Customer_Segmentation_Clustering-Müşteri Segmentasyon Kümeleme.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e488913b",
   "metadata": {},
   "source": [
    "# Customer_Segmentation_Clustering-\n",
    "# Müşteri Segmentasyon Kümeleme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8f8f21d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Satın Alma Alışkanlıkları "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d67fde95",
   "metadata": {},
   "outputs": [],
   "source": [
    "#KMeans En Yakın Komşu Kümelemesi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8e9935d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option(\"display.max_columns\",200)\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.metrics import silhouette_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c65374ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('PBL5recommendationdata.csv', encoding = \"latin-1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be1a37c2",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "58c6d668",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Customers.id</th>\n",
       "      <th>Customers.fname</th>\n",
       "      <th>Customers.lname</th>\n",
       "      <th>Customers.company</th>\n",
       "      <th>Customers.create_date</th>\n",
       "      <th>Customers.status</th>\n",
       "      <th>Customers.mailing</th>\n",
       "      <th>Customers.reminders</th>\n",
       "      <th>Customers.tax_exempt</th>\n",
       "      <th>Customers.account_id</th>\n",
       "      <th>Customers.sales_rep</th>\n",
       "      <th>Customers.rewards</th>\n",
       "      <th>Customers.profile_id</th>\n",
       "      <th>Customers.last_modified</th>\n",
       "      <th>Customers.customer_type</th>\n",
       "      <th>Orders.id</th>\n",
       "      <th>Orders.customer_id</th>\n",
       "      <th>Orders.fname</th>\n",
       "      <th>Orders.lname</th>\n",
       "      <th>Orders.company</th>\n",
       "      <th>Orders.order_number</th>\n",
       "      <th>Orders.reorder_id</th>\n",
       "      <th>Orders.external_source</th>\n",
       "      <th>Orders.external_id</th>\n",
       "      <th>Orders.currency</th>\n",
       "      <th>Orders.sales_rep</th>\n",
       "      <th>Orders.subtotal</th>\n",
       "      <th>Orders.tax</th>\n",
       "      <th>Orders.shipping</th>\n",
       "      <th>Orders.coupon_id</th>\n",
       "      <th>Orders.coupon_amount</th>\n",
       "      <th>Orders.gift_id</th>\n",
       "      <th>Orders.gift_amount</th>\n",
       "      <th>Orders.fee_name</th>\n",
       "      <th>Orders.fee_amount</th>\n",
       "      <th>Orders.discount_name</th>\n",
       "      <th>Orders.discount_amount</th>\n",
       "      <th>Orders.total</th>\n",
       "      <th>Orders.balance_due</th>\n",
       "      <th>Orders.shipping_carrier</th>\n",
       "      <th>Orders.shipping_method</th>\n",
       "      <th>Orders.shipping_trans</th>\n",
       "      <th>Orders.shipping_flags</th>\n",
       "      <th>Orders.weight</th>\n",
       "      <th>Orders.tracking</th>\n",
       "      <th>Orders.payment_status</th>\n",
       "      <th>Orders.payment_date</th>\n",
       "      <th>Orders.payment_user</th>\n",
       "      <th>Orders.payment_type</th>\n",
       "      <th>Orders.payment_method</th>\n",
       "      <th>Orders.payment_amount</th>\n",
       "      <th>Orders.purchase_order</th>\n",
       "      <th>Orders.payment_id</th>\n",
       "      <th>Orders.payment_code</th>\n",
       "      <th>Orders.payment_ref</th>\n",
       "      <th>Orders.status</th>\n",
       "      <th>Orders.placed_date</th>\n",
       "      <th>Orders.updated_date</th>\n",
       "      <th>Orders.shipped_date</th>\n",
       "      <th>Orders.comments</th>\n",
       "      <th>Orders.notes</th>\n",
       "      <th>Orders.registry_id</th>\n",
       "      <th>Orders.gift_message</th>\n",
       "      <th>Orders.website</th>\n",
       "      <th>Orders.mailing</th>\n",
       "      <th>Orders.flags</th>\n",
       "      <th>Orders.partial_ship</th>\n",
       "      <th>Orders.customer_type</th>\n",
       "      <th>Order_Items.id</th>\n",
       "      <th>Order_Items.parent</th>\n",
       "      <th>Order_Items.product_id</th>\n",
       "      <th>Order_Items.product_name</th>\n",
       "      <th>Order_Items.attributes</th>\n",
       "      <th>Order_Items.attribute_names</th>\n",
       "      <th>Order_Items.attribute_prices</th>\n",
       "      <th>Order_Items.qty</th>\n",
       "      <th>Order_Items.price</th>\n",
       "      <th>Order_Items.cost</th>\n",
       "      <th>Order_Items.registry_item</th>\n",
       "      <th>Order_Items.related_id</th>\n",
       "      <th>Order_Items.reorder_frequency</th>\n",
