Customers Segmentation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Customers Segmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option('max_columns', 150)\n",
    "\n",
    "import gc\n",
    "import os\n",
    "\n",
    "# matplotlib and seaborn for plotting\n",
    "import matplotlib\n",
    "matplotlib.rcParams['figure.dpi'] = 120 #resolution\n",
    "matplotlib.rcParams['figure.figsize'] = (8,6) #figure size\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('darkgrid')\n",
    "color = sns.color_palette()\n",
    "\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.metrics import silhouette_score\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "root = 'C:/Data/instacart-market-basket-analysis/'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "aisles = pd.read_csv(root + 'aisles.csv')\n",
    "departments = pd.read_csv(root + 'departments.csv')\n",
    "orders = pd.read_csv(root + 'orders.csv')\n",
    "order_products_prior = pd.read_csv(root + 'order_products__prior.csv')\n",
    "order_products_train = pd.read_csv(root + 'order_products__train.csv')\n",
    "products = pd.read_csv(root + 'products.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For segmentation I am considering users from prior set only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32434489, 15)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "order_products = order_products_prior.merge(products, on ='product_id', how='left')\n",
    "order_products = order_products.merge(aisles, on ='aisle_id', how='left')\n",
    "order_products = order_products.merge(departments, on ='department_id', how='left')\n",
    "order_products = order_products.merge(orders, on='order_id', how='left')\n",
    "order_products.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>add_to_cart_order</th>\n",
       "      <th>reordered</th>\n",
       "      <th>product_name</th>\n",
       "      <th>aisle_id</th>\n",
       "      <th>department_id</th>\n",
       "      <th>aisle</th>\n",
       "      <th>department</th>\n",
       "      <th>user_id</th>\n",
       "      <th>eval_set</th>\n",
       "      <th>order_number</th>\n",
       "      <th>order_dow</th>\n",
       "      <th>order_hour_of_day</th>\n",
       "      <th>days_since_prior_order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>33120</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Organic Egg Whites</td>\n",
       "      <td>86</td>\n",
       "      <td>16</td>\n",
       "      <td>eggs</td>\n",
       "      <td>dairy eggs</td>\n",
       "      <td>202279</td>\n",
       "      <td>prior</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>28985</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Michigan Organic Kale</td>\n",
       "      <td>83</td>\n",
       "      <td>4</td>\n",
       "      <td>fresh vegetables</td>\n",
       "      <td>produce</td>\n",
       "      <td>202279</td>\n",
       "      <td>prior</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>9327</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>Garlic Powder</td>\n",
       "      <td>104</td>\n",
       "      <td>13</td>\n",
       "      <td>spices seasonings</td>\n",
       "      <td>pantry</td>\n",
       "      <td>202279</td>\n",
       "      <td>prior</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>45918</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Coconut Butter</td>\n",
       "      <td>19</td>\n",
       "      <td>13</td>\n",
       "      <td>oils vinegars</td>\n",
       "      <td>pantry</td>\n",
       "      <td>202279</td>\n",
       "      <td>prior</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>30035</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>Natural Sweetener</td>\n",
       "      <td>17</td>\n",
       "      <td>13</td>\n",
       "      <td>baking ingredients</td>\n",
       "      <td>pantry</td>\n",
       "      <td>202279</td>\n",
       "      <td>prior</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  product_id  add_to_cart_order  reordered           product_name  \\\n",
       "0         2       33120                  1          1     Organic Egg Whites   \n",
       "1         2       28985                  2          1  Michigan Organic Kale   \n",
       "2         2        9327                  3          0          Garlic Powder   \n",
       "3         2       45918                  4          1         Coconut Butter   \n",
       "4         2       30035                  5          0      Natural Sweetener   \n",
       "\n",
       "   aisle_id  department_id               aisle  department  user_id eval_set  \\\n",
       "0        86             16                eggs  dairy eggs   202279    prior   \n",
       "1        83              4    fresh vegetables     produce   202279    prior   \n",
       "2       104             13   spices seasonings      pantry   202279    prior   \n",
       "3        19             13       oils vinegars      pantry   202279    prior   \n",
       "4        17             13  baking ingredients      pantry   202279    prior   \n",
       "\n",
       "   order_number  order_dow  order_hour_of_day  days_since_prior_order  \n",
       "0             3          5                  9                     8.0  \n",
       "1             3          5                  9                     8.0  \n",
       "2             3          5                  9                     8.0  \n",
       "3             3          5                  9                     8.0  \n",
       "4             3          5                  9                     8.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "order_products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "206209"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "order_products.user_id.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Segmentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since there are thousands of products in the dataset I will rely on aisles, which represent categories of products. Even with aisles features will be too much so I will use Principal Component Analysis to find new dimensions along which clustering will be easier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>aisle</th>\n",
       "      <th>air fresheners candles</th>\n",
       "      <th>asian foods</th>\n",
       "      <th>baby accessories</th>\n",
       "      <th>baby bath body care</th>\n",
       "      <th>baby food formula</th>\n",
       "      <th>bakery desserts</th>\n",
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       "      <th>beauty</th>\n",
       "      <th>beers coolers</th>\n",
       "      <th>body lotions soap</th>\n",
       "      <th>bread</th>\n",
       "      <th>breakfast bakery</th>\n",
       "      <th>breakfast bars pastries</th>\n",
       "      <th>bulk dried fruits vegetables</th>\n",
       "      <th>bulk grains rice dried goods</th>\n",
       "      <th>buns rolls</th>\n",
       "      <th>butter</th>\n",
       "      <th>candy chocolate</th>\n",
       "      <th>canned fruit applesauce</th>\n",
       "      <th>canned jarred vegetables</th>\n",
       "      <th>canned meals beans</th>\n",
       "      <th>canned meat seafood</th>\n",
       "      <th>cat food care</th>\n",
       "      <th>cereal</th>\n",
       "      <th>chips pretzels</th>\n",
       "      <th>cleaning products</th>\n",
       "      <th>cocoa drink mixes</th>\n",
       "      <th>coffee</th>\n",
       "      <th>cold flu allergy</th>\n",
       "      <th>condiments</th>\n",
       "      <th>cookies cakes</th>\n",
       "      <th>crackers</th>\n",
       "      <th>cream</th>\n",
       "      <th>deodorants</th>\n",
       "      <th>diapers wipes</th>\n",
       "      <th>digestion</th>\n",
       "      <th>dish detergents</th>\n",
       "      <th>dog food care</th>\n",
       "      <th>doughs gelatins bake mixes</th>\n",
       "      <th>dry pasta</th>\n",
       "      <th>eggs</th>\n",
       "      <th>energy granola bars</th>\n",
       "      <th>energy sports drinks</th>\n",
       "      <th>eye ear care</th>\n",
       "      <th>facial care</th>\n",
       "      <th>feminine care</th>\n",
       "      <th>first aid</th>\n",
       "      <th>food storage</th>\n",
       "      <th>fresh dips tapenades</th>\n",
       "      <th>fresh fruits</th>\n",
       "      <th>fresh herbs</th>\n",
       "      <th>fresh pasta</th>\n",
       "      <th>fresh vegetables</th>\n",
       "      <th>frozen appetizers sides</th>\n",
       "      <th>frozen breads doughs</th>\n",
       "      <th>frozen breakfast</th>\n",
       "      <th>frozen dessert</th>\n",
       "      <th>frozen juice</th>\n",
       "      <th>frozen meals</th>\n",
       "      <th>frozen meat seafood</th>\n",
       "      <th>frozen pizza</th>\n",
       "      <th>frozen produce</th>\n",
       "      <th>frozen vegan vegetarian</th>\n",
       "      <th>fruit vegetable snacks</th>\n",
       "      <th>grains rice dried goods</th>\n",
       "      <th>granola</th>\n",
       "      <th>hair care</th>\n",
       "      <th>honeys syrups nectars</th>\n",
       "      <th>hot cereal pancake mixes</th>\n",
       "      <th>hot dogs bacon sausage</th>\n",
       "      <th>ice cream ice</th>\n",
       "      <th>ice cream toppings</th>\n",
       "      <th>indian foods</th>\n",
       "      <th>instant foods</th>\n",
       "      <th>juice nectars</th>\n",
       "      <th>kitchen supplies</th>\n",
       "      <th>kosher foods</th>\n",
       "      <th>latino foods</th>\n",
       "      <th>laundry</th>\n",
       "      <th>lunch meat</th>\n",
       "      <th>marinades meat preparation</th>\n",
       "      <th>meat counter</th>\n",
       "      <th>milk</th>\n",
       "      <th>mint gum</th>\n",
       "      <th>missing</th>\n",
       "      <th>more household</th>\n",
       "      <th>muscles joints pain relief</th>\n",
       "      <th>nuts seeds dried fruit</th>\n",
       "      <th>oils vinegars</th>\n",
       "      <th>oral hygiene</th>\n",
       "      <th>other</th>\n",
       "      <th>other creams cheeses</th>\n",
       "      <th>packaged cheese</th>\n",
       "      <th>packaged meat</th>\n",
       "      <th>packaged poultry</th>\n",
       "      <th>packaged produce</th>\n",
       "      <th>packaged seafood</th>\n",
       "      <th>packaged vegetables fruits</th>\n",
       "      <th>paper goods</th>\n",
       "      <th>pasta sauce</th>\n",
       "      <th>pickled goods olives</th>\n",
       "      <th>plates bowls cups flatware</th>\n",
       "      <th>popcorn jerky</th>\n",
       "      <th>poultry counter</th>\n",
       "      <th>prepared meals</th>\n",
       "      <th>prepared soups salads</th>\n",
       "      <th>preserved dips spreads</th>\n",
       "      <th>protein meal replacements</th>\n",
       "      <th>red wines</th>\n",
       "      <th>refrigerated</th>\n",
       "      <th>refrigerated pudding desserts</th>\n",
       "      <th>salad dressing toppings</th>\n",
       "      <th>seafood counter</th>\n",
       "      <th>shave needs</th>\n",
       "      <th>skin care</th>\n",
       "      <th>soap</th>\n",
       "      <th>soft drinks</th>\n",
       "      <th>soup broth bouillon</th>\n",
       "      <th>soy lactosefree</th>\n",
       "      <th>specialty cheeses</th>\n",
       "      <th>specialty wines champagnes</th>\n",
       "      <th>spices seasonings</th>\n",
       "      <th>spirits</th>\n",
       "      <th>spreads</th>\n",
       "      <th>tea</th>\n",
       "      <th>tofu meat alternatives</th>\n",
       "      <th>tortillas flat bread</th>\n",
       "      <th>trail mix snack mix</th>\n",
       "      <th>trash bags liners</th>\n",
       "      <th>vitamins supplements</th>\n",
       "      <th>water seltzer sparkling water</th>\n",
       "      <th>white wines</th>\n",
       "      <th>yogurt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "aisle    air fresheners candles  asian foods  baby accessories  \\\n",
       "user_id                                                          \n",
       "1                             0            0                 0   \n",
       "2                             0            3                 0   \n",
       "3                             0            0                 0   \n",
       "4                             0            0                 0   \n",
       "5                             0            2                 0   \n",
       "\n",
       "aisle    baby bath body care  baby food formula  bakery desserts  \\\n",
       "user_id                                                            \n",
       "1                          0                  0                0   \n",
       "2                          0                  0                0   \n",
       "3                          0                  0                0   \n",
       "4                          0                  0                0   \n",
       "5                          0                  0                0   \n",
       "\n",
       "aisle    baking ingredients  baking supplies decor  beauty  beers coolers  \\\n",
       "user_id                                                                     \n",
       "1                         0                      0       0              0   \n",
       "2                         2                      0       0              0   \n",
       "3                         0                      0       0              0   \n",
       "4                         0                      0       0              0   \n",
       "5                         0                      0       0              0   \n",
       "\n",
       "aisle    body lotions soap  bread  breakfast bakery  breakfast bars pastries  \\\n",
       "user_id                                                                        \n",
       "1                        0      0                 0                        0   \n",
       "2                        0      1                 1                        2   \n",
       "3                        0      0                 0                        0   \n",
       "4                        0      1                 0                        0   \n",
       "5                        0      0                 0                        0   \n",
       "\n",
       "aisle    bulk dried fruits vegetables  bulk grains rice dried goods  \\\n",
       "user_id                                                               \n",
       "1                                   0                             0   \n",
       "2                                   0                             0   \n",
       "3                                   0                             0   \n",
       "4                                   0                             0   \n",
       "5                                   0                             0   \n",
       "\n",
       "aisle    buns rolls  butter  candy chocolate  canned fruit applesauce  \\\n",
       "user_id                                                                 \n",
       "1                 0       0                1                        0   \n",
       "2                 0       0                0                        0   \n",
       "3                 0       0                0                        0   \n",
       "4                 0       0                0                        0   \n",
       "5                 0       0                0                        0   \n",
       "\n",
       "aisle    canned jarred vegetables  canned meals beans  canned meat seafood  \\\n",
       "user_id                                                                      \n",
       "1                               0                   0                    0   \n",
       "2                               0                   0                    1   \n",
       "3                               0                   0                    0   \n",
       "4                               0                   0                    0   \n",
       "5                               1                   0                    0   \n",
       "\n",
       "aisle    cat food care  cereal  chips pretzels  cleaning products  \\\n",
       "user_id                                                             \n",
       "1                    0       3               0                  0   \n",
