLjn4++KVXOPkgoaAGx6exyb3h7XyRVDKBAiMY/dH1qTF7QZyweQPutS/WdOjNCuf1T/INGlhrs7IhITSZ9rC45oqnja2hrbhDKLo7MtcnNUf+hq1PPH6cP3VAStfY+62LXhImEbqQUlB/anBZJ/N4nY0GASBtycDwAokhTDTCjSqT4VTN6xtizwz0vNsb30YXCt2oy3yVO26T9a/VD/4DGtcf286iH8s0fJY73tV0pX19VLt/wbLhb2iuu9H4kFky68oBmA+CzNYWiEAoHObQ75ggXtxifmR7xfAl37NQIA7Fh3QXFPfqywe/15eP86Hpt/PYWEWPJp4a3P2o/cUeFqonricCYw+Snnd93U5+h5OYX4nEAvdLUyMRkZ8LG3116QJVZ07MRKuy8/JyHQtexEjZAz/OgRfqdTT3aemQZPH9WNl+lL+mLlrCMY12+D4h6ZD1pCPjNrYFG5SYy0UxqTF7To958J77t7O2LXxRmM9DHjwjns7dufkbb0oU+16qy0+9X+fYxmsjIU67p2w8TTp4xtRpmktJgBQPse9dC+B7U0hz7WrviYTX+Ty9WCneOAJi9ohlj0vxXFzYPeU5s1x6qwm6TP84qKDGgNc3SvUlWroCVmZ8Pdhr24WjzEdPFqopLGTl/aeDCXJ1YZfg2NZZbfYC8H4f8aN9FaRlv0V64S9Ocfxjbhi6S/b2vFdbfQn3SqO/RWyTR2TEB3pkxSgROCFvkqTi0f56iO1EP/UmHrA3ay+Gy+f4+VdqmiLT6/qbK2SzetZTSlB+SRHXMqfdTpt9lHGGs/r7gAz9M/UCqbXJCB+LwSlxEBdN8IowInBO2HPuvRsU8DnHn+C848/wWL/hiJ+OhUdK/F3Lm0X64zn509PZ84t6Eyi9q2p9XHgzKaJq9H1apay1TSklmdB3D3clR5feEE/d3F5XW+V1xPeLgONz9rzr0w+9k2hf8ZwN7oDODAGtre3y9h9b5xCKzjq7jXsGUVnHn+C6OZ0wFZWOu+1ZlboK+3aaPWMkNr03O/cLK21lqm4ppVnNwVHFG3HnY91vwFbLl9q85Zpb4kPAg2AejSwLkKLIRmKJDI1mjnPtuu8lxsZoWcIvIf84F+bRm3SY7Jj9AObr2mImZsEnL+LGNtDTt6WGsZJ4ZydlJxOeFi2Op5rdtoLROTkYF8jm5+GIJn99+z0u6ZVsthZ06cd4FMzAQCAetRawVSqWkvRBz88xoqBnqhYUv1qJdUjz7p+mXe27cfmuqRJ1NOtQ3rKH3JmBw1UX2PQ2vXpj3NJePvZ08x+5LMA9wY742tUWhqXh4a/bEJEqkUnStVxsbuPVjpRxPa/gZE733b6nM4tEP/TSmq8dAWR+zGFQ2OshOr9EUvn+Z626ELJj/lHPBdK3Sp/jNq1C+PBZuGQ2xjieN7wvDHslNwdGbn3N/QI4fhZWeHm998p3Ndql++7b376Ny2JiInT6XU996nT7H36VNs6NYdXSvTD4189cN7jP7nGO12NGEuEqGwuFhruYprVqGBtzcODRhEu8+cwkJ03bMbn9LTaLdlLL6Z0gkJsWkIPfeM1X5m1xiG2TWGsdoHVUx+hAYAUZGJGNN9jcq94M61MHPVYEr16Uy3ApydcWH4SK3lGv6xCSm5uZTbZWM0USyVorIeC+V/9+uPoHLap/UXI99h28MHuBMdrbUs0+9Pn/+H3apUwbL2HWFjYaGx3MvPSTgQHq51vQ4Ap0ZopcnNzkefpos4GYmWKiY/QgNkiVLYcrB98P14NNhMvnj/LiVF7cNkJhSiSCIhqaEdtqZGIoEA98Z8j0ZbNutUb8jhQ6zYwyRUR6DKnHr9usz64emDtY324Jlcx+Q3BdjGycpKZ4GhI2ZvJ03Ruy4VXMRiRHDwuBMVuLhTy2NYTF7QNLlmvAmPUTjaTuz/O61+DPFlCf9hgl6RNXTF2syszH75IydPhbednbHN4Cy7zk4ztgmsYvKCBkDlhMCcsTsV9ycO+B3jZvXAmee/4E2E7vkcewYGqrxmUwQiJ0+F2NyctfbJ+mxVvrxB+zQEN775DqG875leeHiX7RDnnFhDmzC/N7oOaAxAfcTWc2hTAIB/JQ9sWHgc/5vbi3K7azp3VbsXOXkqBh46wGjCW2OOlnb0/grxWVlotnWLQfpr6O2DgwMGst5POXt7RE6eip8unMfBCM2e6kzxeuJkmAk