       "      <th>Order_Items.account_id</th>\n",
       "      <th>Order_Items.flags</th>\n",
       "      <th>Products.id</th>\n",
       "      <th>Products.status</th>\n",
       "      <th>Products.product_type</th>\n",
       "      <th>Products.template</th>\n",
       "      <th>Products.vendor</th>\n",
       "      <th>Products.import_id</th>\n",
       "      <th>Products.name</th>\n",
       "      <th>Products.display_name</th>\n",
       "      <th>Products.menu_name</th>\n",
       "      <th>Products.list_price</th>\n",
       "      <th>Products.price</th>\n",
       "      <th>Products.sale_price</th>\n",
       "      <th>Products.cost</th>\n",
       "      <th>Products.flags</th>\n",
       "      <th>Products.left_flag</th>\n",
       "      <th>Products.right_flag</th>\n",
       "      <th>Products.last_modified</th>\n",
       "      <th>Products.taxable</th>\n",
       "      <th>Products.shopping_gtin</th>\n",
       "      <th>Products.shopping_brand</th>\n",
       "      <th>Products.shopping_mpn</th>\n",
       "      <th>Products.shopping_gender</th>\n",
       "      <th>Products.shopping_color</th>\n",
       "      <th>Products.shopping_age</th>\n",
       "      <th>Products.shopping_flags</th>\n",
       "      <th>Products.amazon_asin</th>\n",
       "      <th>Products.amazon_type</th>\n",
       "      <th>Products.amazon_item_type</th>\n",
       "      <th>Products.amazon_price</th>\n",
       "      <th>Products.google_shopping_id</th>\n",
       "      <th>Products.google_shopping_type</th>\n",
       "      <th>Products.google_shopping_cat</th>\n",
       "      <th>Products.google_adwords</th>\n",
       "      <th>Products.shopping_cat</th>\n",
       "      <th>Products.shopping_type</th>\n",
       "      <th>Products.pricegrabber_cat</th>\n",
       "      <th>Products.shopzilla_cat</th>\n",
       "      <th>Products.thefind_cat</th>\n",
       "      <th>Products.quickbooks_id</th>\n",
       "      <th>Products.qb_edit_sequence</th>\n",
       "      <th>Products.price_break_type</th>\n",
       "      <th>Products.price_breaks</th>\n",
       "      <th>Products.short_description</th>\n",
       "      <th>Products.long_description</th>\n",
       "      <th>Products.websites</th>\n",
       "      <th>Products.video</th>\n",
       "      <th>Products.audio</th>\n",
       "      <th>Products.seo_title</th>\n",
       "      <th>Products.seo_description</th>\n",
       "      <th>Products.seo_keywords</th>\n",
       "      <th>Products.seo_header</th>\n",
       "      <th>Products.seo_footer</th>\n",
       "      <th>Products.seo_url</th>\n",
       "      <th>Products.seo_category</th>\n",
       "      <th>Products.unit</th>\n",
       "      <th>Products.packaging</th>\n",
       "      <th>Products.display_packaging</th>\n",
       "      <th>Products.multiple</th>\n",
       "      <th>Products.length</th>\n",
       "      <th>Products.width</th>\n",
       "      <th>Products.height</th>\n",
       "      <th>Products.rx</th>\n",
       "      <th>Products.latex</th>\n",
       "      <th>Products.upc</th>\n",
       "      <th>Products.msds_link</th>\n",
       "      <th>Products.msds_label</th>\n",
       "      <th>Products.lit_link</th>\n",
       "      <th>Products.lit_label</th>\n",
       "      <th>Products.hcpcs</th>\n",
       "      <th>Products.case_qty</th>\n",
       "      <th>Products.markup</th>\n",
       "      <th>Products.override_markup</th>\n",
       "      <th>Products.notes</th>\n",
       "      <th>Products.import_flags</th>\n",
       "      <th>Products.map_price</th>\n",
       "      <th>Products.features_title</th>\n",
       "      <th>Products.warranty</th>\n",
       "      <th>Products.hygienic</th>\n",
       "      <th>Products.default_quantity</th>\n",
       "      <th>Products.user_size</th>\n",
       "      <th>Products.assembly</th>\n",
       "      <th>Products.installation</th>\n",
       "      <th>Products.shipping_length</th>\n",
       "      <th>Products.shipping_width</th>\n",
       "      <th>Products.shipping_height</th>\n",
       "      <th>Products.shipping_weight</th>\n",
       "      <th>Products.handling_time</th>\n",
       "      <th>Products.rotation_link</th>\n",
       "      <th>Products.google_shopping_label</th>\n",
       "      <th>Products.product_option</th>\n",
       "      <th>Products.size</th>\n",
       "      <th>Products.material</th>\n",
       "      <th>Products.arm_style</th>\n",
       "      <th>Products.leg_style</th>\n",
       "      <th>Products.seat_size</th>\n",
       "      <th>Products.family_id</th>\n",
       "      <th>Products.saved_status</th>\n",
       "      <th>Products.freight_cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>797</td>\n",