       "2                    0       0              12                  0   \n",
       "3                    0       0               0                  0   \n",
       "4                    0       0               1                  0   \n",
       "5                    0       0               1                  0   \n",
       "\n",
       "aisle    cocoa drink mixes  coffee  cold flu allergy  condiments  \\\n",
       "user_id                                                            \n",
       "1                        0       0                 0           0   \n",
       "2                        0       0                 0           5   \n",
       "3                        0       0                 0           0   \n",
       "4                        0       0                 0           0   \n",
       "5                        0       0                 0           0   \n",
       "\n",
       "aisle    cookies cakes  crackers  cream  deodorants  diapers wipes  digestion  \\\n",
       "user_id                                                                         \n",
       "1                    0         0      2           0              0          0   \n",
       "2                    0        11      0           0              0          0   \n",
       "3                    0         6      0           0              0          0   \n",
       "4                    0         0      0           0              0          0   \n",
       "5                    0         0      0           0              0          0   \n",
       "\n",
       "aisle    dish detergents  dog food care  doughs gelatins bake mixes  \\\n",
       "user_id                                                               \n",
       "1                      0              0                           0   \n",
       "2                      0              0                           0   \n",
       "3                      0              0                           0   \n",
       "4                      1              0                           0   \n",
       "5                      0              0                           0   \n",
       "\n",
       "aisle    dry pasta  eggs  energy granola bars  energy sports drinks  \\\n",
       "user_id                                                               \n",
       "1                0     0                    0                     0   \n",
       "2                0     0                    6                     0   \n",
       "3                0     0                    0                     0   \n",
       "4                0     0                    0                     0   \n",
       "5                0     1                    0                     0   \n",
       "\n",
       "aisle    eye ear care  facial care  feminine care  first aid  food storage  \\\n",
       "user_id                                                                      \n",
       "1                   0            0              0          0             0   \n",
       "2                   0            0              0          0             0   \n",
       "3                   0            0              0          0             0   \n",
       "4                   0            0              0          0             0   \n",
       "5                   0            0              0          0             0   \n",
       "\n",
       "aisle    fresh dips tapenades  fresh fruits  fresh herbs  fresh pasta  \\\n",
       "user_id                                                                 \n",
       "1                           0             5            0            0   \n",
       "2                           9            33            0            0   \n",
       "3                           0            19            0            0   \n",
       "4                           2             2            0            0   \n",
       "5                           0             4            1            1   \n",
       "\n",
       "aisle    fresh vegetables  frozen appetizers sides  frozen breads doughs  \\\n",
       "user_id                                                                    \n",
       "1                       0                        0                     0   \n",
       "2                       0                        0                     1   \n",
       "3                       5                        0                     0   \n",
       "4                       0                        0                     0   \n",
       "5                       6                        0                     0   \n",
       "\n",
       "aisle    frozen breakfast  frozen dessert  frozen juice  frozen meals  \\\n",
       "user_id                                                                 \n",
       "1                       0               0             0             0   \n",
       "2                       0               0             0            12   \n",
       "3                       2               0             0             0   \n",
       "4                       0               0             0             3   \n",
       "5                       0               0             0             0   \n",
       "\n",
       "aisle    frozen meat seafood  frozen pizza  frozen produce  \\\n",
       "user_id                                                      \n",
       "1                          0             0               0   \n",
       "2                          0             0               0   \n",
       "3                          0             0               0   \n",
       "4                          0             0               0   \n",
       "5                          0             0               0   \n",
       "\n",
       "aisle    frozen vegan vegetarian  fruit vegetable snacks  \\\n",
       "user_id                                                    \n",
       "1                              0                       0   \n",
       "2                              4                       0   \n",
       "3                              0                       0   \n",
       "4                              0                       0   \n",
       "5                              0                       0   \n",
       "\n",
       "aisle    grains rice dried goods  granola  hair care  honeys syrups nectars  \\\n",
       "user_id                                                                       \n",
       "1                              0        0          0                      0   \n",
       "2                              0        1          0                      0   \n",
       "3                              0        0          0                      0   \n",
       "4                              0        0          0                      0   \n",
       "5                              0        0          0                      1   \n",
       "\n",
       "aisle    hot cereal pancake mixes  hot dogs bacon sausage  ice cream ice  \\\n",
       "user_id                                                                    \n",
       "1                               0                       0              0   \n",
       "2                               0                       0              0   \n",
       "3                               0                       0              4   \n",
       "4                               0                       0              0   \n",
       "5                               0                       0              2   \n",
       "\n",
       "aisle    ice cream toppings  indian foods  instant foods  juice nectars  \\\n",
       "user_id                                                                   \n",
       "1                         0             0              0              0   \n",
       "2                         0             0              0              1   \n",
       "3                         0             0              4              0   \n",
       "4                         0             0              0              0   \n",
       "5                         0             0              0              0   \n",
       "\n",
       "aisle    kitchen supplies  kosher foods  latino foods  laundry  lunch meat  \\\n",
       "user_id                                                                      \n",
       "1                       0             0             0        0           0   \n",
       "2                       0             0             0        0          10   \n",
       "3                       0             0             0        0           0   \n",
       "4                       0             0             0        0           0   \n",
       "5                       0             0             0        0           1   \n",
       "\n",
       "aisle    marinades meat preparation  meat counter  milk  mint gum  missing  \\\n",
       "user_id                                                                      \n",
       "1                                 0             0     0         0        0   \n",
       "2                                 0             0     0         0        0   \n",
       "3                                 0             0     0         0        0   \n",
       "4                                 0             0     0         0        0   \n",
       "5                                 0             0     3         0        0   \n",
       "\n",
       "aisle    more household  muscles joints pain relief  nuts seeds dried fruit  \\\n",
       "user_id                                                                       \n",
       "1                     0                           0                       9   \n",
       "2                     0                           0                       3   \n",
       "3                     0                           0                       3   \n",
       "4                     0                           0                       0   \n",
       "5                     0                           0                       0   \n",
       "\n",
       "aisle    oils vinegars  oral hygiene  other  other creams cheeses  \\\n",
       "user_id                                                             \n",
       "1                    0             0      0                     0   \n",
       "2                    0             1      0                     0   \n",
       "3                    0             0      0                     1   \n",
       "4                    0             0      0                     0   \n",
       "5                    1             0      0                     0   \n",
       "\n",
       "aisle    packaged cheese  packaged meat  packaged poultry  packaged produce  \\\n",
       "user_id                                                                       \n",
       "1                      8              0                 0                 0   \n",
       "2                      5              0                 1                 0   \n",
       "3                      5              0                 0                 0   \n",
       "4                      0              0                 0                 0   \n",
       "5                      1              0                 0                 0   \n",
       "\n",
       "aisle    packaged seafood  packaged vegetables fruits  paper goods  \\\n",
       "user_id                                                              \n",
       "1                       0                           0            2   \n",
       "2                       0                           3            0   \n",
       "3                       0                          14            1   \n",
       "4                       0                           0            0   \n",
       "5                       0                           8            0   \n",
       "\n",
       "aisle    pasta sauce  pickled goods olives  plates bowls cups flatware  \\\n",
       "user_id                                                                  \n",
       "1                  0                     0                           0   \n",
       "2                  0                     1                           0   \n",
       "3                  0                     0                           0   \n",
       "4                  0                     0                           1   \n",
       "5                  0                     0                           0   \n",
       "\n",
       "aisle    popcorn jerky  poultry counter  prepared meals  \\\n",
       "user_id                                                   \n",
       "1                   12                0               0   \n",
       "2                   10                0               0   \n",
       "3                    0                0               2   \n",
       "4                    0                0               0   \n",
       "5                    0                0               0   \n",
       "\n",
       "aisle    prepared soups salads  preserved dips spreads  \\\n",
       "user_id                                                  \n",
       "1                            0                       0   \n",
       "2                            1                       0   \n",
       "3                            0                       0   \n",
       "4                            0                       0   \n",
       "5                            0                       0   \n",
       "\n",
       "aisle    protein meal replacements  red wines  refrigerated  \\\n",
       "user_id                                                       \n",
       "1                                0          0             0   \n",
       "2                                0          0             5   \n",
       "3                                0          0             0   \n",
       "4                                0          1             1   \n",
       "5                                0          0             0   \n",
       "\n",
       "aisle    refrigerated pudding desserts  salad dressing toppings  \\\n",
       "user_id                                                           \n",
       "1                                    0                        0   \n",
       "2                                    0                        0   \n",
       "3                                    0                        0   \n",
       "4                                    0                        0   \n",
       "5                                    0                        0   \n",
       "\n",
       "aisle    seafood counter  shave needs  skin care  soap  soft drinks  \\\n",
       "user_id                                                               \n",
       "1                      0            0          0     0           13   \n",
       "2                      0            0          0     0            0   \n",
       "3                      0            0          0     0            0   \n",
       "4                      0            0          0     0            1   \n",
       "5                      0            0          0     0            0   \n",
       "\n",
       "aisle    soup broth bouillon  soy lactosefree  specialty cheeses  \\\n",
       "user_id                                                            \n",
       "1                          0                2                  0   \n",
       "2                          0                1                  0   \n",
       "3                          0               15                  0   \n",
       "4                          1                0                  0   \n",
       "5                          0                0                  0   \n",
       "\n",
       "aisle    specialty wines champagnes  spices seasonings  spirits  spreads  tea  \\\n",
       "user_id                                                                         \n",
       "1                                 0                  0        0        1    0   \n",
       "2                                 0                  0        0        3    1   \n",
       "3                                 0                  0        0        4    1   \n",
       "4                                 1                  0        0        0    0   \n",
       "5                                 0                  0        0        0    0   \n",
       "\n",
       "aisle    tofu meat alternatives  tortillas flat bread  trail mix snack mix  \\\n",