5MQYwGDvfn8XuD+d1rseWP5rJC5pIJFSIGQDS7OkjJnXAspADOgkaGQf6y76Qqbm5aPDHJr3aaFOhIrb16k3bFibwtLVViGpURjpabd/GWNsWIhFeTpjEWHu6sqxDRyzr0BEA0OmvXXiTksxY23NatcaoesZPnmuKtLtimksaJi9obXvWhVQqheC/tafPCelYMvlvzFozRKVccmIGbGyJPe/1HSE5WVsr6m5/+ABLQq9Bk4/L6Hr1MbtVa736MhS+9g4qf4+9T59izmVq4ZDL2dtjUM1aGE8hyocxODd8hOL6SXw8Fl27iodxsVrriYRC9A4MxOSgZkYN9KkJU1oTpSNmle3K4be64xm0RhVO+KGVnmb6+Lsg5mMyPHycYGtvjQ1H/ocu1X/GjysGonW3OrT7G//wawDAxvp7aLfFJs2+W4vComLYiS1x+fcfjG0O4zQaVTItubfDdL7QXzrKgja7xjC0ca+n9kx5Svkk7S2mPpK5RrV2r4s5NYazZpvJj9AA4N8ni7B+/j+o0bA8OvZpoPJMvlkAgBEx4xKFRTLv+cwcw+f95PkyCU36f3tnHhZVucfxLwwIyA5KgqKCC0pdlhS8VphFmoj2WGLPcxNU9GaFJYlL3qumuXSNkqUSlzQtTX3MSjMVMRO3NArMjcUtFCQDFQHZYbh/TDNzzmznzMrMmd/nH897znve83Kc+c67/JbzsuO08CSEevTnvCfUoz+OPpOG6GMpyK38HSN9whDV3Tg5MSxC0OzsRZizaqLKa5aQxo4ghMK35XLfUD5ixuTgiNUYe2Ihll3aarRNAdqysWDs7SR5DV27Ct8CnDAPrtXpvvvvIJK7oN1qME7ybYsYoRGq+fmzzttdJKwTscZtMf5kXd2H1aEzDdIWE6sWtNSSpSitv846p2kjIKkgHulhm+Bg6yjbOJAS6DwA84KWAgBWFi1ERWM51oRuhJNIdcwoS9l4IAgmg1x74/yDa3q3c7nGOHHarFbQ3jw3BeIOMYZ6Dsf0AMkOYYu4RUmoFNl3ezdyq3KQFroJjiLVZiKLB69GUkE85p6fqVKwZhVIQq2QmBGWxrLHpuLFU0s46714agm+e2qF2uvqgkPqi9WuoYk7JA7mUjEDgC62XTDeL07jfblVOch6fLtaMZPSVaQ+xVqHgYbtBGFq3Ozln+tFFzYpXX+lTzQAoLa1XimByobr+xn1jBNk1CpHaDcbbgAAQtyHKF2L6TEB+yu4w2dz8VHoBiQVxCPl/L+RFir/j79YI4m5NTPwbV7tMG2xNKGrnVbk9DSos0Sc+EwIFk7h98F75d1tuFpWpdSXcyXlmLl6t9r7DGVfpvie+LSbkrkXJ3+/ofJaF3s7nN6oOWqJrnZyRaV/Ycp7X+l0rzlx9l6h0rkZgbHYcfMoAEkCFXWM8xtulD5Z5Qjt7D3J1vOT3UZqfa+tjXavrKmdHV993fU1AIAwj6FaP9uQfPDlUUQkqhczAPjm2AXegqqKsXM2ahQzQ6GtmLWLxYhITFMrZgDQ0tqGiMQ0ZJ8pUlsnPKiX7PjnC/zXhJhiFjrAj/d95sKuJ94FAHwyRPWm1IxAZR9pJsayQQOsdIRW3SLx93Oz9+CoqYyDLf/EJm/0mysTMCZc01UmzC9nZXUdbt6pxs071bh1pxrf/HQeLW3coakVmf/J98gtkC/s2tuJ8N6rY/BoQA9cuVWFpZuy0dDUIrv+zxkZOLuZ34hSSsKy7ah68FBWjgoLRM/u7igoKceVW5KRnCEiKW3ce4ZV5hKzjg7J38NkWmwkoiMGorGpBVsO5OHMxVLZtSUbD2HM8MGqn73wZZmYJqd/p9NIa9N/9Q8Xbmq6O3hotCN7pc9zaO8QY+sfykmHJvR6Cm8NeMlofbNKQevh2BMXagpwp+k2+nQNMNpz/uEucQnZU74dcb3isadcsgnAnIJqg4+nK3w8XRExWJLA5fDZYtyvbdCqjeaWNpaYff3+NPT19ZKV/bq74/iQNwHIRz7tYjGO/nYF0UP55SDY89N5FN+sBKBZYKrr+IcsV8X6b09j8/5fZGU+ghI5Xf5FDPDzwu5V01jXpaOu8fM+w517dQAk78FQ08KtB/IM0o65k9B3NBL6jkZ7hxgXH9xAqGc/oyUXZmKVU86xvpIoGHtv7zL6sx5x9MVPlZJfKum/nclTr8nXNZbPjGGJmSLML/HCtfwzsH+w7ajS/arwdOXOKaqOtXtOaS1ma3YcY5UVxYzJ/o/4Jcg5nClPuvvSO59rqClh7Z5T8v7M1j8yjLkjsrFFmGd/k4gZYKWC1sVWYllf06qc0WfZ5XkGfdbS4A9Z5XG+ql24OoMYNVMpQ/DjJ8aLqPDx7hOskQ7f0dOuI/IkKHmfc98zZWyE/Jix7sXEy01uflBWqV2GqBHh/bSqT3BjlYIGAB+GSBKJJBXE473C+Vh6eS6SCuJxt6XSKM+T2reN9TVs+jptGD1bHtvNx5NfGGtfb3k4nTU7cnk/y11NKCddYI4iIxLTsO3Qb7KyrlNBPut3b02Kkh0XlfJz1Vmy4aDaa8OmyzNyvRD1GK/2CO2wyjU0AHC2c0Fm2BYk/56Iv5r+BACEeURgZmAyp3GttgQ6D8CN+qsIcNbOmdfQMNesKqvrtN7BzC8uM3SXeBHg5w0AGDaDnaJPGzHbmVPAKuuze6vIyQ2zEfX3VD77bDFWvKZ6l0/M2FJeMn20wZ5vLtS1NeLCg+uoa22Au70zQj37o6vItH7GVitoAGBva6/SWl+dBb+ulv2tHa0AgPlBy3S631x4yDNMUZe/neYNRaCfFyYs2AyxWC4I69+ZpFUbmkw09MWxC/trVFvfBDdn9ghVG7MOS2LdtX3YU3acs15C39GYFjDG6P2x2imnKSlrKO3sLpgUkciwH6u9Jy7hdlUN69zrH3yNdi3SCVZW1xm0T4pMi5WHiY9+UznPa3K6PLv8nv8lGrUvpqC5vQXRx1J4iRkAbCvNQfSxFLSJtTcz0garHqGZgpI6iTX1x+FbOrknbJbPjDHqpoAhuVdTDwDwdneWHQMSezK+0053FycA1bKyoa3zZ8U9xdsko08Py8681CZux9gTC3W69/nj85Ez8iOItDRQ5wsJmhFYfOlt3G+5Kyv3dxkEOxvTprDj4pfLNy1G0ADg9GfJsqksc/2Lr43Y8Mf64sI17vwC+mAnskVbu2TUuGrLESxKHAUAyNglH8VYupgBElFiwhWs8X5LHSadXiorj86dRwEeLYmobtFws3eHi50r4vu8ipSBizu7SwAAB8Zaz4HTyn545gxzXU5RwE6e514fSxwfyVlHX85skntT7D1xUXb81eF82bGlTzfr29iufHyEyauLq1K9BoV2DIVVC1p4UjrCk9J51+NTPzwpHQuXX8Pqf6xFasg6POH9tKG6qzdbFv+rs7tgMJjikZKxl9MFTKSQT/PmnWo1NQlNrCzcJjvWdpTFrL/88pcG6xMTqxa0Dclx8PXiTlt2LmsOzmXNMUGPjMsA/+6ssiFNF0yNnciWNVJ78tVMmbuVOl6ODpMdx/3HOGuaJzfII3Qovt/j698yyjNNSUH1FYO0c676qkHaUcSqBS0yyB8HV87o7G6YlF82s4WZj6h9l3sBSzYeMlaX9OIEQyQSlm3XGD1kfvyzrHJEYhoam1s5n6GN8CuacKRk7JUdd3Uwr3VUXQhxN4x3Q6incbwkaFPAyrC1tcF/pz6H97+QJxeWfmHHDB8MDxcnVNytwenzf7DMItRFnOhsnBzsYWMDmZBFTte8SfDrlhSWQI14/RMAwJBB/gjq7YPahiYUlJSjQsFMRBumxUbKdjyl63tCcXNa9Gg8Jp56V+92lgQbJzenxY7QKu7VytazpGtbn35/GgAwfukWtetd6w+c0WpNzJBIn1dV85C7shF5cWQIti1T9obIPlOEXUcKcOLcda1svDobRb9MrhGVKsHLLy7Djpx8/HDqsl5iBkhMOBQRiiO6h72L7Phk1QWt7t35d+BHgEJwq2Xh5wcR3q8nAGBzdh6OX7yB8qoHCO7zCAAoCZaXq3FeJBfSfvyc8Sa6u7tw1DY+g/r44NctKXgugjsk0I7lCVgxM8YEvdIdRZF64tVMzvqfL+LeJHnEy1UnmzU7AxsXmxMHR6wGACy7tBW3G+9y1JZw+u5FbLpxgHW/MbDp6NC06mC+VNyrReySzXB3dkTuh2+gubUN/0yWTB+kC/hPzvkUDc2tahf0pSLDd8GfT31VdaTn8te+DVtDRDX8m+eT18vioZlTGOfUwhg87jUez/UwXsQNc+e3ojK8kfo1AEkQR0uMTKuJVnEbxhxfICuP8Y3EC35PYKCbP2xgA3GHGJdrSrGn/DhOVclNWPZGrYKrne5ho7iw+DW09xMljsAO9sp/ysSoEGz7MV