       "user_id                                                                      \n",
       "1                             0                     0                    0   \n",
       "2                             1                     0                    0   \n",
       "3                             0                     0                    0   \n",
       "4                             0                     1                    0   \n",
       "5                             0                     0                    0   \n",
       "\n",
       "aisle    trash bags liners  vitamins supplements  \\\n",
       "user_id                                            \n",
       "1                        0                     0   \n",
       "2                        0                     0   \n",
       "3                        0                     0   \n",
       "4                        0                     0   \n",
       "5                        0                     0   \n",
       "\n",
       "aisle    water seltzer sparkling water  white wines  yogurt  \n",
       "user_id                                                      \n",
       "1                                    0            0       1  \n",
       "2                                    2            0      42  \n",
       "3                                    2            0       0  \n",
       "4                                    1            0       0  \n",
       "5                                    0            0       3  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cross_df = pd.crosstab(order_products.user_id, order_products.aisle)\n",
    "cross_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>aisle</th>\n",
       "      <th>air fresheners candles</th>\n",
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       "      <th>crackers</th>\n",
       "      <th>cream</th>\n",
       "      <th>deodorants</th>\n",
       "      <th>diapers wipes</th>\n",
       "      <th>digestion</th>\n",
       "      <th>dish detergents</th>\n",
       "      <th>dog food care</th>\n",
       "      <th>doughs gelatins bake mixes</th>\n",
       "      <th>dry pasta</th>\n",
       "      <th>eggs</th>\n",
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       "      <th>fresh herbs</th>\n",
       "      <th>fresh pasta</th>\n",
       "      <th>fresh vegetables</th>\n",
       "      <th>frozen appetizers sides</th>\n",
       "      <th>frozen breads doughs</th>\n",
       "      <th>frozen breakfast</th>\n",
       "      <th>frozen dessert</th>\n",
       "      <th>frozen juice</th>\n",
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       "      <th>frozen vegan vegetarian</th>\n",
       "      <th>fruit vegetable snacks</th>\n",
       "      <th>grains rice dried goods</th>\n",
       "      <th>granola</th>\n",
       "      <th>hair care</th>\n",
       "      <th>honeys syrups nectars</th>\n",
       "      <th>hot cereal pancake mixes</th>\n",
       "      <th>hot dogs bacon sausage</th>\n",
       "      <th>ice cream ice</th>\n",
       "      <th>ice cream toppings</th>\n",
       "      <th>indian foods</th>\n",
       "      <th>instant foods</th>\n",
       "      <th>juice nectars</th>\n",
       "      <th>kitchen supplies</th>\n",
       "      <th>kosher foods</th>\n",
       "      <th>latino foods</th>\n",
       "      <th>laundry</th>\n",
       "      <th>lunch meat</th>\n",
       "      <th>marinades meat preparation</th>\n",
       "      <th>meat counter</th>\n",
       "      <th>milk</th>\n",
       "      <th>mint gum</th>\n",
       "      <th>missing</th>\n",
       "      <th>more household</th>\n",
       "      <th>muscles joints pain relief</th>\n",
       "      <th>nuts seeds dried fruit</th>\n",
       "      <th>oils vinegars</th>\n",
       "      <th>oral hygiene</th>\n",
       "      <th>other</th>\n",
       "      <th>other creams cheeses</th>\n",
       "      <th>packaged cheese</th>\n",
       "      <th>packaged meat</th>\n",
       "      <th>packaged poultry</th>\n",
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       "      <th>packaged seafood</th>\n",
       "      <th>packaged vegetables fruits</th>\n",
       "      <th>paper goods</th>\n",
       "      <th>pasta sauce</th>\n",
       "      <th>pickled goods olives</th>\n",
       "      <th>plates bowls cups flatware</th>\n",
       "      <th>popcorn jerky</th>\n",
       "      <th>poultry counter</th>\n",
       "      <th>prepared meals</th>\n",
       "      <th>prepared soups salads</th>\n",
       "      <th>preserved dips spreads</th>\n",
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       "      <th>red wines</th>\n",
       "      <th>refrigerated</th>\n",
       "      <th>refrigerated pudding desserts</th>\n",
       "      <th>salad dressing toppings</th>\n",
       "      <th>seafood counter</th>\n",
       "      <th>shave needs</th>\n",
       "      <th>skin care</th>\n",
       "      <th>soap</th>\n",
       "      <th>soft drinks</th>\n",
       "      <th>soup broth bouillon</th>\n",
       "      <th>soy lactosefree</th>\n",
       "      <th>specialty cheeses</th>\n",
       "      <th>specialty wines champagnes</th>\n",
       "      <th>spices seasonings</th>\n",
       "      <th>spirits</th>\n",
       "      <th>spreads</th>\n",
       "      <th>tea</th>\n",
       "      <th>tofu meat alternatives</th>\n",
       "      <th>tortillas flat bread</th>\n",
       "      <th>trail mix snack mix</th>\n",
       "      <th>trash bags liners</th>\n",
       "      <th>vitamins supplements</th>\n",
       "      <th>water seltzer sparkling water</th>\n",
       "      <th>white wines</th>\n",
       "      <th>yogurt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>206205</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206206</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206207</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206208</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>55</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>71</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206209</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "user_id                                                          \n",
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       "user_id                                                                     \n",
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       "user_id                                                                 \n",
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       "user_id                                                                      \n",
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       "user_id                                                             \n",
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       "user_id                                                            \n",
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       "user_id                                                                         \n",
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       "user_id                                                               \n",
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       "user_id                                                                      \n",
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       "user_id                                                                    \n",
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       "user_id                                                                       \n",
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       "user_id                                                                   \n",
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       "user_id                                                                       \n",
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       "user_id                                                              \n",
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       "user_id                                                                  \n",
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       "user_id                                                       \n",
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       "user_id                                                               \n",
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       "user_id                                                            \n",
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       "aisle    tofu meat alternatives  tortillas flat bread  trail mix snack mix  \\\n",
       "user_id                                                                      \n",
       "206205                        0                     0                    0   \n",
       "206206                        0                     0                    0   \n",
       "206207                        0                     2                    1   \n",
       "206208                        0                     7                    0   \n",
       "206209                        0                     0                    0   \n",
       "\n",
       "aisle    trash bags liners  vitamins supplements  \\\n",
       "user_id                                            \n",
       "206205                   0                     0   \n",
       "206206                   1                     0   \n",
       "206207                   0                     0   \n",
       "206208                   0                     0   \n",
       "206209                   1                     0   \n",
       "\n",
       "aisle    water seltzer sparkling water  white wines  yogurt  \n",
       "user_id                                                      \n",
       "206205                               0            0       5  \n",
       "206206                               1            0       0  \n",
       "206207                              11            0      15  \n",
       "206208                               0            0      33  \n",
       "206209                               0            0       3  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cross_df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will normalize each row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>aisle</th>\n",
       "      <th>air fresheners candles</th>\n",
       "      <th>asian foods</th>\n",
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       "      <th>baby food formula</th>\n",
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       "      <th>baking supplies decor</th>\n",
       "      <th>beauty</th>\n",
       "      <th>beers coolers</th>\n",
       "      <th>body lotions soap</th>\n",
       "      <th>bread</th>\n",
       "      <th>breakfast bakery</th>\n",
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       "      <th>buns rolls</th>\n",
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       "      <th>candy chocolate</th>\n",
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       "      <th>condiments</th>\n",
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       "      <th>dog food care</th>\n",
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       "      <th>dry pasta</th>\n",
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       "      <th>eye ear care</th>\n",
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       "      <th>fresh pasta</th>\n",
       "      <th>fresh vegetables</th>\n",
       "      <th>frozen appetizers sides</th>\n",
       "      <th>frozen breads doughs</th>\n",
       "      <th>frozen breakfast</th>\n",
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       "      <th>frozen juice</th>\n",
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       "      <th>frozen pizza</th>\n",
       "      <th>frozen produce</th>\n",
       "      <th>frozen vegan vegetarian</th>\n",
       "      <th>fruit vegetable snacks</th>\n",
       "      <th>grains rice dried goods</th>\n",
       "      <th>granola</th>\n",
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       "      <th>hot cereal pancake mixes</th>\n",
       "      <th>hot dogs bacon sausage</th>\n",
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       "      <th>indian foods</th>\n",
       "      <th>instant foods</th>\n",
       "      <th>juice nectars</th>\n",
       "      <th>kitchen supplies</th>\n",
       "      <th>kosher foods</th>\n",
       "      <th>latino foods</th>\n",
       "      <th>laundry</th>\n",
       "      <th>lunch meat</th>\n",
       "      <th>marinades meat preparation</th>\n",
       "      <th>meat counter</th>\n",
       "      <th>milk</th>\n",
       "      <th>mint gum</th>\n",
       "      <th>missing</th>\n",
       "      <th>more household</th>\n",
       "      <th>muscles joints pain relief</th>\n",
       "      <th>nuts seeds dried fruit</th>\n",
       "      <th>oils vinegars</th>\n",
       "      <th>oral hygiene</th>\n",
       "      <th>other</th>\n",
       "      <th>other creams cheeses</th>\n",
       "      <th>packaged cheese</th>\n",
       "      <th>packaged meat</th>\n",
       "      <th>packaged poultry</th>\n",
       "      <th>packaged produce</th>\n",
       "      <th>packaged seafood</th>\n",
       "      <th>packaged vegetables fruits</th>\n",
       "      <th>paper goods</th>\n",
       "      <th>pasta sauce</th>\n",
       "      <th>pickled goods olives</th>\n",
       "      <th>plates bowls cups flatware</th>\n",
       "      <th>popcorn jerky</th>\n",
       "      <th>poultry counter</th>\n",
       "      <th>prepared meals</th>\n",
       "      <th>prepared soups salads</th>\n",
       "      <th>preserved dips spreads</th>\n",
       "      <th>protein meal replacements</th>\n",
       "      <th>red wines</th>\n",
       "      <th>refrigerated</th>\n",
       "      <th>refrigerated pudding desserts</th>\n",
       "      <th>salad dressing toppings</th>\n",
       "      <th>seafood counter</th>\n",
       "      <th>shave needs</th>\n",
       "      <th>skin care</th>\n",
       "      <th>soap</th>\n",
       "      <th>soft drinks</th>\n",
       "      <th>soup broth bouillon</th>\n",
       "      <th>soy lactosefree</th>\n",
       "      <th>specialty cheeses</th>\n",
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       "      <th>trash bags liners</th>\n",
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       "      <th>water seltzer sparkling water</th>\n",
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       "    </tr>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015385</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005128</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025641</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005128</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.015385</td>\n",
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       "      <td>0.005128</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.005128</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.025641</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005128</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015385</td>\n",
       "      <td>0.005128</td>\n",
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       "      <td>0.010256</td>\n",
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       "      <td>0.215385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.056818</td>\n",
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       "      <td>0.045455</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.034091</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.011364</td>\n",
       "      <td>0.056818</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.159091</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022727</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.170455</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.045455</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.111111</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.055556</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.055556</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.055556</td>\n",
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       "      <td>0.055556</td>\n",
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       "      <td>0.055556</td>\n",
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       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.027027</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.108108</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.162162</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.081081</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.216216</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.081081</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "aisle    air fresheners candles  asian foods  baby accessories  \\\n",
       "user_id                                                          \n",
       "1                           0.0     0.000000               0.0   \n",
       "2                           0.0     0.015385               0.0   \n",
       "3                           0.0     0.000000               0.0   \n",
       "4                           0.0     0.000000               0.0   \n",
       "5                           0.0     0.054054               0.0   \n",
       "\n",
       "aisle    baby bath body care  baby food formula  bakery desserts  \\\n",
       "user_id                                                            \n",
       "1                        0.0                0.0              0.0   \n",
       "2                        0.0                0.0              0.0   \n",
       "3                        0.0                0.0              0.0   \n",
       "4                        0.0                0.0              0.0   \n",
       "5                        0.0                0.0              0.0   \n",
       "\n",
       "aisle    baking ingredients  baking supplies decor  beauty  beers coolers  \\\n",
       "user_id                                                                     \n",
       "1                  0.000000                    0.0     0.0            0.0   \n",
       "2                  0.010256                    0.0     0.0            0.0   \n",
       "3                  0.000000                    0.0     0.0            0.0   \n",
       "4                  0.000000                    0.0     0.0            0.0   \n",
       "5                  0.000000                    0.0     0.0            0.0   \n",
       "\n",
       "aisle    body lotions soap     bread  breakfast bakery  \\\n",
       "user_id                                                  \n",
       "1                      0.0  0.000000          0.000000   \n",
       "2                      0.0  0.005128          0.005128   \n",
       "3                      0.0  0.000000          0.000000   \n",
       "4                      0.0  0.055556          0.000000   \n",
       "5                      0.0  0.000000          0.000000   \n",
       "\n",
       "aisle    breakfast bars pastries  bulk dried fruits vegetables  \\\n",
       "user_id                                                          \n",
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       "4                       0.000000                           0.0   \n",
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       "\n",
       "aisle    bulk grains rice dried goods  buns rolls  butter  candy chocolate  \\\n",
       "user_id                                                                      \n",
       "1                                 0.0         0.0     0.0         0.016949   \n",
       "2                                 0.0         0.0     0.0         0.000000   \n",
       "3                                 0.0         0.0     0.0         0.000000   \n",
       "4                                 0.0         0.0     0.0         0.000000   \n",
       "5                                 0.0         0.0     0.0         0.000000   \n",
       "\n",
       "aisle    canned fruit applesauce  canned jarred vegetables  \\\n",
       "user_id                                                      \n",
       "1                            0.0                  0.000000   \n",
       "2                            0.0                  0.000000   \n",
       "3                            0.0                  0.000000   \n",
       "4                            0.0                  0.000000   \n",
       "5                            0.0                  0.027027   \n",
       "\n",
       "aisle    canned meals beans  canned meat seafood  cat food care    cereal  \\\n",
       "user_id                                                                     \n",
       "1                       0.0             0.000000            0.0  0.050847   \n",
       "2                       0.0             0.005128            0.0  0.000000   \n",
       "3                       0.0             0.000000            0.0  0.000000   \n",
       "4                       0.0             0.000000            0.0  0.000000   \n",
       "5                       0.0             0.000000            0.0  0.000000   \n",
       "\n",
       "aisle    chips pretzels  cleaning products  cocoa drink mixes  coffee  \\\n",
       "user_id                                                                 \n",
       "1              0.000000                0.0                0.0     0.0   \n",
       "2              0.061538                0.0                0.0     0.0   \n",
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       "4              0.055556                0.0                0.0     0.0   \n",
       "5              0.027027                0.0                0.0     0.0   \n",
       "\n",
       "aisle    cold flu allergy  condiments  cookies cakes  crackers     cream  \\\n",
       "user_id                                                                    \n",
       "1                     0.0    0.000000            0.0  0.000000  0.033898   \n",
       "2                     0.0    0.025641            0.0  0.056410  0.000000   \n",
       "3                     0.0    0.000000            0.0  0.068182  0.000000   \n",
       "4                     0.0    0.000000            0.0  0.000000  0.000000   \n",
       "5                     0.0    0.000000            0.0  0.000000  0.000000   \n",
       "\n",
       "aisle    deodorants  diapers wipes  digestion  dish detergents  dog food care  \\\n",
       "user_id                                                                         \n",
       "1               0.0            0.0        0.0         0.000000            0.0   \n",
       "2               0.0            0.0        0.0         0.000000            0.0   \n",
       "3               0.0            0.0        0.0         0.000000            0.0   \n",
       "4               0.0            0.0        0.0         0.055556            0.0   \n",
       "5               0.0            0.0        0.0         0.000000            0.0   \n",
       "\n",
       "aisle    doughs gelatins bake mixes  dry pasta      eggs  energy granola bars  \\\n",
       "user_id                                                                         \n",
       "1                               0.0        0.0  0.000000             0.000000   \n",
       "2                               0.0        0.0  0.000000             0.030769   \n",
       "3                               0.0        0.0  0.000000             0.000000   \n",
       "4                               0.0        0.0  0.000000             0.000000   \n",
       "5                               0.0        0.0  0.027027             0.000000   \n",
       "\n",
       "aisle    energy sports drinks  eye ear care  facial care  feminine care  \\\n",
       "user_id                                                                   \n",
       "1                         0.0           0.0          0.0            0.0   \n",
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       "4                         0.0           0.0          0.0            0.0   \n",
       "5                         0.0           0.0          0.0            0.0   \n",
       "\n",
       "aisle    first aid  food storage  fresh dips tapenades  fresh fruits  \\\n",
       "user_id                                                                \n",
       "1              0.0           0.0              0.000000      0.084746   \n",
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       "4              0.0           0.0              0.111111      0.111111   \n",
       "5              0.0           0.0              0.000000      0.108108   \n",
       "\n",
       "aisle    fresh herbs  fresh pasta  fresh vegetables  frozen appetizers sides  \\\n",
       "user_id                                                                        \n",
       "1           0.000000     0.000000          0.000000                      0.0   \n",
       "2           0.000000     0.000000          0.000000                      0.0   \n",
       "3           0.000000     0.000000          0.056818                      0.0   \n",
       "4           0.000000     0.000000          0.000000                      0.0   \n",
       "5           0.027027     0.027027          0.162162                      0.0   \n",
       "\n",
       "aisle    frozen breads doughs  frozen breakfast  frozen dessert  frozen juice  \\\n",
       "user_id                                                                         \n",
       "1                    0.000000          0.000000             0.0           0.0   \n",
       "2                    0.005128          0.000000             0.0           0.0   \n",
       "3                    0.000000          0.022727             0.0           0.0   \n",
       "4                    0.000000          0.000000             0.0           0.0   \n",
       "5                    0.000000          0.000000             0.0           0.0   \n",
       "\n",
       "aisle    frozen meals  frozen meat seafood  frozen pizza  frozen produce  \\\n",
       "user_id                                                                    \n",
       "1            0.000000                  0.0           0.0             0.0   \n",
       "2            0.061538                  0.0           0.0             0.0   \n",
       "3            0.000000                  0.0           0.0             0.0   \n",
       "4            0.166667                  0.0           0.0             0.0   \n",
       "5            0.000000                  0.0           0.0             0.0   \n",
       "\n",
       "aisle    frozen vegan vegetarian  fruit vegetable snacks  \\\n",
       "user_id                                                    \n",
       "1                       0.000000                     0.0   \n",
       "2                       0.020513                     0.0   \n",
       "3                       0.000000                     0.0   \n",
       "4                       0.000000                     0.0   \n",
       "5                       0.000000                     0.0   \n",
       "\n",
       "aisle    grains rice dried goods   granola  hair care  honeys syrups nectars  \\\n",
       "user_id                                                                        \n",
       "1                            0.0  0.000000        0.0               0.000000   \n",
       "2                            0.0  0.005128        0.0               0.000000   \n",
       "3                            0.0  0.000000        0.0               0.000000   \n",
       "4                            0.0  0.000000        0.0               0.000000   \n",
       "5                            0.0  0.000000        0.0               0.027027   \n",
       "\n",
       "aisle    hot cereal pancake mixes  hot dogs bacon sausage  ice cream ice  \\\n",
       "user_id                                                                    \n",
       "1                             0.0                     0.0       0.000000   \n",
       "2                             0.0                     0.0       0.000000   \n",
       "3                             0.0                     0.0       0.045455   \n",
       "4                             0.0                     0.0       0.000000   \n",
       "5                             0.0                     0.0       0.054054   \n",
       "\n",
       "aisle    ice cream toppings  indian foods  instant foods  juice nectars  \\\n",
       "user_id                                                                   \n",
       "1                       0.0           0.0       0.000000       0.000000   \n",
       "2                       0.0           0.0       0.000000       0.005128   \n",
       "3                       0.0           0.0       0.045455       0.000000   \n",
       "4                       0.0           0.0       0.000000       0.000000   \n",
       "5                       0.0           0.0       0.000000       0.000000   \n",
       "\n",
       "aisle    kitchen supplies  kosher foods  latino foods  laundry  lunch meat  \\\n",
       "user_id                                                                      \n",
       "1                     0.0           0.0           0.0      0.0    0.000000   \n",
       "2                     0.0           0.0           0.0      0.0    0.051282   \n",
       "3                     0.0           0.0           0.0      0.0    0.000000   \n",
       "4                     0.0           0.0           0.0      0.0    0.000000   \n",
       "5                     0.0           0.0           0.0      0.0    0.027027   \n",
       "\n",
       "aisle    marinades meat preparation  meat counter      milk  mint gum  \\\n",
       "user_id                                                                 \n",
       "1                               0.0           0.0  0.000000       0.0   \n",
       "2                               0.0           0.0  0.000000       0.0   \n",
       "3                               0.0           0.0  0.000000       0.0   \n",
       "4                               0.0           0.0  0.000000       0.0   \n",
       "5                               0.0           0.0  0.081081       0.0   \n",
       "\n",
       "aisle    missing  more household  muscles joints pain relief  \\\n",
       "user_id                                                        \n",
       "1            0.0             0.0                         0.0   \n",
       "2            0.0             0.0                         0.0   \n",
       "3            0.0             0.0                         0.0   \n",
       "4            0.0             0.0                         0.0   \n",
       "5            0.0             0.0                         0.0   \n",
       "\n",
       "aisle    nuts seeds dried fruit  oils vinegars  oral hygiene  other  \\\n",
       "user_id                                                               \n",
       "1                      0.152542       0.000000      0.000000    0.0   \n",
       "2                      0.015385       0.000000      0.005128    0.0   \n",
       "3                      0.034091       0.000000      0.000000    0.0   \n",
       "4                      0.000000       0.000000      0.000000    0.0   \n",
       "5                      0.000000       0.027027      0.000000    0.0   \n",
       "\n",
       "aisle    other creams cheeses  packaged cheese  packaged meat  \\\n",
       "user_id                                                         \n",
       "1                    0.000000         0.135593            0.0   \n",
       "2                    0.000000         0.025641            0.0   \n",
       "3                    0.011364         0.056818            0.0   \n",
       "4                    0.000000         0.000000            0.0   \n",
       "5                    0.000000         0.027027            0.0   \n",
       "\n",
       "aisle    packaged poultry  packaged produce  packaged seafood  \\\n",
       "user_id                                                         \n",
       "1                0.000000               0.0               0.0   \n",
       "2                0.005128               0.0               0.0   \n",
       "3                0.000000               0.0               0.0   \n",
       "4                0.000000               0.0               0.0   \n",
       "5                0.000000               0.0               0.0   \n",
       "\n",
       "aisle    packaged vegetables fruits  paper goods  pasta sauce  \\\n",
       "user_id                                                         \n",