/pvCl5ZoEkqocQdkkJ/kjFDLC8MNvRx7T/ccz+Mw/Zf3J7Skw4uQiA9iYffLF4QYsM8meVB/aSmyZ4Ohvvl4APT89bh9qGJqOJ2QM9I74ShNCweEFTXKtwdTJtuBJ1mGKzQWyZqwWCh7kp8eXSyZ3YE934arh5eLbogsULmrlia2OD3z59G4/PSkfU3CycXGPY9SRVER20JbWQvdD/qHs0YnvOY11PGvgVsq6wv5QLgtk2acx2VIVaTi2MUXnPsG6T8LTPdABAZnEcenV9FPXt1bjTKDe6ZN6n2F8A6O86DC/5LwMAlNSewr7yVXC174a6VvlidZTPVAzvxk5Goqot5rOaxfXILGbnaJ07+HuIOHxyFSPbDu77iMb65kgPR/Vh2c0dEjQjkb9W4pqze3ECXl65DYu/yMbKqfzjQUl/5UdFBmHiMyHw8XRBTX0Tvjj4K3Lzr7Hq6rIhkFoYAzubLkgZvI91brTvW7C3lY9ys65MVhKVxvZaOIncZOVJvVcgwEWSlu/6wzx8c0vuiKwN1x/mYajXBEwJUJ3PcUa/DfB26C0rSwVMETd7H7wxQO6ik1oYwxI0qZgpiiyTzOI4JARkwNcpCADww+1UrCl6gXVP+s7jeHboAHi4OuFIXgk2fPczqw1FI2bC+JCgGZkBft0AAAd+KcIrI8Nl5iR8OZJXgiN5JWqvM2PaawtTzKRkXZ2M5CB5ouW43suV6hTc348nu8tHbVIxA4B+Lvo5gT/b4zW115hiBgBBbsr2XgAwua9y6kBF5gerD5Wdf1/yXqRiBgDjei5AYQ07ycqOnHzsyFG96bRo2ijY2pomMQghhwTNBJzLmoPwpHRM/mCHQU03Dme+rpegqZp2NbfXs8qBLhFKddo6+EWuNTTN7fXILInjrsgDTVmIfr33LQDV7+decxm8HfyVzjPJzngN3u7O+nWQ0AmrEzRVi/XMc3FRIVj0r2je9QF+JhlSURsyK4NXfVPYlWmacpkbta2VWH91KuJ6r0AgY0So76SPiQAAAg5JREFUSnT0xVHkgtrWSs73Y062f4QEixU0P283JWFQLCc+H4HE5yM01uHCkPXNzRatorEIfk7m6aOpyM5SiREnU8zaO7gdy9VR1nAJ/l1VZ14a6zcXW2/M0rltovMQrn8GoZFwz3HY/kcKSmrliW+P3lmvdTuOIldkFL8kK39cojp5yffl/5Md6zKqCvOMZZXFHe1YU/SC1u0AgI9jIHaWzsfv1fJ1tMN/fsy6Lu1nW0cLAKCpvQ5ZVwybDYwwPBY7QiP0Y5TvLIzynYWzd3fhw8JY+HUdhPE939G6ndlBu3HxQQ7Si19EoEsEZgd9jfVXp7LqLAg+hIMVafioaByC3Z/FguBD+PSKdsEmh3WbhHCvcVh3NQEt7Y2I7TkPC4IP6SSO0wLXAgBy/9qMjOKJ8Hbwx/ie7Bj50unm7puLUNFYhEFuI5A0ULesX4TpsFhfToIgCEVoykkQhGAgQSMIQjCQoBEEIRhI0AiCEAwkaARBCAYSNIIgBAMJGkEQgoEEjSAIwUCCRhCEYCBBIwhCMJCgEQQhGEjQCIIQDCRoBEEIBhI0giAEAwkaQRCCgQSNIAjBQIJGEIRgIEEjCEIwkKARBCEYSNAIghAMJGgEQQgGEjSCIAQDCRpBEIKBBI0gCMFAgkYQhGAgQSMIQjCQoBEEIRhI0AiCEAwkaARBCAYSNIIgBAMJGkEQguH/Z9ekPKknprsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Taken from https://www.geeksforgeeks.org/generating-word-cloud-python/\n",
    "from wordcloud import WordCloud, STOPWORDS\n",
    "for cluster in range(k):\n",
    "    words = '' \n",
    "    stopwords = set(STOPWORDS) \n",
    "    # iterate through the csv file \n",
    "    for val in processed_data[processed_data.cluster == cluster]['Name']: \n",
    "\n",
    "        # typecaste each val to string \n",