       "1                          0.000000     0.033898          0.0   \n",
       "2                          0.015385     0.000000          0.0   \n",
       "3                          0.159091     0.011364          0.0   \n",
       "4                          0.000000     0.000000          0.0   \n",
       "5                          0.216216     0.000000          0.0   \n",
       "\n",
       "aisle    pickled goods olives  plates bowls cups flatware  popcorn jerky  \\\n",
       "user_id                                                                    \n",
       "1                    0.000000                    0.000000       0.203390   \n",
       "2                    0.005128                    0.000000       0.051282   \n",
       "3                    0.000000                    0.000000       0.000000   \n",
       "4                    0.000000                    0.055556       0.000000   \n",
       "5                    0.000000                    0.000000       0.000000   \n",
       "\n",
       "aisle    poultry counter  prepared meals  prepared soups salads  \\\n",
       "user_id                                                           \n",
       "1                    0.0        0.000000               0.000000   \n",
       "2                    0.0        0.000000               0.005128   \n",
       "3                    0.0        0.022727               0.000000   \n",
       "4                    0.0        0.000000               0.000000   \n",
       "5                    0.0        0.000000               0.000000   \n",
       "\n",
       "aisle    preserved dips spreads  protein meal replacements  red wines  \\\n",
       "user_id                                                                 \n",
       "1                           0.0                        0.0   0.000000   \n",
       "2                           0.0                        0.0   0.000000   \n",
       "3                           0.0                        0.0   0.000000   \n",
       "4                           0.0                        0.0   0.055556   \n",
       "5                           0.0                        0.0   0.000000   \n",
       "\n",
       "aisle    refrigerated  refrigerated pudding desserts  salad dressing toppings  \\\n",
       "user_id                                                                         \n",
       "1            0.000000                            0.0                      0.0   \n",
       "2            0.025641                            0.0                      0.0   \n",
       "3            0.000000                            0.0                      0.0   \n",
       "4            0.055556                            0.0                      0.0   \n",
       "5            0.000000                            0.0                      0.0   \n",
       "\n",
       "aisle    seafood counter  shave needs  skin care  soap  soft drinks  \\\n",
       "user_id                                                               \n",
       "1                    0.0          0.0        0.0   0.0     0.220339   \n",
       "2                    0.0          0.0        0.0   0.0     0.000000   \n",
       "3                    0.0          0.0        0.0   0.0     0.000000   \n",
       "4                    0.0          0.0        0.0   0.0     0.055556   \n",
       "5                    0.0          0.0        0.0   0.0     0.000000   \n",
       "\n",
       "aisle    soup broth bouillon  soy lactosefree  specialty cheeses  \\\n",
       "user_id                                                            \n",
       "1                   0.000000         0.033898                0.0   \n",
       "2                   0.000000         0.005128                0.0   \n",
       "3                   0.000000         0.170455                0.0   \n",
       "4                   0.055556         0.000000                0.0   \n",
       "5                   0.000000         0.000000                0.0   \n",
       "\n",
       "aisle    specialty wines champagnes  spices seasonings  spirits   spreads  \\\n",
       "user_id                                                                     \n",
       "1                          0.000000                0.0      0.0  0.016949   \n",
       "2                          0.000000                0.0      0.0  0.015385   \n",
       "3                          0.000000                0.0      0.0  0.045455   \n",
       "4                          0.055556                0.0      0.0  0.000000   \n",
       "5                          0.000000                0.0      0.0  0.000000   \n",
       "\n",
       "aisle         tea  tofu meat alternatives  tortillas flat bread  \\\n",
       "user_id                                                           \n",
       "1        0.000000                0.000000              0.000000   \n",
       "2        0.005128                0.005128              0.000000   \n",
       "3        0.011364                0.000000              0.000000   \n",
       "4        0.000000                0.000000              0.055556   \n",
       "5        0.000000                0.000000              0.000000   \n",
       "\n",
       "aisle    trail mix snack mix  trash bags liners  vitamins supplements  \\\n",
       "user_id                                                                 \n",
       "1                        0.0                0.0                   0.0   \n",
       "2                        0.0                0.0                   0.0   \n",
       "3                        0.0                0.0                   0.0   \n",
       "4                        0.0                0.0                   0.0   \n",
       "5                        0.0                0.0                   0.0   \n",
       "\n",
       "aisle    water seltzer sparkling water  white wines    yogurt  \n",
       "user_id                                                        \n",
       "1                             0.000000          0.0  0.016949  \n",
       "2                             0.010256          0.0  0.215385  \n",
       "3                             0.022727          0.0  0.000000  \n",
       "4                             0.055556          0.0  0.000000  \n",
       "5                             0.000000          0.0  0.081081  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = cross_df.div(cross_df.sum(axis=1), axis=0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(206209, 134)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### PCA and K-Means Clustering\n",
    "\n",
    "Reducing this dataframe to only 10 dimensions as KMeans does not work properly in higher dimension. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.113443</td>\n",
       "      <td>0.039084</td>\n",
       "      <td>-0.042863</td>\n",
       "      <td>0.018866</td>\n",
       "      <td>-0.088340</td>\n",
       "      <td>-0.104530</td>\n",
       "      <td>-0.116424</td>\n",
       "      <td>0.083779</td>\n",
       "      <td>-0.062457</td>\n",
       "      <td>-0.026213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.036988</td>\n",
       "      <td>0.108884</td>\n",
       "      <td>-0.066406</td>\n",
       "      <td>-0.123270</td>\n",
       "      <td>0.098849</td>\n",
       "      <td>-0.033951</td>\n",
       "      <td>-0.054720</td>\n",
       "      <td>-0.053306</td>\n",
       "      <td>-0.020162</td>\n",
       "      <td>-0.008098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.064282</td>\n",
       "      <td>0.103962</td>\n",
       "      <td>0.000710</td>\n",
       "      <td>-0.012220</td>\n",
       "      <td>-0.046984</td>\n",
       "      <td>0.112258</td>\n",
       "      <td>-0.029785</td>\n",
       "      <td>0.007953</td>\n",
       "      <td>0.012701</td>\n",
       "      <td>0.001861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.093210</td>\n",
       "      <td>0.054093</td>\n",
       "      <td>0.001867</td>\n",
       "      <td>-0.003974</td>\n",
       "      <td>-0.071357</td>\n",
       "      <td>-0.019266</td>\n",
       "      <td>-0.025105</td>\n",
       "      <td>-0.038207</td>\n",
       "      <td>0.006912</td>\n",
       "      <td>-0.000437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.094629</td>\n",
       "      <td>-0.037051</td>\n",
       "      <td>-0.024952</td>\n",
       "      <td>-0.021575</td>\n",
       "      <td>0.055369</td>\n",
       "      <td>0.107650</td>\n",
       "      <td>-0.008033</td>\n",
       "      <td>0.103943</td>\n",
       "      <td>0.051746</td>\n",
       "      <td>-0.025777</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6  \\\n",
       "0 -0.113443  0.039084 -0.042863  0.018866 -0.088340 -0.104530 -0.116424   \n",
       "1 -0.036988  0.108884 -0.066406 -0.123270  0.098849 -0.033951 -0.054720   \n",
       "2  0.064282  0.103962  0.000710 -0.012220 -0.046984  0.112258 -0.029785   \n",
       "3 -0.093210  0.054093  0.001867 -0.003974 -0.071357 -0.019266 -0.025105   \n",
       "4  0.094629 -0.037051 -0.024952 -0.021575  0.055369  0.107650 -0.008033   \n",
       "\n",
       "          7         8         9  \n",
       "0  0.083779 -0.062457 -0.026213  \n",
       "1 -0.053306 -0.020162 -0.008098  \n",
       "2  0.007953  0.012701  0.001861  \n",
       "3 -0.038207  0.006912 -0.000437  \n",
       "4  0.103943  0.051746 -0.025777  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca = PCA(n_components=10)\n",
    "df_pca = pca.fit_transform(df)\n",
    "df_pca = pd.DataFrame(df_pca)\n",
    "df_pca.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "Sum_of_squared_distances = []\n",
    "K = range(1,10)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters=k)\n",
    "    km = km.fit(df_pca)\n",
    "    Sum_of_squared_distances.append(km.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sGHXr1k21GEGjRo2IiopizZo1lC9f3vbsSsrS20uXLqVgwYK2oJBZLVq0AGDcuHEkJSXdd9odWJ/FKV68OF988QU//fRTqnOLFi1i2bJltueYANuzMQkJCVmqrUOHDri5ubFgwYJU+0nFxsYyYcIE2xiwTlMMCAhg5cqVnDt3zjY2PDw83Z5TjpKZ+rKifPny9OvXjytXrtCnTx/b4h0pLBYLq1evZsaMGeTLl4+xY8emu8aJEyfYunWr7e/R0dHMmjULo9GYahnwlOd57t0L61Hw9PTEbDYTERGR6vj8+fNti3gkJSXZ9RoGg4Fx48ZhMpmYOHFiquX5RURS6BklEZGH8FfLg4N1L6AyZcrc93yBAgXYuHEjv//+O5UrV+bYsWMcP36c2rVr8/LLL9vGTZgwgR49ejB+/Hi++eYbypcvz+nTpzlw4ACFChVKN12oUaNGGI1Grly5kmqJ7dq1a+Pm5kZUVBQtW7bM8t2blI1ljx8/To0aNfjb3/5237Emk4lp06bx2muv8eKLL9K0aVNKlCjBL7/8wqFDhyhevDhvv/22bXzKFL6wsDB+/fXXdHsp/ZUSJUowYsQIJk+eTKdOnWjWrBk+Pj7s3buXS5cu0bZtW9uKdr6+vkycOJE333yTF154wRb4tm/fTkBAwH2nRtojM/VlVUhICAaDgblz59KqVSsaNWpE6dKliYmJ4eDBg5w9e5bSpUvz0Ucf2Z5xu1fevHkZMmQI27Zto3DhwuzevZtLly4xYMAA2x0x+P+f1ahRo6hfv36q96wjtW/fnuPHj9OtWzdat26Nu7s7P/zwAydPnqRAgQLcunWL27dv2/06Tz75JN27d2flypXMnj3btgqhiEgKBSURkYdw+PBh24pb91OxYsUHBqWCBQsyYcIEpkyZwqpVq8ifPz+vvfYaAwcOTLX6VunSpfnyyy+ZN28eu3fv5siRIxQqVIiXXnqJ/v37p1uQISAggMqVK/Pzzz/b7iKBNRhUqlSJEydOZHnaHYDRaKRZs2asWbPmgXeTUtSuXZt169YRFhbGwYMH+de//kWRIkV46aWX6NevX6pFLdq0acOePXvYvXs3q1ev/suNTDPy8ssvU7p0aT7++GPbHk9lypTh9ddfp3PnzqnGNmvWjOXLlzNnzhy2bt2Kt7c3//znP6lSpUqqPXscKTP1ZYXBYCAkJIRmzZqxatUqfvzxR/bu3Yuvry+BgYH07NmT9u3b254fS6t27dq0a9eODz/8kL1791KmTBmmT5+e7k5Xv379CA8P58CBA5w/f/6RBaXu3btjsVhYs2YN69atI0+ePAQGBvL+++/j6enJwIED2bNnDzVq1LD7tQYPHsz27dv59NNPad++far9wkREDJasTvQVERGRHOvy5cs0bdqUpk2bMn/+fGeXIyLicvSMkoiIiIiISBoKSiIiIiIiImkoKImIiIiIiKShZ5RERERERETS0B0lERERERGRNBSURERERERE0lBQEhERERERSUNBSUREREREJA0FJRERERERkTQUlERERERERNJwc3YBuc2dO7GYzc5bcd1kMpA3r4/T68gt1E/HU08dS/10PPXUsdRPx1NPHUv9dDxX6WlKHVmloORgZrMFsznZiRUYXaSO3EL9dDz11LHUT8dTTx1L/XQ89dSx1E/Hc5We2jd5TlPvRERERERE0lBQEhERERERSUNBSUREREREJA0FJRERERERkTQUlERERERERNJQUBIREREREUlDQUlERERERCQNBSUREREREZE0FJRERERERETSUFASERERERFJQ0FJREREREQkDQWlHG7zZjcSE+9/PjHROkZERERERB6eglIOtnmzG6++6k3//l4ZhqXEROjf34tXX/VWWBIRERERyQR9es7BWrdOon37RDZvdgcgLCwOk8l6LiUkbd7sTvv2ibRuneTESkVEREREchYFpRzM3d0ajgBbWFq0KIHERHj9dU82b3ajfftEwsLicHd3ZqUiIiIiIjmLy029S05O5uOPP6Z58+ZUqVKFVq1asWLFCiwWi23MjRs3ePvtt6lbty41a9bkjTfe4Pr166muk5SUxPvvv09wcDBVq1alS5cu/Pjjj+leb9OmTbRt25aqVavSsmVL1q1b98i/R0dKCUspd5b69PGkSxfYtEkhSUREREQkq1zujtLUqVNZsWIFXbt2pXnz5ly6dIkPP/yQK1euMGrUKJKSknjttdeIjY1l/PjxJCUlMWvWLHr37s3GjRtx/18qmDx5Mhs2bGDo0KEULVqUZcuW8eqrr7J+/XoCAwMB2LZtGyNGjODll1+mYcOG7Nq1i9GjR+Pp6Un79u2d2YZMSQlLly8b+fpr64+0bdskhSQRERERkSxyqaAUERHBqlWr+Oc//8m7775rO160aFH69etHly5d+PXXXzl16hRbtmyhXLlyAFSsWJF27dqxdetWOnTowLVr1/j8888ZNWoUPXr0AKBBgwa0bNmSJUuWMHnyZABmz55Ny5YtGTVqFAANGzbkzp07zJkzJ0cFpRS3bhlsf75zx/CAkSIiIiIi8iAuNfXu/PnzmM1mnnnmmVTHn3rqKZKTk9m3bx/79+8nMDDQFpIAypYtS5kyZdi7dy8ABw8eJCkpiRYtWtjGeHh40LhxY/bs2QPA5cuXOX/+fKoxAC1btuTixYucO3fuUX2bDpeycMOFC0YMBusUxf37TfTrl/FqeCIiIiIi8mAudUcpICAAgCtXrqQ6fvHiRcAabsLDwyldunS6ry1ZsqQt3ISHh+Pj40PBggVTjSlVqhR//PEHMTExhIeHA6S7VqlSpQBraEuZopcZJpOB7MyfiYkwYIB14YYOHZIICrLwwQfW+XZffeWO0Whg4cJ4TcHLIuvPM/t/rrmZeupY6qfjqaeOpX46nnrqWOqn47lKT1PqyCqXCkqlS5emZs2azJ07lyJFilCvXj0uXbrEmDFj8PDwIDY2lsjISFuYuZevry8xMTEAREVFkSdPngzHAERHRxMVFQWAn5/ffcdkRd68Pln6uqxITIQePWDTJnjhBfj0UzfMZtiyBX7/HUwm66IOHh5ufPopCkt2yM6f6+NCPXUs9dPx1FPHUj8dTz11LPXT8XJ6T10qKAHMmTOHsWPHEhISAoC/vz/Dhg1j/vz5+Pj4YLFYMBjSp0OLxYLRaE2sycnJ9x0DYDQaSU5OBkg37t4xWXHnTixms+WvBzrApk0m1q3zokOHJObMiScqypqcFyzwoWlTMJuhcOFk1q0z0rp1HB06mLOlrtzEZDKQN69Ptv5cczv11LHUT8dTTx1L/XQ89dSx1E/Hc5WeptSRVS4XlJ544gnmz59PZGQkN27coGTJkhiNRsaPH0/evHnJkydPhnd7YmNjbXeRHjQm5by/vz+Q/s5Rypi0d5oeltlswWxOztLXZla7dsksWWKhdeskjEZrMAIjTZpA166JfPaZO9evG+nXL5527RL/d14yxxqYs/Pnmvupp46lfjqeeupY6qfjqaeOpX46nqv01L5pfy43EfPrr7/m1KlT+Pv7U7ZsWTw8PPj1118xm808+eSTBAYG2p5ZutfFixcpU6YMAEFBQURHRxMREZFqzIULFyhWrBheXl62548uXLiQbgxYF4jICdq3T8pwSt2ECQkEBFjfmOvXu3PnTjYXJiIiIiKSg7lcUAoLC2PRokWpji1fvhx/f3/q1q1LgwYNCA8P58yZM7bzZ86cITw8nPr16wPwj3/8A4Dt27fbxiQkJLB7924aNGgAWBdtKFGiBDt27Ej1Wjt27KB06dIUK1bskXx/2aVAAXj33XgAbtwwMmmSp5MrEhERERHJOUzjx48f7+wi7mUymVi8eDFGoxGz2cyiRYvYsGEDoaGh1KpVi6CgILZt28aGDRt44oknOH36NKGhoRQtWpR33nkHo9GIv78/V65cYenSpXh7e3P79m0mTJjA5cuXmTZtGvny5QOs0+sWLFjArVu3MBqNLFu2jA0bNjBu3LhUy49nxt27ibbnnJzBaDTg7e3B3buJVKxo5ocfTFy8aOTECRPBwUkUK6a5t5lxbz+d+XPNTdRTx1I/HU89dSz10/HUU8dSPx3PVXqaUkdWGSwu+I5YsWIFq1at4o8//iAwMJA+ffrQrl072/lr164xefJkDhw4gLu7O/Xr1yc0NJRChQrZxiQkJDBz5ky2bNlCbGwslSpVYsSIEVStWjXVa3322WcsXbqUa9euUaJECfr27UvHjh2zXHtERIxT52KaTEYCAnxtdZw9a6BxY1/i4gxUqGBm165YPLL+fnnspO2n2E89dSz10/HUU8dSPx1PPXUs9dPxXKWnKXVklUsGpZzMVd4Q99Yxe7YH771nnXo3alQ8gwcnOK2+nMZV/qHnJuqpY6mfjqeeOpb66XjqqWOpn47nKj21Nyi53DNK4ngDBiRQoYJ1ybtZszw4e9a+zbdERERERHI7BaXHgIcHzJwZB0B8vIFhw7zQfUQRERERkftTUHpM1KmTTM+e1il3+/a58fnnLreFloiIiIiIy1BQeoyMHh1PoULWeaLjxnly65am4ImIiIiIZERB6TGSNy+89551b6WICCPjx2tvJRERERGRjCgoPWaefTaJ5s2TAFi71p19+0xOrkhERERExPUoKD1mDAaYOjUOHx/rag7DhnkRF+fkokREREREXIyC0mOoRAkLI0ZYp+CdPWtk9mztQCsiIiIici8FpcfUa68lUrWqdW+lOXM8+O03vRVERERERFLo0/Fjys0NZs2Kw2i0kJhoYMgQT5K1GbWIiIiICKCg9FirVi2Z115LBODwYTdWrXJ3ckUiIiIiIq5BQekxN2JEPMWKWW8lTZjgyfXr2ltJRERERERB6THn52ddBQ8gMtLAmDHaW0lEREREREFJaNnSTLt21il4Gze68+232ltJRERERB5vCkoCwHvvxZMnj3VvpeHDvYiJcXJBIiIiIiJOpKAkABQpYmH0aOveSpcuGZkxQ1PwREREROTxpaAkNj17JlK7tnVvpYUL3fn3v/X2EBEREZHHkz4Ji43RaN1byc3NgtlsYMgQL8xmZ1clIiIiIpL9FJQklYoVkxk4MAGA48dNLF2qvZVERERE5PGjoCTpvP12AqVLW/dWeu89T65c0d5KIiIiIvJ4UVCSdLy9YcYM695KMTEGQkM9sVicXJSIiIiISDZSUJIMBQeb6dzZurfS9u3ufP21m5MrEhERERHJPgpKcl8TJsSTP7/1VtKoUZ5ERjq5IBERERGRbKKgJPf1xBMWxo+3TsH773+NvPee9lYSERERkceDgpI8UNeuSdSvnwTAsmXuHD2qt4yIiIiI5H761CsPZDBYF3bw8LBgsVj3VkpMdHZVIiIiIiKPloKS/KWyZS0MHmzdW+nXX02EhXk4uSIRERERkUdLQUkeyqBBCZQrZwZg1iwPzp/X3koiIiIiknspKMlD8fSEWbPiAbh718Dw4V7aW0lEREREci0FJXlo9eqZefFF6xS83bvdWL9eeyuJiIiISO6koCSZMnZsPE88kQzAmDGe/PmnkwsSEREREXkEFJQkU/Llg8mTrVPwbt40MmGC9lYSERERkdxHQUkyrWPHJJo0se6t9OmnHhw8aHJyRSIiIiIijqWgJJlmMMC0aXF4e1tXcxgyxJP4eCcXJSIiIiLiQApKkiWlSlkYNsyajs6cMfHRR9pbSURERERyDwUlybLXX0+kUiXr3koffujB77/r7SQiIiIiuYM+2UqWubvDrFlxGAwWEhIMDBvmqb2VRERERCRXUFASu9SsmUyfPokAfP+9G2vWaG8lEREREcn5FJTEbqGh8fztb9a9lcaP9+KPPwxOrkhERERExD4KSmK3PHlgyhTrwg63bxsYM0Z7K4mIiIhIzqagJA7Rpk0SrVtbp+CtX+/Od99pbyURERERybkUlMRhpkyJx8/PuprD8OFexMY6uSARERERkSxSUBKHKVrUwqhR1il4Fy8amTVLeyuJiIiISM6koCQO9coridSsad1baf58D06e1FtMRERERHIefYoVhzKZYObMOEwmC2azgaFDvTCbnV2ViIiIiEjmKCiJw1WunEy/ftaFHX780cTy5e5OrkhERERSWUXdAAAgAElEQVREJHMUlOSRGDo0npIlrXsrTZ7sybVr2ltJRERERHIOBSV5JHx9Yfr0OACiow2MGqW9lUREREQk51BQkkemSRMznTpZp+B9/bU727drbyURERERyRkUlOSRmjgxnrx5rXsrjRzpRXS0kwsSEREREXkICkrySBUqZGHcOOveSlevGpk6VVPwRERERMT1KSjJI9e9eyL16iUBsGSJO8eP620nIiIiIq5Nn1jlkTMaYebMeNzdLSQnG3j7bS+SkpxdlYiIiIjI/SkoSbb4+9+TeeONBAB++cXEokXaW0lEREREXJeCkmSbN99MoEwZ695K06d7cvGi9lYSEREREdekoCTZxssLZs607q0UG2tg5EgvLBYnFyUiIiIikgEFJclW9eub6dbNurfSrl1ubN7s5uSKRERERETSU1CSbDduXBwFClin4I0a5cnt204uSEREREQkDQUlyXYBATBhgnVvpT/+MDJxovZWEhERERHXoqAkTtG5cxLBwdY1wleu9ODQIZOTKxIRERER+X8KSuIUBgNMnx6Hl5d1NYdhwzxJSHByUSIiIiIi/6OgJE4TGGhhyBBrOvrtNxNz53o4uSIRERERESsFJXGqAQMSqFjRDMAHH3gQHq69lURERETE+RSUxKnc3a17KxkMFuLjDQwbpr2VRERERMT5FJTE6Z56KpmePa17K+3f78batdpbSUREREScS0FJXMLo0fEULmzdW2n8eE9u3dIUPBERERFxHgUlcQn+/vDee9a9lSIijIwbp72VRERERMR5FJTEZbRrl0TLlta9lT7/3J29e7W3koiIiIg4h4KSuAyDAaZMicPHJ2VvJS/u3nVyUSIiIiLyWFJQEpdSvLiF0FDrFLxz54zMnq29lUREREQk+ykoict59dVEqlWz7q00Z44Hp07pbSoiIiIi2UufQMXlmEwwa1YcRqOFpCQDQ4Z4kZzs7KpERERE5HHikkHp888/p23btlSvXp3WrVvz6aefYrlnF9KzZ8/St29fatWqRd26dRk1ahSRkZGprhEdHc3YsWOpX78+1atX55VXXuHMmTPpXmvZsmU0a9aMKlWq0KFDB3bt2vXIvz/5a1WrJtO3r3VvpSNHTKxc6e7kikRERETkceJyQWndunWMGTOGp59+mrCwMFq1asXEiRNZunQpAJGRkfTq1YuIiAimT5/OkCFD2LlzJ4MHD051nZTjQ4YMYfr06dy6dYuePXty+/Zt25glS5YwY8YMOnXqxNy5cylVqhRvvPEGR44cydbvWTI2fHg8xYtbbyVNnOjJ9evaW0lEREREsoebswtI68svv6RmzZqMHj0agKeffprz58/z6aef0qdPH9asWUNkZCQbN24kICAAgMKFC9O3b1+OHj1K7dq1+emnn9i9ezeLFi0iODgYgNq1a9O0aVNWr17NgAEDiIuLY+HChfTq1YuBAwcC0KhRI7p27cq8efNYvny5U75/+X9+fjBtWhw9evgQGWlg9GhPFi+Oc3ZZIiIiIvIYcLk7SgkJCeTJkyfVsfz589vuBO3fv59atWrZQhJAw4YN8fX1Ze/evbYxPj4+1K9f3zYmICCAp556yjbmxIkTREZG0qJFC9sYg8FA8+bNOXz4MHFx+kDuCpo3N9O+vXUK3qZN7uzcqb2VREREROTRc7mg1LNnTw4cOMCmTZuIiopi3759bNiwgQ4dOgAQHh5OYGBgqq8xGo0UL16c8+fP28YUL14cN7fUN8xKlizJuXPnbGMASpcunWpMqVKlMJvNXLx48RF8d5IVkyfH4+9vfUZtxAgvoqOdXJCIiIiI5HouN/WudevWHDp0iOHDh9uONWjQgFGjRgHWZ5R8fX3TfZ2vry/R//sEHRUVhZ+fX4ZjYmJibGOAdONSrh2dxU/jJpMBZ+ZP6+s7vw5HKloUxo5NYOhQTy5fNjJzphcTJyZky2vnxn46m3rqWOqn46mnjqV+Op566ljqp+O5Sk9T6sgqlwtK/fv359ixYwwbNoyqVavy22+/MXfuXN58803mzZsHWKfIpWWxWGzHk5OTMxwD1rtPKWMykrK6Xsq4zMqb1ydLX+dorlKHo7z1FqxfD99/DwsWuNOnjzs1a2bf6+e2froC9dSx1E/HU08dS/10PPXUsdRPx8vpPXWpoHTs2DH279/PpEmTeOGFFwCoU6cOJUqU4PXXX2f37t34+flleLcnNjaWIkWKAJAnTx5u3bqVbkxMTIzt+Sd/f3/bsbx586a6Tso1suLOnVjMZstfD3xETCYDefP6OL2OR2H6dAONG3uTlGSgd28z33wTh9sjfgfn5n46i3rqWOqn46mnjqV+Op566ljqp+O5Sk9T6sgqlwpKV69eBaBmmlsFTz31FAC///47gYGB6Z4fSk5O5vLly7aFGQIDA9m/fz/Jycmp7gxdvHiRoKAg2xiACxcuULVqVduYCxcu4OHhQYkSJbL0PZjNFsxmZ+6OanSROhzv73+HkJAEZs/25MQJE4sWmXj99cRH/Kq5t5/Oo546lvrpeOqpY6mfjqeeOpb66Xiu0lP7pv251ETMlBBz9OjRVMePHTsGQPHixalfvz5HjhwhIiLCdn7fvn3ExMTYVrlr0KABMTEx7Nu3zzYmIiKCI0eO0KBBAwBq1KiBj48PO3bssI2xWCzs3LmTOnXq4OHh8Wi+SbHLW28lEBho/Qc3ZYonly9rbyURERERcTyXuqP05JNP0rJlS6ZOncqdO3eoVq0aZ86cYc6cOVSqVInmzZsTFRXFqlWreOWVVwgJCeH27dvMmDGDRo0aUaNGDcB6B6pOnToMGzaMYcOGkS9fPubMmUOePHno2rUrAN7e3vTu3Zt58+bh7u5OjRo1+PLLLzl58iQrVqxwZhvkAby9YcaMODp39iE21kBoqBeffHKX+zySJiIiIiKSJQZLyuoFLiIhIYGwsDA2bdrEjRs3KFq0KM2aNWPgwIG2FelOnz7Ne++9x08//YSvry/NmjVj+PDhqVawu3PnDlOnTmXXrl0kJydTs2ZNQkNDbXetwHoHKSwsjM8//5yIiAjKli3L4MGDadSoUZbrj4iIceotRpPJSECAr9PreNQGDvRi3Tp3AD7++C7PPpv0SF7ncelndlJPHUv9dDz11LHUT8dTTx1L/XQ8V+lpSh1Z5XJBKadzlTeEs+t41G7eNNCggQ8REUYKF07mwIEY/rc+h0M9Lv3MTuqpY6mfjqeeOpb66XjqqWOpn47nKj21Nyi51DNKIg/riScsjB8fD8D160YmT/Z0ckUiIiIikpsoKEmO1aVLEg0bWqfcLV/uzpEjejuLiIiIiGPok6XkWAaDdWEHT08LFouBoUO9SHzUq4WLiIiIyGNBQUlytKAgC2+9lQDAr7+aCAvTsu4iIiIiYj8FJcnxQkISKF/eDMDMmR6cO6e1wkVERETEPgpKkuN5eMCMGdaFHeLiDAwf7oXWchQREREReygoSa5Qr56Zl16yTsHbs8eNL790qb2URURERCSHUVCSXGPMmHgKFrSu1T92rCd//unkgkREREQkx1JQklwjXz6YPNk6Be/mTSPvvqu9lUREREQka+wOStHR0Vy/fh2AhIQElixZwqRJkzhy5IjdxYlkVocOSTRtat1bafVqDw4cMDm5IhERERHJiewKSj///DNNmjRh5cqVAEyaNImZM2eyefNmevbsybfffuuQIkUelsEA06bF4eNjXc1h6FAv4uKcXJSIiIiI5Dh2BaUPPviAoKAgunTpQlxcHF999RXdu3fn8OHDdO7cmQULFjiqTpGHVrKkhWHDrFPwwsONfPih9lYSERERkcyxKyidOHGC/v37U6JECQ4ePEhcXBwdOnQAoE2bNvz+++8OKVIks15/PZHKla17K330kQenT+txPBERERF5eHZ9ejQajXh4WH9bv2fPHvz9/alatSpgfXbJy8vL/gpFssDNDWbNisNotJCYaGDoUE+Sk51dlYiIiIjkFHYFpcqVK/PFF1/w008/sW3bNho3bozBYODWrVssXryYypUrO6pOkUyrUSOZPn0SATh0yI3Vq92dXJGIiIiI5BR2BaXhw4dz8OBBunXrhslkon///gC0a9eO8+fPM3jwYIcUKZJVoaHxFC1qvZX07rue3LhhcHJFIiIiIpITuNnzxU8++STffPMN4eHhlCtXDh8fHwDGjx9PzZo1KViwoEOKFMkqPz+YOjWOl1/24c4dA2PHerJggZbBExEREZEHs/sJdz8/P6pUqcLFixfZu3cv0dHR1K1bVyFJXEarVmbatrVOwVu/3p3vvtPeSiIiIiLyYHYHpU2bNtG4cWM6duxIv379uHDhAiNHjmTQoEEkJCQ4okYRu733Xjx+fta9lYYP9yI21skFiYiIiIhLsysobd26lREjRlCvXj0++OADkv+3rFiLFi3Yu3cv8+fPd0iRIvb6298svPOOdW+lixeNzJypvZVERERE5P7sCkoLFiyga9euTJ8+nRYtWtiOP/fcc4SEhPD111/bXaCIo/TqlUitWta9lcLCPPjlF+2tJCIiIiIZs+uT4rlz52jevHmG56pVq8b169ftubyIQ5lMMHNmHG5uFsxmA0OHemE2O7sqEREREXFFdgWlAgUKEB4enuG58PBwChQoYM/lRRyuUqVk+ve3Pjt37JiJ5cu1t5KIiIiIpGdXUGrTpg0fffQR27dvty3cYDAY+OWXX5g/fz6tWrVySJEijjRkSAIlS1qfp5s82ZNr17S3koiIiIikZldQGjx4MNWrV2fw4MHUqlULgJdeeokXXniB0qVL8+abbzqkSBFH8vGBGTOseylFRxsIDfV0ckUiIiIi4mrs2nDWw8ODJUuW8P3333Pw4EFu375Nnjx5qFOnDsHBwRgM+k29uKZnnjHz3HOJrF/vztat7mzblkTr1knOLktEREREXIRdQQng9u3bJCQkMGTIEAAuXbrEv/71L6KiovD397e7QJFHZeLEeL77zo3bt613lRo2TMLPz9lViYiIiIgrsGvq3ZkzZ2jXrh0TJkywHbty5QozZszgueee4/Lly3YXKPKoFCxoYdw4695KV68amTJFU/BERERExMquoDR9+nSKFSvG2rVrbcfq1avHnj17eOKJJ5gxY4bdBYo8St27J/L009Ypd0uWuHPsmPZWEhERERE7g9Lx48cZOHAgBQsWTHU8ICCA119/nR9++MGu4kQeNYMBZs6Mx8PDgsViYMgQLxITnV2ViIiIiDibXUHJYDAQExOT4bmEhAQS9YlTcoBy5ZJ54w3r8vYnT5pYuFB7K4mIiIg87uwKSnXr1mX+/PlERESkOh4REcGCBQuoW7euXcWJZJc330ygbFkzADNmeHLhglZsFBEREXmc2bXq3bBhw+jcuTNNmzalevXqBAQE8Oeff/LTTz/h6enJ+++/76g6RR4pT0/rFLyOHX24e9fAiBFerFlz19lliYiIiIiT2HVHqUSJEmzZsoWuXbsSGxvLL7/8QmRkJF26dGHjxo0EBgY6qk6RR+4f/zDToIF1uuh337mxcWP63yMkJsLmzXavqi8iIiIiLs7uT3wFCxZkxIgRjqhFxKk2b3Zj/353PDwsJCQYeOcdT5o1u0tAgPV8YiL07+/F5s3uLFlyl/bttUGtiIiISG5ld1CKiori0KFDxMbGYrFY0p3v2LGjvS8hki1at06ifftENm+2LuZw86aRd9/1YMWK1CGpfftEWrdWSBIRERHJzewKSnv27GHw4MHcvZvxsxwGg0FBSXIMd3cIC4sDsIWlTz5xp1cv+PBDTzZvdqN9+0TCwuJw18J4IiIiIrmaXUHp/fffJygoiNDQUAoXLozRqM06JWdLCUsxMfDtt9Y01KEDREUpJImIiIg8TuwKSmfPnmX+/PnUrl3bUfWIOJ27O3zySRxNmhj57TcTUVGQL5+FCRPiFZJEREREHhN23QIqWrQo0dHRjqpFxKUEBSXb/nz7toFnn/Xht99011RERETkcWDXp77XX3+defPmcfnyZUfVI+J0KQs3bNvmTuvWSZQsaT1+6ZKRNm182LPH5NwCRUREROSRs2vq3VdffcX169dp3rw5AQEBeHl5pTpvMBjYtWuXXQWKZKe0q9stWpRA/vxuVKtm5tQpE1FRBrp08WbGjHheeinR2eWKiIiIyCNiV1AqUqQIRYoUcVQtIk6VNiRZF24w4uEBu3fH0batJz/+6EZysoEhQ7w4e9bImDHxaA0TERERkdzHrqA0ZcoUR9Uh4nTbtrmlCUn/f87dHTZvvkuXLt7s32/9ZzNvngfnzhmYPz8OHx8nFS0iIiIij4RDfhd+8+ZNrl27xtWrV7l69SqXL1/m999/Z82aNY64vEi2aN8+iSVL7t53CXB3d1i79i5Tptzl7383A7B1qzsdO/pw/bohm6sVERERkUfJrjtKp06d4u233+bcuXMZnjcYDHTr1s2elxDJVu3bJz3wvLs79OmTROfOSfTp483evW4cP26iVSsfVq26S6VKyQ/8ehERERHJGey6ozR9+nQiIyMZMWIEderUoUGDBowZM4bg4GAMBgOffPKJo+oUcSl588KaNXd56aUEAK5cMdKunQ+7dmlFPBEREZHcwK6gdOLECd5880169epF27ZtiY2NpXv37ixYsIBmzZqxcuVKR9Up4nLc3WHmzHjGjYvDYLAQE2PgxRe9+fhj7UorIiIiktPZFZQSEhIIDAwEICgoiN9++8127rnnnuP48eP2VSfi4gwGGDgwkaVL4/D2tpCcbCA01It33vHEbHZ2dSIiIiKSVXYFpaJFi3Lp0iUASpUqRXR0tG3zWQ8PD+7cuWN/hSI5QNu2SWzaFEuhQtZnlBYv9uDll72JjnZyYSIiIiKSJXYFpRYtWjBz5ky2b99OwYIFCQoK4oMPPuC3335j6dKllChRwlF1iri86tWT2b49looVrbeSdu5049lnfbh6VSviiYiIiOQ0dgWlkJAQatWqxZdffglAaGgou3btomPHjhw6dIhBgwY5pEiRnKJ4cQtbtsTStKl19byTJ020bOnDiRPalVZEREQkJ7FreXBPT08++ugjEhMTAWjYsCFbtmzhl19+oVKlSpQsWdIhRYrkJHnywMqVdxk92pOlSz24ft1Ihw4+hIXF0br1g5cfFxERERHXYNevuUNDQ7l06RLu9+zOWaJECVq3bk1SUhL9+vWzu0CRnMjNDaZOjWfy5DiMRguxsQZ69fJiwQJ3LBZnVyciIiIifyXTd5SuXr1q+/PGjRtp1qwZJlP6vWP27t3L999/b191Ijnca68lUqpUMn37ehMba2DsWC/Cw41MmRKPm133c0VERETkUcr0R7UJEyawZ88e299DQkIyHGexWKhfv37WKxPJJVq0MPPVV7G8+KI3164ZWbHCgwsXjCxZchd/f2dXJyIiIiIZyXRQevfdd/n++++xWCyMGjWK/v37p3sWyWg04u/vT926dR1WqEhOVqVKMjt2WMPSzz+b2L3bjXbtfFi16i4lS2ounoiIiIiryXRQKly4MJ06dQLAYDDQuHFj8ufP7/DCRHKbIkUsbNoUS//+Xmzf7s6pUyZatfJh5cq71KqV7OzyREREROQedi3m0KlTJ6Kjozlz5gwAkZGRvPvuu/Tr14+NGzc6pECR3MTXF5Yti6NfvwQAbt400qmTD199pQeWRERERFyJXUFp7969tG7d2raP0rhx4/j888+5fv06oaGhrFu3ziFFiuQmJhNMmBDP9OlxmEwW4uIM9OnjzUcfeWhFPBEREREXYVdQmj9/Pg0aNGDgwIFERUWxc+dO+vbty4YNG+jbty+ffPKJo+oUyXV69Upk9eq75MljTUeTJnny1lueJCQ4uTARERERsS8onTp1ip49e+Ln58e+ffswm820bNkSgPr163PhwgWHFCmSWz3zjJktW2IpUcL6jNLq1R507erN7dtOLkxERETkMWdXUPL09CQpKQmAffv2UaBAASpUqADAzZs38dfaxyJ/qWLFZLZujaVmTTMA+/e70aaND+fOGZxcmYiIiMjjy66gVKtWLZYuXcqWLVvYtm0bLVq0AOCXX35h7ty51KxZ0yFFiuR2hQtbWL8+lmefTQTgzBkTrVv7cOhQ+s2cRUREROTRsysohYaGcv36dYYOHUrx4sXp378/AK+//joJCQkMHTrUIUWKPA58fGDx4jjeeCMegIgII507e/Pll1oRT0RERCS72fUJrESJEnz99dfcunWLJ554wnZ83rx5PPnkk3h4eNhdoMjjxGiE0aMTCApKZuhQLxISDPTv783Zs/EMHZqAQbPxRERERLKFXXeUwLrp7L0hCaB69eoKSSJ26N49ic8/v0vevNYV8WbM8GTgQC/i451cmIiIiMhjItN3lCpWrMjatWupWrUqFSpUwPCAX3EbDAb+85//2FWgyOOqQQMzW7fG0r27NxcuGPniC3cuXTKwfHkcBQpowyURERGRRynTQWngwIEULlzY9ucHBSURsU+5csls3x5Lz55eHD7sxg8/uNG6tQ+rV8dStqzCkoiIiMijkumgFBISYvvzoEGDHFqMiKRXoICFL764y+DBXqxf787580batPFl2bK71K9vdnZ5IiIiIrlSpoPS1atXMzW+aNGimX0JEUnDywvCwuIICkpm5kxPbt828M9/ejNrVhxduyY5uzwRERGRXCfTQalJkyaZmm7366+/ZvYlRCQDBgMMH25dEW/wYOuKeG+8YV0Rb+TIBIx2L80iIiIiIikyHZTee+89W1C6c+cOM2fO5Omnn6Z169YULFiQ27dv891337F7925Gjhzp8IJFHnedOydRvPhdevXyIiLCyOzZnpw7Z+Sjj+Lw9nZ2dSIiIiK5Q6aD0nPPPWf788CBA+nUqRMTJ05MNebZZ59l8uTJbNu2jS5dujz0tX/44Qdefvnl+54fNGgQISEhnD17lqlTp/Ljjz/i5uZG06ZNGTlyJP7+/rax0dHRTJ8+nW+//ZaYmBhq1KjBO++8Q9myZVNdc9myZXz66adcv36doKAgBg0aRLNmzR66ZhFnqFfPuiJejx4+hIcb2bTJncuXjaxYcZdChbTIg4iIiIi97Jqsc+DAAVq1apXhucaNG/PTTz9l6nqVKlVi7dq16f57+umn8fPzo23btkRGRtKrVy8iIiKYPn06Q4YMYefOnQwePDjVtVKODxkyhOnTp3Pr1i169uzJ7du3bWOWLFnCjBkz6NSpE3PnzqVUqVK88cYbHDlyJPPNEMlmQUEWtm6NoX596zNKP/5ook0bH06d0hw8EREREXtl+o7SvfLnz8/x48epX79+unOHDh2yLSP+sPz8/KhevXqqY7t27eLgwYN8+OGHBAYGsnDhQiIjI9m4cSMBAQEAFC5cmL59+3L06FFq167NTz/9xO7du1m0aBHBwcEA1K5dm6ZNm7J69WoGDBhAXFwcCxcupFevXgwcOBCARo0a0bVrV+bNm8fy5cuz0BGR7JU/P6xde5chQ7xYu9adixeNtG3rw8cf36VxY62IJyIiIpJVdv3q+YUXXiAsLIyZM2dy7Ngxzp8/z9GjR5k0aRJLly6lZ8+edhUXFxfHpEmTaNy4se3O1f79+6lVq5YtJAE0bNgQX19f9u7daxvj4+OTKsAFBATw1FNP2cacOHGCyMhIWrRoYRtjMBho3rw5hw8fJi4uzq7aRbKLhwd89FEco0bFAxAVZaBbN28++cTdyZWJiIiI5Fx23VHq378/UVFRLF++nI8//hgAi8WCl5cXb775Jj169LCruOXLl3Pjxg1WrFhhOxYeHk6bNm1SjTMajRQvXpzz58/bxhQvXhw3t9TfXsmSJfnqq69sYwBKly6dakypUqUwm81cvHiRv//973bVL5JdDAYYPDiBwMBkQkK8iI83MHSoF+HhRsaOjcdkcnaFIiIiIjmLXUHJYDAwYsQIBgwYwPHjx7lz5w758+enRo0a+Pj4pBp79epVChUqlC683E9CQgIrV66kTZs2lCpVynY8MjISX1/fdON9fX2Jjo4GICoqCj8/vwzHxMTE2MYA6calXDvlWpllMhmw80adXayv7/w6couc1s/nnkumRIk4XnzRi5s3DYSFeXDhgpEFC+LJ4J+NU+S0nro69dPx1FPHUj8dTz11LPXT8Vylpyl1ZJVdQSlFnjx5aNiw4X3Pm81mmjZtyhdffEGlSpUe6prbt2/n5s2bvPrqq+nOZbSPk8VisR1PTk6+715Pxv9tNpOcnJzheYvFkmpcZuXN6/PXg7KBq9SRW+SkfrZsCYcPQ7t28J//wNatbnTq5MbmzeBK+z/npJ7mBOqn46mnjqV+Op566ljqp+Pl9J46JCg9jJQA8rB27NhBuXLlqFChQqrjfn5+Gd7tiY2NpUiRIoA1uN26dSvdmJiYGPLkyQNgW0o8JiaGvHnzprpOyjWy4s6dWMxm5y3PbDIZyJvXx+l15BY5tZ9588KWLdC7txe7d5v48Ud46qlk1qyJp3LljH9JkF1yak9dlfrpeOqpY6mfjqeeOpb66Xiu0tOUOrIq24JSZiQmJnLgwIEM7yYFBgZy8eLFVMeSk5O5fPmybWGGwMBA9u/fT3Jycqo7QxcvXiQoKMg2BuDChQtUrVrVNubChQt4eHhQokSJLNVuNlswm535QdToInXkFjm3n35+8OmnsYwc6cnKlR5cvWqkTRsvFi++S7NmzlwRL+f21DWpn46nnjqW+ul46qljqZ+O5yo9tW/an0tOxDx9+jR3796lVq1a6c7Vr1+fI0eOEBERYTu2b98+YmJibKvcNWjQgJiYGPbt22cbExERwZEjR2jQoAGA7TmqHTt22MZYLBZ27txJnTp18PDweFTfnki2cXeHmTPjGT8+DoPBQkyMgRdf9Objj7UinoiIiMiDuOQdpdOnTwNQpkyZdOe6d+/OqlWreOWVVzEch/8AACAASURBVAgJCeH27dvMmDGDRo0aUaNGDQCeeuop6tSpw7Bhwxg2bBj58uVjzpw55MmTh65duwLg7e1N7969mTdvHu7u7tSoUYMvv/ySkydPplplTySnMxhgwIBESpe2MGCAF7GxBkJDrSviTZyoFfFEREREMuKSQenmzZsAqZ4dShEQEMAnn3zCe++9x9ChQ/H19aVVq1YMHz481bi5c+cydepUpk+fTnJyMjVr1mT27NmprhkSEoLJZOLzzz9n6dKllC1blvnz52d4J0v+j707j7O57v8//vicbebMjG0SXdYsdeVHImvGlkQTjRYtSL4uE1GppKso0UIiouxEpauyFWOt7EtEKVpQVIgucmFwzpmz//44GYkWcz6cMzPP++3mdruc+cznvM7rOpl5ns/7/fpIfnfjjQHmzXPTqZOTgwctTJkSmYg3caKHswyJFBERESnUjPC5TlnIg2AwSPXq1ZkzZ87fnnqXXx0+7IrpWkyr1UJqanLM6ygoCmI/9+0z6NTJyTffRC4lVa8e5K23PJQte2E2WxbEnsaS+mk+9dRc6qf51FNzqZ/mi5eenqwjr+Jyj5KInD9ly4ZZsMDNddcFAPj6ays33JDEli3650BERETkJP1mJFIIpaTA9OkeunXzAXDggIV27ZJYtCguV+OKiIiIXHAXJChZLBZuueUWSpQocSGeTkT+BpsNXnjBy5AhOVgsYdxug65dExk3zs75X5ArIiIiEt/O+ePjuXPnntPxN998M4Zh8MILL5zrU4nIBZCZ6adixRDduztxuQwGDUrk++8tvPCCF7umiIuIiEghdc5B6Yknnjjt74ZhAJF7EP3+MYgEJRGJb9dfH2T+fDd33+1k/34Lb74ZmYj32mseihaNdXUiIiIiF945L71btmxZ7p8xY8bgdDrp06cPS5cuZevWraxatYqnn36aEiVKMGHChPNRs4icBzVqhFiyxE3NmkEAVq2y0aZNEnv2GH/xnSIiIiIFzzkHpbJly+b+GTduHD179uTee++lXLlyOBwOSpcuTYcOHbjvvvsYPnz4+ahZRM6TSy4JM2+emxtu8AOwY0dkIt6nn2rui4iIiBQuUf32s2vXLqpVq3bWr1WqVImffvopmtOLSAwkJ8O0aTn07BmZiHfokIVbb01i3jxNxBMREZHCI6qgdOmllzJv3ryzfm3GjBlcfvnl0ZxeRGLEaoVnnvEyfHgOVmuYnByDe+91MmqUQxPxREREpFCI6iPi+++/n4ceeogff/yR6667jtTUVA4dOsSHH37Izp07mTx5sll1ikgMdOnip0KFEJmZTo4fNxgyJIEffrAwfHgODkesqxMRERE5f6IKSq1atWLs2LGMHTuW0aNHEw6HsVgs1K5dm9dff526deuaVaeIxMi11wZZuNBNp05O9u618M47dvbsMZg61YNujSYiIiIFVdSbDlq0aEGLFi3wer1kZ2dTvHhxHPqoWaRAueKKEIsXu+nSxclnn1lZt87GjTcm85//uKlcWWvxREREpOAxZZTVrl27mDFjBtOnT+fIkSN8+umnnDhxwoxTi0icKFUqzHvvucnIiEzE27XLwo03JrFhgzXGlYmIiIiYL6orSsFgkIEDBzJnzhzC4TCGYXDDDTcwduxY9u7dy1tvvcUll1xiVq0iEmNOJ0yalEOlSiFGj07g8GEL7ds7GTUqh/btA7EuT0RERMQ0UV1RGj9+PPPnz+f5559n3bp1hH8dh/X4448TCoV4+eWXTSlSROKHxQJPPulj9GgPNlsYn8+gVy8nw4ZpIp6IiIgUHFEFpTlz5tC7d29uu+02ihcvnvv4FVdcQe/evVm3bl3UBYpIfOrQIcDMmR6KFYuko5deSqBnz0RycmJcmIiIiIgJogpKhw4d+sMbzpYuXZpjx45Fc3oRiXONGwdZvNjFpZeGAHjvPTvt2zs5dMiIcWUiIiIi0YkqKFWsWJFVq1ad9WsbN26kYsWK0ZxeRPKBqlXDLF7spn79yB6ljRttpKcn8d13psyKEREREYmJqH6T6dKlC2+++SbPPvssH3/8MYZhsHv3bqZOncrUqVPp2LGjWXWKSBy76KIwc+Z4uO22yES83bsjE/HWrNFEPBEREcmfopp6d/vtt3P48GEmTJjAO++8Qzgcpk+fPtjtdjIzM+nQoYNZdYpInEtIgHHjcqhcOcTw4QlkZxvceaeTu+/2MXiwD7v97N/n98PixTYyMjQ1T0REROJHVEEpOzubHj160KlTJz7//HOOHj1K0aJFueqqq04b7iAihYNhwGOP+ahUKcTDDyfi8xm8/noCa9faWLHCTULC6cf7/dCzZyJZWXamTPEoLImIiEjciGrp3e23386iRYtISUmhSZMm3HTTTTRr1kwhSaSQa98+wOzZHkqUiAx52LnTSv36yfx2vstvQ1JGhp/0dIUkERERiR9RBaXs7GxKlChhVi0iUoA0bBhk8WI3lStHwtLPP1uoWzeZffsiIalHj4TckDR+fM4fLs0TERERiYWogtI999zDsGHD2LBhA4cPHzarJhEpICpXDrN4sYtrrolcLTp61EKDBkmkp8O8eTaFJBEREYlbUe1RmjdvHvv376dr165n/bphGHzzzTfRPIWI5HMlSsCsWR769Elk5kw7Ho/BsmVQvXqQceMUkkRERCQ+RRWUMjIyzKpDRAowhwNGjsxhyxYLO3ZERoZ//bWVzp2dvPJKDqVLh2NcoYiIiMjpogpKDzzwgFl1iEgB5vdDr16J7NhhpWHDIFu2WPF4YMUKG82aJTFqVA433BCMdZkiIiIiuaIKSgA5OTns2LEDv99POBz5VDgUCuHxePj000/p27dv1EWKSP71++l2kyb5sFiSufrqED/9ZOHwYQv33JNE584+nn3WS3JyrCsWERERiTIobdiwgYceeohjv535+xvJyckKSiKF2O9DUmRwg4XUVPj0Uw833pjA5s2Rf4amT3ewbp2N8eM91K4dinHlIiIiUthFNfVu1KhRFC9enFdeeYWWLVvSqlUrJkyYQMeOHTEMg8mTJ5tVp4jkQ4sX2/5wBLjdDvPne2jZ0p/72PffW2jTJomXX3YQ1Eo8ERERiaGogtKOHTt48MEHuf7662nRogX79++nWbNmDBgwgPbt2zN+/Hiz6hSRfCgjI8CUKZ4/HAFut8Mbb+QwaZKHp57yYreHCQQMXnghgXbtnOzebVz4okVERESIMiiFQiEuueQSACpVqsTOnTtzv9a6dWuNBhcRMjICfzoC3G6Hm28O0Lu3j8WL3Vx2WeRS0saNNq69NpkZM2yENRRPRERELrCoglKFChXYsWMHABUrVsTj8bBr1y4AAoEALpcr+gpFpNCoWTPERx+56drVB8CJEwYPPuike/dEjhyJcXEiIiJSqEQVlG666SZeeuklpk+fTokSJahRowbPP/88y5cvZ+zYsVStWtWsOkWkkEhKghdf9PL2225KlowMdZg3z07z5smsWWONcXUiIiJSWEQVlDIzM7nrrrvYunUrAAMHDmTbtm306tWL77//nn//+9+mFCkihU/LlkFWrXLTunUAgJ9/tnDbbUkMHJiA1xvj4kRERKTAM8Jhc1f/nzhxgu+//57KlSuTkpJi5qnzhcOHXQSDsRttbLVaSE1NjnkdBYX6ab5z7Wk4DG++aefppxPweCLDHf7f/wsyfnwO1arp/xO9R82nnppL/TSfemou9dN88dLTk3XkVVRXlM4mJSWFmjVrFsqQJCLmMwzo0sXPsmUuatWKDHr45hsrrVolMWmSnZB+pomIiMh5ENUNZ1u0aIFh/Pn43mXLlkXzFCIiAFStGmbhQjcvveRg9GgHXq/BU08lsnSpjVdeyeGSSzQaT0RERMwTVVCqX7/+GUHJ5XLx5Zdf4vV66dKlS1TFiYj8lt0O/fr5uPbaIA88kMiePRZWrrTRvHkSI0Z4adMmEOsSRUREpICIKigNHTr0rI/7/X4eeOABPB5PNKcXETmrhg2DLF/uon//RGbOtHP4sIWuXZ107Ojj+ee9aOWviIiIRMv0PUoAdrudzp07M3v27PNxehERihaFMWNymDzZQ7FikWV3b7/toEWLZD799Lz80yYiIiKFyHn7beLIkSO64ayInHft2gVYtcpFkyaRZXc//mjhppuSGD7cQUAr8URERCSPolp6N3fu3DMeCwaD/Pzzz7z11lvUrVs3mtOLiPwtZcqEmTXLw4QJdoYMScDnMxg+PIHly22MG+ehUiUNehAREZFzE1VQeuKJJ/7wa7Vr12bAgAHRnF5E5G+zWKBXLz9Nmwbp2TORHTusfPaZlRYtkhkyJIe77grwF0M6RURERHJFFZTONvrbMAxSUlIoWrRoNKcWEcmTGjVCfPihm+efT2DyZAcul8FDDzn58EM/I0bkkJoa6wpFREQkP4gqKJUtW9asOkRETON0wuDBXq67LkDv3okcPGhh4UI7n35q5dVXc2jePBjrEkVERCTORRWUxowZ87ePNQyD+++/P5qnExE5Jy1aBFm1yk2fPgksXmznwAELd9yRRI8ePp580ktiYqwrFBERkXgVVVDKysri0KFDuN1ubDYbF110EdnZ2eTk5GAYBuHwqQ3UCkoiEgsXXRTm9ddzePvtIE8+mYDbbTBxooPVq62MG5dD9eqhWJcoIiIicSiq8eBPPPEEdrud4cOHs2XLFlatWsUXX3zB1KlTKVmyJCNGjGD79u1s376dbdu2mVWziMg5MQzo1MnP8uUurr46suxu2zYrrVsnMX68nZCykoiIiPxOVEHppZdeonfv3tx0001Yrdbcxxs1asQjjzzCqFGjoi5QRMQslSuHmT/fzaOPerFYwvh8BgMHJnL77U7279dIPBERETklqqC0f/9+ypUrd9avFS9enF9++SWa04uImM5uh8cf9zF/vpuKFSOXktassdG8eTJZWVGtRhYREZECJKqgdMUVVzB9+nT8fv9pj+fk5DB58mRq164dVXEiIudLvXohVqxw0aFD5N+vo0cNMjOdPPhgIsePx7g4ERERibmoPj59+OGHyczM5Prrr6dJkyakpqbyyy+/sGrVKnw+H//5z3/MqlNExHQpKTB6dA4tWwbo2zeRI0cMZsyws369lbFjc2jQQGPERURECquorig1bNiQGTNmULNmTZYvX85rr73G6tWrSUtLY/bs2Vx++eVm1Skict7cdFOAlStdNG0aAGDPHgvt2jkZOtTB7y6Yi4iISCER9YL86tWr88orr5hRi4hIzPzjH2FmzvQwebKd559PwOs1GDkygZUrbYwb56Fy5fBfn0REREQKjKiuKAHs3buXnTt3AnDs2DGeeeYZ7rvvPubOnRt1cSIiF5LFAj16+PngAzfVqkWW3W3ebKVFi2SmT7cTVlYSEREpNKIKSqtXryY9PZ05c+YAMHDgQGbOnMmBAwfo168fs2bNMqVIEZEL6f/9vxAffOCmRw8fAG63waOPJtKlSyKHDmmMuIiISGEQVVAaN24cjRs35v777+f48eN89NFHdO/enffff5/u3bvz5ptvmlWniMgFlZgIzz3nZdYsN5dcEhkjvmSJnebNk1i+3PoX3y0iIiL5XVRBafv27XTp0oWUlBTWrFlDMBikdevWAKSlpbF7925TihQRiZVmzYKsXOmibdvIVIeDBy3cdVcS/fol4PHEuDgRERE5b6IKSgkJCQQCkSlRa9as4aKLLuKKK64A4NChQxQtWjT6CkVEYiw1FV57LYdXXvGQnBzZqPTaaw6uvz6JL7+MequniIiIxKGofsLXqVOHqVOnsmDBAhYvXkyrVq0A+OqrrxgzZgxXX321KUWKiMSaYcBddwVYscJF3bqRQQ/ffmvlhhuSGDPGTigU4wJFRETEVFEFpX79+nHgwAH69u1LuXLl6NmzJwA9evTA5/PRt29fU4oUEYkXl14aJivLzeOPe7Faw/j9Bs8+m8httznZt0+DHkRERAqKqIJS+fLlWbhwIWvXrmXBggVcfPHFAIwdO5ZFixZRoUKF3GM3bdqE2+2OrloRkThgs8Gjj/pYsMBNpUqRS0nr1tlo3jyZ99+P+vZ0IiIiEgeiXlxvGAYlS5Y87bFatWrhcDhy/x4MBrnnnnv44Ycfon06EZG4UadOiGXLXHTuHBkjnp1t