    "        val = str(val) \n",
    "\n",
    "        # split the value \n",
    "        tokens = val.split() \n",
    "\n",
    "        # Converts each token into lowercase \n",
    "        for i in range(len(tokens)): \n",
    "            tokens[i] = tokens[i].lower() \n",
    "\n",
    "        words += \" \".join(tokens)+\" \"\n",
    "\n",
    "    wordcloud = WordCloud(width = 800, height = 800, \n",
    "                    background_color ='white', \n",
    "                    stopwords = stopwords, \n",
    "                    min_font_size = 10).generate(words) \n",
    "\n",
    "    # plot the WordCloud image                        \n",
    "    pyplot.figure(figsize = (4, 4), facecolor = None) \n",
    "    pyplot.imshow(wordcloud) \n",
    "    pyplot.axis(\"off\") \n",
    "    pyplot.tight_layout(pad = 0)\n",
    "    pyplot.title('Cluster ' + str(cluster))\n",
    "\n",
    "    pyplot.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check that our clustering has produced useful results, we can look at the level of correlation between cluster means. This gives us a measure of whether our clusters are producing groups of data with significant differences between them or not. Large correlation indicates that our groups have similar content, while low correlation indicates that our groups differ enough to be considered separate entities:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "# https://www.kaggle.com/allunia/hidden-treasures-in-our-groceries\n",
    "cluster_stats = pandas.DataFrame(data=model.means_)\n",
    "seaborn.set(style=\"white\")\n",
    "corr = cluster_stats.transpose().corr()\n",
    "\n",
    "mask = np.zeros_like(corr, dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "f, ax = pyplot.subplots(figsize=(6, 6))\n",
    "seaborn.heatmap(corr, mask=mask, cmap=\"coolwarm\",\n",
    "            vmin=-1, vmax=1, square=True, center=0,\n",
    "            linewidths=.5, cbar_kws={\"shrink\": .5},\n",
    "           annot=True)\n",
    "ax.set_xlabel(\"Cluster\")\n",
    "ax.set_ylabel(\"Cluster\")\n",
    "ax.set_title(\"Cluster center correlation\");"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}