0KOHk549Ezl2LMbFiYiISFQu2C7ksO7UKCIFUEoKjBjh5fXXPaSmRq4uzZljp3nzZNav1xhxERGR/ErjmkRETHDjjQFWrXLTokVkEuhPP1m4+WYngwc78PliXJyIiIicMwUlERGTlC4d5p13PLzwQg6JiWHCYYPRoxNo0yaJ777TP7ciIiL5iX5yi4iYyDCgWzc/H37opnr1yBjxLVustGyZxOuv29EqZBERkfxBQUlE5Dy44ooQS5a4uf9+H4YRxuMx+Pe/E+nc2ckvv2iMuIiISLxTUBIROU8SEmDgQC9z5ngoUyYy6OHDD200a5bEhx9q0IOIiEg8U1ASETnPGjcOsnKli5tv9gNw6JCFu+9O4t//TkC3lxMREYlP5xyU9uzZQygUOh+1iIgUWMWLw8SJOYwd66FIkchGpddfd9CyZRJbtugzKxERkXhzzj+db7/9djZv3gxAv3792Lt3718/icXCAw88QKlSpc69QhGRAsIw4PbbA6xY4aJBg8gY8Z07raSnJzF6tINgMMYFioiISK5zDkper5edO3cC8P7773PkyJG//B7DMHjggQe4+OKL/9ZzfPHFF3Tu3JlatWrRqFEjHn/8cf73v//lfv3777+ne/fu1KlThwYNGtC/f3+OHTt22jlOnDjB008/TVpaGrVq1aJr1665df/WtGnTaNmyJVdeeSXt2rVj6dKlf6tGEZG8qlAhzNy5Hvr392KzhQkEDAYPTuCWW5zs3atBDyIiIvHACIfPbVhtz549WbFiBYZhEA6HMYw//qFuGAbffPPNORX01Vdf0bFjR6655ho6d+7MwYMHGTlyJOXKlePdd9/l2LFjtG3bllKlStGzZ0/+97//MXz4cK688kqmTp2ae54ePXqwdetWHnvsMVJSUhgzZgz/+9//WLhwIcWLFwdgypQpjBw5kvvvv58aNWowZ84cli5dyhtvvEG9evXOqe6TDh92EQzGbmmi1WohNTU55nUUFOqn+dTT033xhYWePZ3s2hX53KpIkTAvvphD+/aBv/X96qf51FNzqZ/mU0/NpX6aL156erKOvLKd6zcMHz6cefPmceTIEcaMGcNtt93GJZdckucCfm/YsGFUq1aNcePGYbVGpkKlpKQwePBg9u7dy6JFizh27Bhz584lNTUVgNKlS9O9e3c+/fRT6taty+eff87KlSuZNGkSzZo1A6Bu3bpcd911vP322/Tq1YucnBwmTpzI//3f/3H//fcD0LRpU+666y7Gjh3L66+/btprEhH5I7VqhVi61MWgQQm88YaD48cNevVysnSpn6FDc/j1cx0RERG5wM45KKWkpNCpUycAPvnkE7p27UqVKlVMKebIkSNs3LiRoUOH5oYkgFatWtGqVSsA1q5dS506dXJDEkCTJk1ITk5m9erV1K1bl7Vr15KUlERaWlruMampqdSrV4/Vq1fTq1cvtmzZwrFjx3LPC5ErYNdffz0jR44kJyeHxMREU16XiMifSU6G4cO9XH99gIcfTuTQIQvvvWfnk0+sjBmTQ1qaNi+JiIhcaFGNWpo+fTpVqlRh165dvPPOO0yaNIlZs2axa9euPJ1vx44dhMNhLrroIh599FFq165N7dq16du3L9nZ2QDs2rWLSpUqnf4iLBbKlSvHjz/+mHtMuXLlsNlOz4EVKlTghx9+yD0G4NJLLz3tmIoVKxIMBtmzZ0+eXoOISF61ahVk5Uo3118fWXa3b5+FW2918swzCXi9MS5ORESkkDnnK0q/9/TTTzNr1ix+u9XJMAxuueUWBg8e/Kd7mH7v8OHDAPTv35+mTZsybtw4fvzxR0aOHMnevXt55513OHbsGMnJZ641TE5O5sSJEwAcP36clJSUsx7jcrlyjwHOOO7kuU+e61xZrQaxvD1V5PljX0dBoX6aTz39c//4B7zzjpdp04I8/bQDj8dg7FgHq1dbmTDBy44dFm68MYjdHjn+9/30+2HRIivt2ukqVF7pPWou9dN86qm51E/zxUtPT9aRV1EFpcmTJzNnzhx69+5NRkYGF198MQcPHmTevHmMHz+eyy67jK5du/7t8/n9kZsxVq9encGDBwNwzTXXULRoUfr06cO6desAzhq+fjtYIhQK/WFAs1gsuceczcnAd/K4c1WsWFKevs9s8VJHQaF+mk89/XN9+0LbttCpE2zeDF9+aaV58yT8frj9dvjPf8gNSxDpp98fOX7WLJg5M3Kc5J3eo+ZSP82nnppL/TRffu9pVEFp9uzZZGZm0rNnz9zHypUrx/3334/f72fWrFnnFJROXs259tprT3u8SZMmAGzbto2UlJSzXu1xu925QyWKFCly2jjxk1wuF0WKFAGgaNGiuY8VK1bstPOcPEdeZGe7CQbPaZCgqaxWg2LFkmJeR0GhfppPPf37SpWChQvhxRftjB5tx++PfAA0axYcOxbgjTe8JCZG+nnokJvMTAfz5tlo1y5A06Zefr1IL+dI71FzqZ/mU0/NpX6aL156erKOvIoqKP388880bNjwrF9r0KDBaeO6/46T+4V8Pt9pjwcCkfX6iYmJVKpU6Yz9Q6FQiJ9++il3MEOlSpVYu3YtoVDotCtDe/bsoXLlyrnHAOzevZuaNWvmHrN7924cDgfly5c/p9pPCgbDMR4taYmTOgoK9dN86um5sFqhf38v114b4P77E/npp0j/PvjAxk03wfz5XpKSyA1JGRl+xo3LwWJBN7DNM71HzaV+mk89NZf6ab546Wl0y/6i+u6yZcuyffv2s37tm2++OW0y3d9RpUoVypYty8KFC097fNmyZUBkxHdaWhqbNm3K3c8EsGbNGlwuV+6Uu8aNG+NyuVizZk3uMYcPH2bTpk00btwYgNq1a5OUlMQHH3yQe0w4HOajjz6ifv36OByOc6pdROR8uuaaICtWuLjtNn/uY5s22ahf38ltt5EbksaPzzltSZ6IiIjkjXXQoEGD8vrN2dnZTJgwgXLlylG1alUMwyAUCrFw4UKGDRvGLbfcctqI7r9iGAalS5fm9ddfZ+fOnRQpUoRVq1YxbNgwWrRowT333EPVqlWZMWMGS5cupWTJkmzevJlBgwbRoEEDunfvDkQC3MaNG3nnnXcoXrw4+/fvp3///oTDYYYMGUJiYiJ2ux2/38/EiRMJBAJ4vV5GjhzJxo0bGTJkCGXKlMlTTzweP+d4D19TWSwGTqcj5nUUFOqn+dTTvEtMhLZtA1SpEmLVKhs+n0F2tsG330K9ekGmT/egz3iip/eoudRP86mn5lI/zRcvPT1ZR14Z4Siq9/l89OjRg/Xr12Oz2ShevDhHjx4lGAxSv359Jk2aREJCwjmfd8WKFYwdO5YdO3ZQrFgxbrrpJh555JHcqzzffvstQ4YM4fPPPyc5OZmWLVvy73//+7QJdtnZ2QwdOpSlS5cSCoW4+uqr6devX+7SO4hcQRo/fjwzZ87k8OHDVK1alYcffpimTZvmtSVxcwfiWNdRUKif5lNPzfHDDwbp6UkcPnxqYUCjRgGefdZLzZrqazT0HjWX+mk+9dRc6qf54qWnJ+vIq6iC0kmrVq1i06ZNZGdnU6xYMerVq0ezZs2iPW2+FC9viFjXUVCon+ZTT6Pn90PPnolkZdmpVi3Id99Z+XUrJwC33eanf38v5cvrk9G80HvUXOqn+dRTc6mf5ouXnkYblKK+jxJAs2bN/jQYBYNBatSowezZs6levboZTykiUij9NiRlZPiZNMlHKJRM48Yhvv8+cnVpzhw78+fbyMz08/DDXooXj3HRIiIi+dAFuwOU1nyKiETn9yHp5OCGf/wDPv7Yw3XXnRr04PMZjBvnoEGDFCZMsOP1xrBwERGRfEi3HxYRyScWL7adEZJOstvhzTdzyMiIhKUqVSKzwY8cMXj66UTS0pKZO9eGPrMSERH5exSURETyiYyMAFOmeP5wBLjdDuPH5zBlioePP3YzbZqHypUja8P37LHQvbuTG25IYv166wWuXEREJP9RUBIRyUcyMgJ/ep8kuz1yjGFAmzYB1qxx8cILOZQsGQlMn39upV27JO65J5HvvtOPABERkT+in5IiIgWY3Q7duvn55BMXjzzixemMrL1bssRO06ZJPPZYAgcPGjGuUkREJP4oKImIFAJFikC/fj7Wr3fRoYMfwwgTDBq88YaDBg2SeeklBy5XrKsUERGJHwpKIiKFSJkyYUaPzmH5cjctWkRuvuRyGQwblkDDhsm89ZadYDDGRYqIiMQBBSURkUKoevUQ777rYdYsNzVqRJLRgQMW+vRJ5Nprk1i61KoJeSIiUqhdkKBkGAb16tUjOTnvd8YVERHzNWsWZOlSN6++6qFs2cjAh+3brXTsmET79k62btXnaSIiUjjZoj3BgQMH+Oqrrzh+/PhZv37zzTdjsViYPn16tE8lIiLngcUCd94ZICMjwOTJDkaPdnD8uMGaNTZatrRx221++vf3Ur68LjGJiEjhEVVQWrRoEU888QQ+n++sXzcMg5tvvjmapxARkQvE6YTevX106uRn5EgH06bZCQQM5syxs2CBjcxMPw895KV48VhXKiIicv5FFZRGjRrFlVdeSf/+/Smun5wiIgXCRReFGTzYS7duPgYPTmD+fDter8HYsQ7eftvOI4946drVT0JCrCsVERE5f6JafH7w4EG6d+9O9erVKVu27Fn/iIhI/lS5cpjXXsth4UIX9epFBj4cOWLw9NOJpKUlM3euTQMfRESkwIoqKNWqVYsffvjBrFpERCQO1asXYsECN9OmeahcOTLwYc8eh1yaPgAAIABJREFUC927O0lPT2LDBmuMKxQRETFfVEvvBg4cyH333ceJEyeoWbMmTqfzjGPq1asXzVOIiEgcMAxo0yZAq1YB3nzTzogRDg4dsrB5s5WMjCRuuMHPgAE+LrssFOtSRURETBFVUPrxxx85dOgQY8aMASLDG04Kh8MYhsG2bduiq1BEROKG3Q7duvm54w4/Y8Y4mDDBgcdjsGSJnY8+snH33X4ee8xHqVJakyciIvlbVEHpxRdfpFy5cvTo0YOSJUuaVZOIiMS5IkWgXz8fXbr4efHFBN5910YwaPDGGw5mz7bzwAM+7rvPh26fJyIi+VVUQWn//v2MHz+etLQ0s+oREZF8pEyZMKNH59C9u4Xnnktg+XIbLpfBiy8m8Prrdh5/3EeHDn6s2sYkIiL5TFTDHC6//HL++9//mlWLiIjkU9Wrh3j3XQ+zZrmpUSMyIe/AAQt9+iRy7bVJLF1q1YQ8ERHJV6K6otS/f38effRRgsEgtWrVIiUl5YxjypQpE81TiIhIPtKsWZClS93MmmVj6NAE9u2zsH27lY4dk2jSJMDAgV5q1tTABxERiX9GOJz3z/hq1qxJIBAgFAqdNsjhtwrbMIfDh10Eg7H7JcBqtZCamhzzOgoK9dN86qm54rmfHg9Mnuxg9GgHx4+f+hnRvr2ffv28lC8fn5eY4rmn+ZH6aT711Fzqp/nipacn68irqK4oDRo06A8DkoiIFG5OJ/Tu7aNTJz8jRzqYNs1OIGAwe7ad+fNtZGb6efhhL8WKxbpSERGRM0UVlG699Vaz6hARkQLqoovCDB7spVs3H4MHJzB/vh2v12DsWAdvv22nTx8v//d/fhISYl2piIjIKVEFpU2bNv3lMbrhrIiIAFSuHOa113L49FMfgwYlsHGjjSNHDAYMSGTyZAdPPeWlXbsAWqggIiLxIKqg1LlzZwzD4LfbnH6/FK+w7VESEZE/V7duiPnzPSxaZOO55xL4/nsLe/ZY6N7dyYQJQQYN8tKwYTDWZYqISCEXVVB68803z3jM7Xbz2WefMW/ePF555ZVoTi8iIgWUYUCbNgFatQrw5pt2RoxwcOiQhc2brWRkJHHDDX4GDPBx2WXaWC0iIrERVVCqX7/+WR9v3rw5SUlJjB8/nokTJ0bzFCIiUoDZ7dCtm5877vAzZoyDCRMceDwGS5bY+egjG3ff7eexx3yUKhWfE/JERKTgiuqGs3+mTp06fPLJJ+fr9CIiUoAUKQL9+vlYv95Fhw5+DCNMMGjwxhsOGjRIZsQIBy5XrKsUEZHC5LwFpaVLl571BrQiIiJ/pEyZMKNH57B8uZsWLQIAuFwGL76YQMOGybz1lp2gti+JiMgFENXSu3vuueeMx0KhED///DP79+/n3nvvjeb0IiJSSFWvHuLddz2sWmXlmWcS+OorKwcOWOjTJ5FJk+w8/bSX664LakKeiIicN1FdUQqHw2f8sVgs/POf/+TZZ5/l4YcfNqtOEREphJo1C7J0qZtXX/VQtmxksMP27VY6dkyifXsnW7eet4URIiJSyEV1RWn69Omn/f3o0aPs3buXSy+9lCJFikRVmIiICIDFAnfeGSAjI8DkyQ5Gj3Zw/LjBmjU2Wra00b69n379vJQvr4EPIiJinjx9FLd161buu+8+5s6dm/vY9OnTadasGXfccQdNmjThtddeM61IERERpxN69/axcaOLe+/1YbNFgtHs2XYaNUrmmWcSyM6OcZEiIlJgnHNQ2rZtG3fffTfbt28nKSkJiASnIUOGUKFCBV599VV69erFyy+/zNKlS00vWERECreLLgozeLCXtWtd3HSTHwCv12DsWAf166cwcaIdny/GRYqISL53zkFp0qRJVKtWjcWLF9OqVSvg1BK84cOH07JlS7p3707Hjh3PWJonIiJilsqVw7z2Wg6LFrmoXz8yIe/IEYMBAxJJS0tm7lwbYa3GExGRPDrnoLRp0yY6d+6M0+nMfWzt2rWUL1+eK664Ivexxo0b880335hTpYiIyB+oWzfE/Pkepk3zULlyZODD7t0Wund3kp6exIYN1hhXKCIi+dE5B6WjR49yySWX5P59165dHDlyhAYNGpx2nNPpxKe1DyIicgEYBrRpE2DNGhdDh+ZQsmQkMG3ebCUjI4l77knku+80IU9ERP6+c/6pUbx4cQ4dOpT79w0bNmAYBtdcc81px+3atYvU1NToKxQREfmb7Hb417/8fPKJi0ce8eJ0RtbeLVlip2nTJB57LIGDB3XzJRER+WvnHJTq16/PjBkzCIVCBAIB5syZQ0JCAk2aNMk9xufz8Z///Ierr77a1GJFRET+jiJFoF8/H+vXu+jQwY9hhAkGDd54w0GDBsmMGOHA5Yocm5Vlw+//43P5/ZFjRESkcDnnoNSzZ0+2bNlCy5YtadWqFd988w3dunXLvW/SnDlzuOuuu/jhhx/IzMw0vWAREZG/q0yZMKNH57B8uZsWLSIDH1wugxdfTKBhw2T69k0gM9NJz56JZw1Lfj/07JlIZqZTYUlEpJA556B02WWXMXPmTBo2bMhll13GwIEDefDBB3O/PmrUKI4cOcLYsWOpVq2aqcWKiIjkRfXqId5918OsWW5q1AgCcOCAhTffdFCkSIisLPsZYelkSMrKspOR4Sc9PRCj6kVEJBaMcNjc4akHDhzg4osvxmIpnJtmDx92EQyGYvb8VquF1NTkmNdRUKif5lNPzaV+nrtQCGbNsjF0aAL79p3+s6pp0wAzZ3pJTU3m9tsDzJtnIyPDz/jxOdjtMSo4n9N71HzqqbnUT/PFS09P1pFXpqeZ0qVLF9qQJCIi8c9igTvvDPDxxy6eespLkSKnPi9cvdpGnTpO2rRBIUlEpJBTohERkULJ6YTevX1s3Oji3nt9WK2RwLRvn4WPPoISJcI0ahTMHfogIiKFi4KSiIgUahddFGbwYC+rVrm45JJTS0SOHDF44olEatRIoWvXRBYvtqHbA4qIFB4KSiIiUuj5/TBsWAL//a+Fpk0DXH75qa/5fAYLF9rp0sVJzZrJPP54Ap99ZsHcHb4iIhJvFJRERKRQ+/10u5kzvXz1FWRkRKbclS8fIikpkooOH7YwbZqD9PRkGjVKZuRIB3v26Aa2IiIFkYKSiIgUWr8PSScHN9jtMGmSl4wMP3v3WmjePMCrr3q49toAFkskNO3aZWHo0ATq1k2hXTsnb71l59ixGL8gERExjYKSiIgUWosX284ISSfZ7TB+fA4ZGX4WLbLjdMKMGR62bHExaFAO1asHc49dv95Gnz6JVK+ewr33JvLhh9az3sBWRETyD9Pvo1TYxcu8+FjXUVCon+ZTT82lfkYvK8tGenogNyT9vqd+fyRQnVyK91tff21h1iw7c+bYOHDg9M8eS5YMccstAW6/3c9VV4UwCukKPb1Hzaeemkv9NF+89DTu7qMkIiKSn2RkBP70Pkl2O2cNSQDVq4cYNMjLF1+4mDHDTfv2/tz9TIcOWZg82UGrVsk0bpzE6NEOfvqpkKYlEZF8SEFJREQkSlYrXHttkHHjcvjqqxO8+qqHpk0DGEYkNH33nZXBgxOoUyeZW2918s47No4fj3HRIiLypxSURERETJSSAnfeGWD2bA+ff+5iwAAvV1wR2c8UDhusXWvjoYec1KiRwn33JbJsmZXA2S9YiYhIDCkoiYiInCdlyoR58EEfq1a5WbbMRY8ePi6+OLJe3+MxeO89Ox06JHHVVckMGJDAl1/q/kwiIvFCQUlEROQ8Mwy48soQzz3nZcsWF++84+bWW/04nZFU9MsvFiZOdHDddck0b57Eq686+Pln7WcSEYklBSUREZELyGaD664LMmFCZD/T6NEeGjc+tfZu2zYrzz2XQK1aybRv72TGDBsnTsSwYBGRQkpBSUREJEaKFIEOHQK8956HzZtP8OSTXi6//NR+ptWrbTz4YGQ/U69eiaxYYSUY/IuTioiIKRSURERE4kC5cmEeesjHmjVuPvzQxb33+ihZMrKfye02mD3bzp13JlG7djKDBiXw9df6ES4icj7pX1kREZE4YhhQq1aIwYMj+5neestNu3Z+EhIi+5n++18L48Y5uPbaZK69Nolx4+wcOKD9TCIiZlNQEhERiVN2O7RqFWTy5Mh+ppEjc7jmmlP7mb7+2sqgQYlcdVUyd97pZPZsGy5XDAsWESlAFJRERETygWLF4O67/cyb52HTphM88YSXypUjS/NCIYMVK2z06hXZz/Tgg4msWWMlFIpx0SIi+ZiCkoiISD5TsWKYPn18rF/vYvFiF//6l48SJSJL81wugxkz7Nx2WxJXX53Mc8852L5dP+5FRM6V/uUUERHJpwwD6tQJMXSoly+/PMEbb3ho29aPwxEJTfv3W3j11QSaNk2mZcskJk60c/Cg9jOJiPwdCkoiIiIFgMMB6ekBpk6N7GcaPjyH+vVP7WfautXKgAGR/UwdOzp5/30bHk8MCxYRiXMKSiIiIgVM8eLQpYufBQs8fPLJCR57zMull0Y2LAWDBkuX2ujRI7Kf6eGHE1i3TvuZRER+T0FJRESkAKtUKcxjj/n45BMXCxa46NLFR/HikaV5x48bvP22g1tuSaJu3WSGDHHw3Xf61UBEBBSURERECgXDgPr1QwwfHtnPNHWqh/R0P3Z7JDT99JOFUaMSSEtLpnXrJKZMsXPokPYziUjhpaAkIiJSyCQkQNu2Ad54I4cvvzzB0KE51KkTzP36559b6d8/kZo1k+nc2cn8+TZycmJYsIhIDCgoiYiIFGKpqfCvf/lZvNjN+vUn6NPHS4UKkQ1LgYDBBx/Y6NYtsp/p0UcT2LDBSjgc46JFRC4ABSUREREBoEqVME884WPjRhdZWW46d/ZRtGgkFR07ZjB9uoOMjCTq1Utm6FAH339/5tK8rCwbfv8fP4ffHzlGRCTeKSiJiIjIaSwWaNgwyIgRXr766gRTpnho1SqAzRYJTXv2WBg5MoGGDVNIT09i2jQ7hw9HAlBmppOePRPPGpb8fujZM5HMTKfCkojEPf0rJSIiIn8oMREyMgJkZAQ4dMhg7lwbM2fa+eILKwCffWbls8+sPPVUAi1aBKhXL0BWlh2A8eNzsEYOyw1JWVl2MjL8pKcH/ugpRUTiQtxdUfJ4PFSrVo1//vOfp/258sorc4/ZunUrd999N7Vr1yYtLY0XX3wRn8932nkOHjxInz59aNCgAVdffTW9e/fmwIEDpx0TCAQYOXIkzZo1o2bNmtx555189tlnF+R1ioiI5DclS4bJzPTz4Ydu1q1z8fDDXsqWjexn8vsNPvjAzqZNNuz2MFlZdu6804nPFwlJPXok5Iak8eNzsNtj/GJERP5C3F1R2rFjB6FQiJEjR1K2bNncxy2WSKbbs2cPXbt2pXbt2owaNYpdu3bx8ssvc/z4cZ5//nkgEoDuvfde3G43gwYNIhAIMGLECP71r38xd+5c7L/+6zx48GDef/99+vbtS5kyZZg2bRqZmZm89957VKpU6cK/eBERkXzisstC9O/v44knfKxfb2XWLBtZWXZOnDDw+yN7l9autVGlipUKFWD7dptCkojkK3EXlLZt24bdbqdVq1a5gea3pkyZQnJyMuPGjcPhcNCsWTMSExN57rnn6NmzJ2XLlmXJkiVs376dBQsWcNlllwFQrVo12rZty6JFi2jXrh0///wzM2fOpH///nTq1AmAxo0b07p1a6ZMmcLgwYMv6OsWERHJjywWSEsLkpYWZMgQLx98YGPWLDvLl1sJhQzcboPt2yPHfv21hWHDHLRpE+Cqq0IYuk2TiMSxuFt6t23bNqpWrXrWkASwdu1amjdvjsPhyH3shhtuIBQKsXbt2txjKlWqlBuSAKpWrUqVKlVYvXo1AOvXrycQCNCqVavcYxwOB82bN2fVqlXn46WJiIgUaElJcMstAd5+28Nnn7moVi142td37bIyenQCrVolc/XVyTz1VALr11sJBv/ghCIiMRR3QWn79u1YLBa6du1KrVq1qF+/Pk8//TQnTpwgJyeHffv2nbEsLjU1lZSUFH788UcAdu3axaWXXnrGuStUqMAPP/yQe0xSUhIXX3zxacdUrFiRX375BZfLdV5en4iISEHn98PAgQls22alTZsA118febxEiVDuMfv2WZg0yUG7dklceWUyjz6awPLlVn635VhEJGbiauldKBTi22+/xWKx0LdvX3r16sWXX37JmDFj2LlzJy+//DIAKSkpZ3xvcnIyJ06cAODYsWNUrFjxrMecDEDHjx+nSJEiZz0G4MSJE7n/+1xYrQaxzJ+R5499HQWF+mk+9dRc6qf51NPo+P3Qq1cCWVk22rULMGWKj2LFbNxxR4C5c220ahWgefMgixbZ+PhjC6GQwaFDFqZPdzB9uoMiRcK0bh2kbdsALVoEycOP4gJP71FzqZ/mi5eenqwjr+IqKIXDYSZOnEjJkiWpUqUKAPXq1aNkyZI89thjfPLJJ3/6vcavi51/+79/f8zJoRChUOgPj4FTwyPOVbFiSXn6PrPFSx0FhfppPvXUXOqn+dTTc+f3Q6dOMG8e3H47/Oc/Nuz2yK8aM2fa6NQJZs2yUayYjeXLITsbsrLgvffgo4/A54Pjxw1mz7Yxe7YNpxNuuAFuvRXatoXixWP8AuOM3qPmUj/Nl997GldByWq10qBBgzMeb968OQD79u0DOOuyOLfbnXuFqEiRIrlXl/JyzMmv50V2tptgMJyn7zWD1WpQrFhSzOsoKNRP86mn5lI/zaee5t28eVZmzUqkXbsAr77q5fjxU/10u928+moYny+BWbNspKfn0K5dkJtvhptvhmPHYOlSKwsX2vjoIysul4HHA++/H/ljs4Vp2jRI27ZB0tMDlCoV61cbO3qPmkv9NF+89PRkHXkVV0HpwIEDrFq1iqZNm3LJJZfkPp6TkwNAyZIlKV26NLt37z7t+w4fPsyJEyeoWrUqAJUqVWLbtm1nnH/Pnj3UrFkTgMqVK3PixAkOHz5Mampq7jG7d++mbNmyJCYm5uk1BINhgsHQXx943ljipI6CQv00n3pqLvXTfOppXrVtG2LKlDDp6QEsFn4d0nCqnxZLiHHjPNx0k422bQOnDXFIToZ27UK0a+fH44HVq60sXGhnyRIbR48aBAIGy5fbWL7cxqOPOmjQIEibNgFuvDFA+fKF7ZdbvUfNpX6aL156Gt2yv7haiOnz+RgwYAAzZsw47fFFixZhsVioU6cOaWlprFy58rQbzC5ZsgSr1UrDhg2ByJjvXbt2sXPnztxjdu7cya5du0hLSwOgUaNGud/72+dfuXIljRs3Pm+vUUREpCDLyAj86X2S7PbIMX/G6YTWrYO88koOX399gtmz3XTt6qN06cgvXOGwwYYNNgYMSKROnRSuvz6JUaMcfPddXP1aIyL5nHXQoEGDYl3EScWKFWPv3r3MmDEDwzAIBALMmzePV155hQ4dOnDzzTdTqVIlpk2bxsaNGylevDgrV65k+PDh3HHHHbRt2xaIXC1avHgx77//PiVLluTbb7+lX79+lClThieffBKLxULRokXZt28fU6dOxel0cvToUZ599ll++uknXnzxRYrncSG0x+PP3ecUCxaLgdPpiHkdBYX6aT711Fzqp/nUU3NF20+rFSpWDHP99UHuu89P8+YBihWDgwcNsrMje40PHLCwZo2NqVMdzJtn48ABg2LFwpQqFS6Q92rSe9Rc6qf54qWnJ+vIKyMcZ+8Ir9fLlClTyMrKYv/+/ZQuXZo77riDbt26YbVaAfj0008ZNmwY27Zto0SJErRr146HHnoIm+3USsKff/6ZwYMHs27dOux2O2lpafTr149Sv1nU7PP5eOmll1iwYAFut5vq1avz+OOP5y7Py4vDh10xvcRotVpITU2OeR0FhfppPvXUXOqn+dRTc52vfobD8NVXFhYtsrFokY1t26xnHFO+fIgbbwzQpk2AevWCWM88JF/Se9Rc6qf54qWnJ+vIq7gLSvldvLwhYl1HQaF+mk89NZf6aT711FwXqp+7dhksXGhn0SIbmzefmYguvjhEenokNKWlBXHk/UPmmNN71Fzqp/nipafRBiUt5hUREZF8r0qVML17+1iyxM3nn59gyJAc0tICWCyRz4N/+cXCm286uPPOJKpXT+H++xNZuNDGr8NuRUTOEFdT70RERESiVbZsmMxMP5mZfg4dMvjgAxsLF9pYtcqK3x/Z2zRrlp1Zs+w4nWFatIhcaWrVKkDRorGuXkTihYKSiIiIFFglS4bp1MlPp07+X+/VFAlNy5bZcLsNPJ7Ikr2FC+3Y7ZF7NbVpE6B16wAXX6zdCSKFmYKSiIiIFApFi8Kttwa49dYAHg+sXBkJTR98YCM728DvN1i2LBKiLJbwafdqKldOoUmksFFQEhERkULH6YT09ADp6QH8fli3zsrChZEJer/8YiEUMli/3sb69Taeegpq1YqEpjZt/FStqtAkUhhomIOIiIgUanY7NG8eZPhwL1u3upg/38199/moUOHUtK4vvrAyeHACjRql0KRJEkOHOvjySwuaHSxScOmKkoiIiMivrFZo0CBIgwZBnnnGy1dfWVi4MLJEb8eOyNjxHTus7NhhZeTIBCpUOP1eTRZ9BC1SYOg/ZxEREZGzMAy48soQTzzhY80aN+vWuXjySS+1agVzj9mzx8KECQ5uuimJmjWTeeyxBFautOL3x7BwETGFgpKIiIjI33DZZSEeesjHhx+6+eyzEzz/fA7XXBPAMCLr7w4etPDGGw7uuCNyr6YHHkhk8WIbHk+MCxeRPFFQEhERETlH5cuH6d7dz7x5Hr780sWIETm0aBHAbo+EpqNHDWbOtNOli5Nq1VLo1i2R996zcfx4jAsXkb9Ne5REREREolCqVJjOnf107uwnOxs++iiyp2n5chsej4HbbTB/vp358+04HKffq6lkSU2DEIlXuqIkIiIiYpJixaB9+wDTpuWwbdsJpk3z0L69n6JFI4HI5zNYutTGI48kUqNGMrfc4mTKFDv79hl/eM6sLNuf7nny+yPHiIi5FJREREREzoOkJGjTJsC4cTl8880J3n3XTefOPkqWjIwdD4UM1q2z0b9/IrVrp3DDDUm88oqD778/FZqysmxkZjrp2TPxrGHJ74eePRPJzHQqLImYTP9FiYiIiJxnDge0aBGkRYsgw4Z52bTJmjt2/KefIp9bb95sZfNmK88/n0C1akFuvDGyPC8jw09Wlh2A8eNzsEamlOeGpKwsOxkZftLTA7F6eSIFkoKSiIiIyAVktULDhkEaNgzy7LNetm6N3KtpwQIbO3dGUtC2bVa2bbMyYkTkXk1VqgTJyrITDsPkyT78fujRI4GsLBsZGX7Gj8/Bbo/xCxMpYBSURERERGLEMOCqq0JcdZWP/v19fPvtqRvcbt0aCU179pzaKTF/vp0GDayULQsff6yQJHI+KSiJiIiIxInLLw9x+eU+HnnEx549BosWRULTxo1WwuHI3qXduy3s3g2GEebnnw1GjnTQpEmQOnWCJCTE+AWIFCAKSiIiIiJxqEKFMPfd5+e++/wcOGCwcKGNl15ycOhQ5ApTOGywaZONTZtsjBgBTmeY+vWDNGkSpEmTADVrhnL3M4nIuVNQEhEREYlzqalhPv7YyqFDFlq3DpCdbWPDBihSJMTx45Hg5PEYrFplY9UqG5BA0aJhGjUK/BqcgvzznyGMP55CLiK/o6AkIiIiEsd+P91u0iQfqak2br89wLx5Nlq39tOuXYD1662sWWPjxx8jwenYMYMlS+wsWRLZwHTxxSGaNAnSuHHkilPFirrZrcifUVASERERiVO/D0mRwQ0W7HaYONFLOBwmK8tOQgK/fs3L3r0Ga9dGQtOaNVYOHIgEp19+sfDeexbeey8SnCpUCNG4cSA3PJUureAk8lsKSiIiIiJxavFi2+9C0qmv2e2RcAT8ekyAjIwA5cuH6dAhQIcOAcJh2LnTwpo1VtassbJunY2jRyPr7/bssfD22w7efjtyvn/+8+TVpiCNGgUoXvxCv1qR+GKEw2F9fGCiw4ddBIOhmD2/1WohNTU55nUUFOqn+dRTc6mf5lNPzaV+Ri8ry0Z6eiA3JP2+p35/JFBlZPz1DWdDIfjqq5PBycaGDVbc7jM3LhlGmJo1QzRpEqBx4yANGgRJTjb7lcUHvUfNFy89PVlHXikomSxe3hCxrqOgUD/Np56aS/00n3pqLvXTfGb21OeDzz+PXG1au9bKp59a8fnODE52e5g6dYK5gyGuvjqIwxHVU8cNvUfNFy89jTYoaemdiIiISCHlcECDBpErRn37gtsNGzeeDE42tmyxEAoZ+P0GGzbY2LDBxvDhkJQUpkGDyFK9pk0D1KihUeRS8CgoiYiIiAgASUnQvHmQ5s2DgI/sbPj4Y9uvwyGsbN8eSUNut8GKFTZWrIiMIi9e/PRR5JddplHkkv8pKImIiIjIWRUrBunpAdLTI/ufDh40WLfOmrvHaffuyES9o0cNFi2ys2hRZCNVqVKh3KtNjRsHqVBBOz0k/1FQEhEREZG/pVSpMLfcEuCWWwKAlz17IqPIV6+OXHU6eDASnA4ePH0UecWKkcEQTZoESUsLUqqUgpPEPwUlEREREcmTChXCdOwYoGPHyCjy7747fRR5dnZk/d3u3RZ273bw1luR77viimDu/ZsaNQpQrFgMX4TIH1BQEhEREZGoGQZcfnmIyy8P0a2bn2Dw9FHkn3xyahT59u2R/U6TJ4PFEuaqq06NIq9fP0hSUoxfjAgKSiIiIiJyHlitcNVVIa66KsQDD/jx+WDzZmvuFafPPrPi9xuEQgaff27l88+tvPIKOBxh6tY9dfPbq68OnnajXZELRUFJRERERM47hwMaNgzSsGGQxx4Dlws++SRy/6aTo8jDYQOfz+Djj218/LGNYcM9CtPEAAAZkElEQVQio8ivuSZI48aRPU41aoSwWGL9aqQwUFASERERkQsuORlatAjSokVkFPnRo5FR5Cdvfrtjx6lR5MuW2Vi2LPJra4kSp48ir1pVo8jl/FBQEhH5/+3de1RVZf7H8c/ZBzAFkQzTvCGpk0oYqFCoqal4TWyan2Wtbo4u03IaG9PMCadmMls6y8ZRJBF/5YTTRfoZGBajkxXVjHjJ8oKoU4hhqYmKN4Jz+f2x5eA56DQi4+bg+7UW/zznOfDdWwo+PM/+PgAAy4WFSSNGODRihNmK/NAh27nVJvMZp+Jicxnp2DGbcnIClZNj7sdr1cp1bpueGZ7atv33HfWyswM0fLjjotv5Kiul998PUFKSo+4uDn6JoAQAAIB6p2VLt37xC4d+8QuzFfn+/Tbl5VUffnvkiBmcvv/eUGamocxMM/l06ODdirxFi+rglJ0doAkTGispqVKpqeU1wlJlpTR58jXKzg5UevpZwtJVjqAEAACAei8iwq2IiEo98ECl3G6psNA4d4aTXZ9/HqCyMnP/XVGRoaKiIL3+uvm+rl2d57bpOdSnj0NJSZXKzjYTUmpquezmDj+vkJSUVOk5ZBdXL4ISAAAA/IrNJnXp4lKXLi5NmGC2Iv/qK8Oz4rRxo11nz5rBqaDAroICu9LSgmS3m63IO3d2Kjs7UE6ntHx5hSorpUcfbaTs7ICLrjbh6kNQAgAAgF+z26XYWJdiYyv0xBPSjz+arcg/+cR8xmnLFrscDpucTpu2brV73peTE6ioqABdf71UUBCgESMISahGUAIAAECD0qiRlJDgVEKCU08/LZ06JeXnm00h8vLs2r7dbEUuSUeP2nT0qPm+Dz4I0MiRTRQXZx58GxfnVOvW/745BBoughIAAAAatJCQ81uRS8eOSR9/HKA5cxpp//7qQ5lcLpu2bbNr2za7li0zx9q0cXlCU3y8U926uRTAb9BXBf6ZAQAAcFUJCZHeey9A+/cbGjnSIbc7QGvXSh07OhUWJm3fbqiiwlxxKikxtHq1odWrzf14TZq41bOnGZzi4pzq1cupZs2svBr8txCUAAAAcNXw7W6Xllah5s0DNGaMQ1lZZjOHVavOaNcuQ5s22bVpk135+Xb98IO58nTmjO3cFj7z12ibza2bbnJ5glN8vFORkW4OwW0ACEoAAAC4KviGJLNxg6HAQGnp0h/ldru9WofHx7skme3Ii4psys+3e8LT7t3mc05ut027d9u1e7fd05I8PNylXr2qnnNy6ZZbnLrmGuuuG7VDUAIAAMBV4f33A3xCUvVrgYFmOJJ0bo7Dc+CszSZFRroVGenQvfeaYydOSFu22D3hacsWu86cMZeRfvjB0AcfGPrgA/MLBAW51b179bNOcXFOXX89TSLqO4ISAAAArgpJSQ6lp5/V8OGOC7YArwpL54eki2nWzLtBhMMhFRQYnuCUn2/Xt9+a2/UqKmzavNmuzZurW5N36ODy6q7XpYtLhnHBLwWLEJQAAABw1fipABQY+NNzLiQgQIqOdik62qXx4yslSQcP2ryec9q+3ZDTaa46FRUZKioytGqVmdhCQ6ubRMTHO9Wjh1MhIZdcBuoQQQkAAAD4L2jd2q3Rox0aPdoMXqdPS19+afd61un4cTM4lZXZtGFDgDZsMH89Nwy3oqK8V53atqVJxJVEUAIAAACugOBgqXdvp3r3NrfruVzSvn3GecHJ0L599nOv2bR9u13bt9v1v/9rvr9VK+8znW6+2XXBLYSoGwQlAAAAwAKGIf3sZy797GcuPfCAuV3v6FGbNm+uDk/bttlVXm4uI33/vaHsbMPTma9xY7diY6sbRMTFOXXttZZdToNDUAIAAADqieuuc2voUKeGDjVXnSoqzANwq55zys+36/Bhs+vD2bM2ff55gD7/vPpX+s6dnV6rTh07sl2vtghKAAAAQD0VFCT17OlSz54uTZpknulUXGzzBKdNm+zatcs800mS9u61a+9eu1auNN/fvLlLcXHVB+LGxDjVuLGFF+RHCEoAAACAn7DZpIgItyIiHPqf/zGbRJw8aZ7pVBWetmyx69QpMziVlhrKzTWUm2v+2h8QYJ7pdH6TiFatONPpQghKAAAAgB9r2lQaMMCpAQPM7XpOp3mm0/mrTsXF5nY9h8OmrVvt2rrVrqVLzfe3b+9Sr17VwalbN5fs9ot9tZqyswMuejaVJFVWmof91qbtupUISgAAAEADYrdLN9/s0s03uzRunNkk4tAhm1db8q++MlRZaa46FRcbKi429H//Zyad4GDzTKeq4NSzp1OhoRf+WtnZAZowobGSkiqVmlpeIyxVVkqTJ1+j7OxApaef9auwRFACAAAAGriWLd0aNcqhUaPMoHL2rO+ZToZKS81Vp9OnbfrkkwB98okZFWw2t7p29d6uFxFhNokYPtyhpKRKTye+1NRyz2rU+SEpKalSw4f7T0iSCEoAAADAVadxY+m225y67TZzu57bLX39dfWqU36+XXv22M+9ZtOuXXbt2mXXihXm+6+/vrpBxIQJFXK55AlLaWkVqqyUHn20kbKzAy662lTfEZQAAACAq5zNJnXs6FbHjg7dd5+58nPsmLR5c3Vw+uILu86eNbfrHT5sKCfHUE6OmX6Cgtxq3tyl7OxAHTxo6IYbpDVr/DckSQQlAAAAABdw7bVSYqJTiYnmqlNlpbRzp+G16vTdd+Z2vYoKm0pLzRC1ebO5EjVihMNvQ5JEUAIAAADwHwgMlGJiXIqJcWniRPNMp5IS7+1627cbkszA5HRaW+/lMqwuAAAAAID/sdmktm3duvtuh37/+x8VGemSZFNCglPDhkm5uQGaPPkaVVZaXWntsKIEAAAAoNZ8u9ulpVWoefNgjRnjUFZWdTc8f9uCR1ACAAAAUCu+IckMRIYCA6WlS3+U2+32ah3uT2GJrXcAAAAAauX99wN8QlL1a4GBZjiqOmfp/ff9a43Gv6oFAAAAUG8kJTmUnn5Ww4c7LrhaVB2WHEpK4sBZAAAAAFeJnwpAgYE/Pac+YusdAAAAAPggKAEAAACAD4ISAAAAAPggKAEAAACAD4ISAAAAAPggKAEAAACAD4ISAAAAAPggKAEAAACAj3odlKZMmaKBAwd6jX399deaOHGievbsqVtvvVWzZs1SWVmZ15xTp05p9uzZ6tOnj2JiYjRu3Djt27evxud/9dVXNXjwYEVHR2v06NFav379f/V6AAAAAPiHehuUsrKytG7dOq+xsrIyPfLIIyotLdW8efM0bdo0rVu3TlOnTvWaVzU+bdo0zZs3T0ePHtXDDz+s48ePe+akp6dr/vz5+vnPf67FixcrIiJCTzzxhDZt2nRFrg8AAABA/RVgdQEXcujQIc2ZM0etWrXyGn/jjTdUVlamd999V82bN5cktWzZUhMnTtTmzZvVq1cvffHFF/roo4+Ulpam/v37S5J69eqlQYMG6a9//asee+wxlZeXa+nSpXrkkUf0+OOPS5L69eunsWPHKiUlRa+99toVvV4AAAAA9Uu9XFF69tln1adPHyUkJHiNf/rpp+rZs6cnJEnS7bffruDgYH3yySeeOU2aNFGfPn08c5o3b664uDjPnC+//FJlZWUaMmSIZ47NZlNiYqLy8/NVXl7+37w8AAAAAPVcvQtKq1at0s6dO5WcnFzjtX/961+KjIz0GjMMQ23btlVRUZFnTtu2bRUQ4L1Y1r59e33zzTeeOZLUoUMHrzkRERFyOp0qLi6uo6sBAAAA4I/q1da7kpISzZ07V3PnzvVaNapSVlam4ODgGuPBwcE6deqUJOnkyZMKCQm54JzTp0975kiqMa/qc1d9rtoIDDRkt9tq/f7LZRi2elFHQ8H9rHvc07rF/ax73NO6xf2se9zTusX9rHv15Z5W1VFb9SYoud1uzZo1S/3799fQoUMvOs9mq3nBbrfbM+5yuS44RzJXn6rmXKyG8+fVRtOmjWv93rpUX+poKLifdY97Wre4n3WPe1q3uJ91j3tat7ifdc/f72m9CUorV65UYWGh1qxZI4fDIak6uDgcDhmGoZCQkAuu9pw5c8bT+KFp06Y6evRojTmnT59W06ZNJUmhoaGesWbNmnl9nqrPAQAAAODqVW+CUm5uro4dO6a+ffvWeC0qKkpTpkxRZGRkjeeHXC6Xvv32W09jhsjISH366adyuVxeK0PFxcW68cYbPXMkaf/+/erevbtnzv79+xUUFKR27drV+fUBAAAA8B/1Jig9//zznmeIqqSkpGjHjh1KTU3V9ddfL5vNpuXLl6u0tNTzDFNeXp5Onz7t6XLXt29fvfLKK8rLy/O0By8tLdWmTZs0adIkSVJsbKyaNGmi3NxcT1Byu91at26d4uPjFRQUdKUuGwAAAEA9VG+CUtVqz/nCwsIUFBSk6OhoSdL999+vjIwMjRs3TlOmTNHx48c1f/589evXT7GxsZKkuLg4xcfHa/r06Zo+fbrCwsK0aNEiNW3aVGPHjpUkNW7cWL/85S+VkpKiwMBAxcbG6p133tHOnTu1YsWKK3fRAAAAAOolm7vqQaB6aObMmcrPz9eHH37oGduzZ49efPFFffHFFwoODtbgwYM1Y8YMrw52J06c0EsvvaT169fL5XKpR48eeuaZZ7zCmNvtVmpqqt5++22VlpaqU6dOmjp1qvr163dFrxEAAABA/VOvgxIAAAAAWKHeHTgLAAAAAFYjKAEAAACAD4ISAAAAAPggKAEAAACAD4ISAAAAAPggKDVA3333nXr16qWNGzdaXYrfcrvdeuuttzRq1CjFxsZq0KBBmjNnjk6dOmV1aX7L6XQqLS1NiYmJ6t69u5KSkpSVlWV1WQ3GlClTNHDgQKvL8Gtnz55V165dddNNN3l9VJ3lh0u3bds2Pfjgg4qJiVHv3r319NNP6+jRo1aX5Zc2btxY43vz/I/FixdbXaJfevvttzVy5EjFxMRo+PDhWrlypWgIXXsul0vLly9XYmKioqOjNWzYMK1YscJv72m9OXAWdaOkpETjx4/XyZMnrS7Fr6Wnp+vll1/W+PHjlZCQoP3792vhwoXau3evXn31VdlsNqtL9DsLFizQihUr9MQTTyg6Oloff/yxZsyYIcMwNGrUKKvL82tZWVlat26d2rRpY3Upfq2wsFAul0sLFizwupeGwd8Ua2PHjh166KGHlJCQoMWLF+vw4cNasGCBHn/8cb355ptWl+d3oqKi9NZbb9UY/9Of/qTt27dr5MiRFlTl31atWqXk5GQ9+OCDGjRokPLz8/WHP/xB5eXlGj9+vNXl+aWXXnpJK1as0NixY5WYmKgDBw5o4cKFKikp0axZs6wu75IRlBoIl8ul1atXa968eVaX4vdcLpfS0tJ07733atq0aZKk3r17KywsTFOnTtWOHTv4C/MlOn36tDIyMvTwww9r4sSJkqSEhATt3LlTGRkZBKXLcOjQIc2ZM0etWrWyuhS/V1BQoMDAQA0ZMkSBgYFWl+P35s2bp65du2rJkiWy2+2SpJCQEM2ZM0cHDhxQu3btLK7Qv4SEhCgmJsZrbP369frHP/6hhQsXKjIy0qLK/Nc777yjHj166Nlnn5Vk/lwqKirSypUrCUq1UFpaqoyMDN1zzz16/vnnPeOtW7fWpEmTdO+996pjx44WVnjp+DNZA1FYWKjnnntOd911F2HpMp06dUpJSUm68847vcarfggdOHDAirL8WqNGjfTWW29p3LhxXuOBgYGqqKiwqKqG4dlnn1WfPn2UkJBgdSl+r6CgQJ06dSIk1YFjx44pPz9f9913nyckSdKQIUP08ccfE5LqQHl5uV544QUNGDBAw4YNs7ocv1RRUaGmTZt6jV177bU6fvy4RRX5t6KiIjmdTt1xxx1e43FxcXK5XMrLy7OostojKDUQN9xwg9atW6dnnnlG11xzjdXl+LXQ0FAlJyerZ8+eXuN/+9vfJEmdO3e2oiy/FhAQoC5duig8PFxut1tHjhzR0qVL9fnnn+v++++3ujy/tWrVKu3cuVPJyclWl9Ig7N69W4ZhaNy4cYqJiVF8fLxmz57Ns4m1UFhYKLfbreuuu07Tpk1TbGysYmNj9dRTT+nEiRNWl9cgvPbaazp8+LBfbmeqLx5++GF99tlnysrK0smTJ5WXl6fVq1dr9OjRVpfml5o3by7JfAzkfMXFxZKkb7/99orXdLnYetdAhIWFWV1Cg7Z161YtW7ZMgwcPJihdpjVr1mj69OmSpP79+2vEiBEWV+SfSkpKNHfuXM2dO9fzwwm153K5tGfPHhmGoaeeekqPPfaYtm/frsWLF2vfvn3KyMjgWaVLUFpaKkmaNWuW+vXrpyVLlqioqEgLFizQgQMH9MYbb3A/L0NFRYVef/11jRgxQhEREVaX47eGDx+uf/7zn5oxY4ZnrG/fvoTPWurQoYN69OihxYsXq1WrVrrtttt04MABJScnKygoSGfOnLG6xEtGUAJ+wubNmzVp0iS1b99ec+bMsbocv3fLLbcoIyND33zzjf785z9r7NixyszMVKNGjawuzW+43W7NmjVL/fv319ChQ60up0Fwu91aunSpwsPDPXvo4+LiFB4erunTpysvL0/9+/e3uEr/UVlZKclsQFD1/82EhASFhobqN7/5jT777DPdfvvtVpbo1z744AP98MMPmjBhgtWl+LXJkydr69atmj59urp3767CwkItXrxYv/71r5WSkkLjplpYtGiRZs+erSlTpkgyd+lMnz5dS5YsUZMmTSyu7tIRlIB/IycnRzNnzlRkZKSWL1/Oyl0diIiIUEREhOLi4tSuXTs98sgjys3NVVJSktWl+Y2VK1eqsLBQa9askcPhkCRP61WHwyHDMPhr/SWy2+269dZba4wPGDBAkrmVjKD0nwsODpakGs8qVIWjgoICgtJlyM3NVefOndWlSxerS/FbW7du1aeffqoXXnhBY8aMkSTFx8erXbt2evTRR/XRRx/V+P7FTwsPD9eSJUtUVlamw4cPq3379jIMQ88995yaNWtmdXmXjJ+kwEWkp6dr2rRpiomJ0cqVK9WiRQurS/JbR48e1erVq2ucn1LVPfD777+3oiy/lZubq2PHjqlv376KiopSVFSU3n33XZWUlCgqKkopKSlWl+h3Dh06pLfffrvG92J5ebkk8wFv/Oc6dOggSTWatVQFe56lrb3Kykp99tlnNHC4TAcPHpQk9ejRw2s8Li5OkrR3794rXlNDkJOTo927dys0NFSdOnVSUFCQCgoK5HQ61a1bN6vLu2QEJeAC3nzzTc2fP1/Dhg3T8uXLa3TFwaU5c+aMZs6cqVWrVnmNV3XAuemmm6woy289//zzyszM9Pq444471KJFC2VmZuqee+6xukS/U1FRoeTk5Brn1Kxdu1aGYdRo7oJ/r2PHjmrTpo1ycnK8xv/+979Lknr16mVFWQ3Cnj17dPbsWb4nL9ONN94oydxef76tW7dKktq2bXvFa2oIUlNTlZaW5jX22muvKTQ09IKr9vUdW+8AH0eOHNHcuXPVpk0bPfDAA9q1a5fX6+3bt+fh+UvUrl073XXXXUpJSZFhGIqOjtaOHTuUmpqqvn37ql+/flaX6FeqfsCfLywsTEFBQZzxVUvt2rXT6NGjtWzZMgUFBSkmJkZbtmzRK6+8ovvvv/+C9xwXZ7PZNGPGDE2dOlVTp07VmDFj9PXXX2vBggUaOnSoX/5lub7Ys2ePJPndeTT1Tbdu3TR06FC99NJLOnHihG655Rbt27dPixYtUlRUlBITE60u0S89+OCD+t3vfqdOnTqpR48eWrt2rd577z0999xzCgkJsbq8S2ZzV21sR4OxceNGPfTQQ/rLX/7il+ndapmZmfrtb3970dfnzp2ru++++wpW1DBUVFRo+fLlevfdd3Xw4EG1aNFCSUlJeuyxxxQUFGR1eX5v5syZys/P14cffmh1KX7rxx9/VHp6urKzs3Xw4EG1bNlS99xzj8aPH+91FhD+cxs2bFBKSooKCwvVrFkzjRo1Sk8++ST/zV+GZcuW6Y9//KO++uormuBcpoqKCqWmpiorK0uHDx9W69atNXjwYD3++OOe5+xw6VasWKGMjAwdOXJEkZGRGj9+fI2zKf0FQQkAAAAAfPCMEgAAAAD4ICgBAAAAgA+CEgAAAAD4ICgBAAAAgA+CEgAAAAD4ICgBAAAAgA+CEgAAAAD4ICgBAAAAgA+CEgAAkgYOHKiZM2daXQYAoJ4gKAEAAACAD4ISAAAAAPggKAEAcAGZmZnq0qWLFi1aZHUpAAALEJQAAPCxdu1aJScna9KkSfrVr35ldTkAAAsQlAAAOM+GDRs0Y8YMTZw4UVOnTrW6HACARWxut9ttdREAAFht4MCBCg4O1v79+xUeHq7169fLMPh7IgBcrfgJAADAOXv27FHv3r1VUlKijIwMq8sBAFiIoAQAwDl9+/bVK6+8ojvvvFMvv/yyDh48aHVJAACLEJQAADinRYsWkqRnnnlGAQEBmj17tsUVAQCsQlACAMBHeHi4nnzySeXl5SkrK8vqcgAAFiAoAQBwAWPHjlX37t314osvqrS01OpyAABXGF3vAAAAAMAHK0oAAAAA4IOgBAAAAAA+CEoAAAAA4IOgBAAAAAA+CEoAAAAA4IOgBAAAAAA+CEoAAAAA4IOgBAAAAAA+CEoAAAAA4IOgBAAAAAA+CEoAAAAA4IOgBAAAAAA+CEoAAAAA4IOgBAAAAAA+/h98QQdm3oiGvwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 960x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize = (8, 5))\n",
    "plt.plot(K, Sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From above plot we can choose optimal K as 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1.97958735e-01  1.60628051e-02  3.16261075e-01 -3.13611333e-02\n",
      "   1.85583794e-02  5.31829366e-04  4.01974081e-03  1.08940611e-02\n",
      "   1.19991570e-03 -3.78870735e-03]\n",
      " [ 1.05582085e-01 -7.31493647e-02  1.72670827e-02  3.69448444e-03\n",
      "   1.76499953e-03 -4.44905063e-03 -9.44210048e-04  1.29285912e-03\n",
      "  -1.75554246e-04  7.69099316e-04]\n",
      " [-6.10351995e-03  1.30794379e-01  4.87323786e-03  2.30166600e-01\n",
      "   1.10145534e-01 -2.28524701e-02  6.69746933e-05 -6.41521694e-03\n",
      "   7.82407578e-03  3.06319625e-03]\n",
      " [ 6.74910688e-02  1.05658770e-01 -1.15571822e-03 -3.09429213e-02\n",
      "  -1.06701173e-02  7.23241776e-03 -5.30136907e-04  4.51631856e-03\n",
      "  -7.08225362e-04 -1.57910679e-04]\n",
      " [-7.39162602e-02 -1.06074425e-02 -2.70617884e-02 -6.97780813e-03\n",
      "  -6.76627323e-03  1.54195330e-03  5.08258923e-04 -2.54073147e-03\n",
      "  -3.23668199e-04 -4.10126578e-04]]\n"
     ]
    }
   ],
   "source": [
    "clusterer = KMeans(n_clusters=5,random_state=42).fit(df_pca)\n",
    "centers = clusterer.cluster_centers_\n",
    "c_preds = clusterer.predict(df_pca)\n",
    "print(centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualizing clustering among first two principal components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\archd\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "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>pc1</th>\n",
       "      <th>pc2</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.113443</td>\n",
       "      <td>0.039084</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.036988</td>\n",
       "      <td>0.108884</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.064282</td>\n",
       "      <td>0.103962</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.093210</td>\n",
       "      <td>0.054093</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.094629</td>\n",
       "      <td>-0.037051</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        pc1       pc2  cluster\n",
       "0 -0.113443  0.039084        4\n",
       "1 -0.036988  0.108884        3\n",
       "2  0.064282  0.103962        3\n",
       "3 -0.093210  0.054093        4\n",
       "4  0.094629 -0.037051        1"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df = df_pca.iloc[:, 0:2]\n",
    "temp_df.columns = [\"pc1\", \"pc2\"]\n",
    "temp_df['cluster'] = c_preds\n",
    "temp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize = (8, 5))\n",
    "ax = sns.scatterplot(data = temp_df, x = \"pc1\", y = \"pc2\", hue = \"cluster\")\n",
    "ax.set_xlabel(\"Principal Component 1\")\n",
    "ax.set_ylabel(\"Principal Component 2\")\n",
    "ax.set_title(\"Cluster Visualization\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top products per cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "cross_df['cluster'] = c_preds\n",
    "\n",
    "cluster1 = cross_df[cross_df.cluster == 0]\n",
    "cluster2 = cross_df[cross_df.cluster == 1]\n",
    "cluster3 = cross_df[cross_df.cluster == 2]\n",
    "cluster4 = cross_df[cross_df.cluster == 3]\n",
    "cluster5 = cross_df[cross_df.cluster == 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5428, 135)"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "aisle\n",
       "water seltzer sparkling water    20.933493\n",
       "fresh fruits                      3.334930\n",
       "soft drinks                       2.803242\n",
       "yogurt                            2.251290\n",
       "energy granola bars               1.554716\n",
       "chips pretzels                    1.344326\n",
       "tea                               1.331614\n",
       "milk                              1.326640\n",
       "packaged vegetables fruits        1.251474\n",
       "soy lactosefree                   1.084009\n",
       "dtype: float64"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster1.drop('cluster',axis=1).mean().sort_values(ascending=False)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(55784, 135)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "aisle\n",
       "fresh vegetables                 37.044726\n",
       "fresh fruits                     21.741252\n",
       "packaged vegetables fruits       12.024272\n",
       "yogurt                            6.156945\n",
       "packaged cheese                   5.017514\n",
       "fresh herbs                       4.151854\n",
       "milk                              4.000556\n",
       "soy lactosefree                   3.704700\n",
       "frozen produce                    3.301323\n",
       "water seltzer sparkling water     3.080059\n",
       "dtype: float64"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster2.drop('cluster',axis=1).mean().sort_values(ascending=False)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7948, 135)"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "aisle\n",
       "packaged produce                 18.354051\n",
       "fresh fruits                     10.877453\n",
       "packaged vegetables fruits        4.240186\n",
       "fresh vegetables                  3.105813\n",
       "water seltzer sparkling water     1.714519\n",
       "milk                              1.615627\n",
       "packaged cheese                   1.544162\n",
       "frozen produce                    1.144942\n",
       "chips pretzels                    1.139155\n",
       "nuts seeds dried fruit            1.033090\n",
       "dtype: float64"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster3.drop('cluster',axis=1).mean().sort_values(ascending=False)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(37949, 135)"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster4.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "aisle\n",
       "fresh fruits                     35.756357\n",
       "fresh vegetables                 15.053466\n",
       "packaged vegetables fruits       12.108804\n",
       "yogurt                            9.897520\n",
       "milk                              5.965269\n",
       "packaged cheese                   5.118000\n",
       "soy lactosefree                   3.779019\n",
       "water seltzer sparkling water     3.613666\n",
       "bread                             3.199057\n",
       "chips pretzels                    3.134496\n",
       "dtype: float64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster4.drop('cluster',axis=1).mean().sort_values(ascending=False)[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(99100, 135)"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster5.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "aisle\n",
       "fresh fruits                     9.766902\n",
       "fresh vegetables                 7.572129\n",
       "yogurt                           7.218274\n",
       "packaged vegetables fruits       5.999395\n",
       "packaged cheese                  4.931604\n",
       "chips pretzels                   4.481231\n",
       "milk                             4.252573\n",
       "water seltzer sparkling water    4.090071\n",
       "refrigerated                     3.257538\n",
       "ice cream ice                    3.098052\n",
       "dtype: float64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster5.drop('cluster',axis=1).mean().sort_values(ascending=False)[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Customer Segmentation Results:"
   ]
  },
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    "- Cluster 1 results into 5428 consumers having a very strong preference for water seltzer sparkling water aisle.\n",
    "- Cluster 2 results into 55784 consumers who mostly order fresh vegetables followed by fruits.\n",
    "- Cluster 3 results into 7948 consumers who buy packaged produce and fresh fruits mostly.\n",
    "- Cluster 4 results into 37949 consumers who have a very strong preference for fruits followed by fresh vegetables.\n",
    "- Cluster 5 results into 99100 consumers who orders products from many aisles. Their mean orders are low compared to other clusters which tells us that either they are not frequent users of Instacart or they are new users and do not have many orders yet. "
   ]
  },
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   "outputs": [],
   "source": []
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