       "      <td>Christy</td>\n",
       "      <td>Dill</td>\n",
       "      <td>Company0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1437764306</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3758</td>\n",
       "      <td>797</td>\n",
       "      <td>Christy</td>\n",
       "      <td>Dill</td>\n",
       "      <td>Company0</td>\n",
       "      <td>3758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.95</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2.86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fedex</td>\n",
       "      <td>11|Ground</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.7204E+14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.426019e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>authorize.net</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6993607863</td>\n",
       "      <td>510142</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1426019099</td>\n",
       "      <td>1.438868e+09</td>\n",
       "      <td>1.426101e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Insured By Eye4Fraud</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5284</td>\n",
       "      <td>3758</td>\n",
       "      <td>2310.0</td>\n",
       "      <td>Basic Rollators, Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>57.20</td>\n",
       "      <td>44.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2310.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sub-product-detail.html</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Basic Steel Rollators,Green</td>\n",
       "      <td>Basic Lightweight Rollators For Adults, With S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.70</td>\n",
       "      <td>57.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.463163e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.088440e+13</td>\n",
       "      <td>MEDLINE</td>\n",
       "      <td>MDS86850EGS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62.0</td>\n",
       "      <td>B00I6GQE0A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>health-care-products</td>\n",
       "      <td>NaN</td>\n",
       "      <td>generic/online%3Aen%3AUS%3A2310</td>\n",
       "      <td>Walking Aids &gt; Rollators, &amp; Walkers &gt; Rollators</td>\n",
       "      <td>Health &amp; Beauty &gt; Health Care</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8000064C-1434298761</td>\n",
       "      <td>1.450325e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ROLLATOR,BASIC,STEEL,6\",GREEN</td>\n",
       "      <td>&lt;ul&gt;&lt;li&gt;  Classically designed, value priced&lt;/...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basic Lightweight Rollators For Adults, With S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basic-Rollators-For-Adults-With-Seat-Green-6-W...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>EA</td>\n",
       "      <td>1 Each / Each</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 EA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E0149 +E0156</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>136.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.80</td>\n",
       "      <td>7.50</td>\n",
       "      <td>30.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PF61071</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>John</td>\n",
       "      <td>Smith</td>\n",
       "      <td>Company1</td>\n",
       "      <td>1386089139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1437764354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "      <td>John</td>\n",
       "      <td>Smith</td>\n",
       "      <td>Company1</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fedex</td>\n",
       "      <td>11|Ground</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.28597E+14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.386090e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>authorize.net</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1386090455</td>\n",
       "      <td>1.440529e+09</td>\n",
       "      <td>1.386103e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31</td>\n",
       "      <td>23</td>\n",
       "      <td>177.0</td>\n",
       "      <td>Urinary Drain Bags,0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sub-product-detail.html</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Urinary Drain Bags</td>\n",
       "      <td>Urinary Drain Bags</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.41</td>\n",
       "      <td>10.29</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.87</td>\n",
       "      <td>65.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.462370e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.008020e+13</td>\n",
       "      <td>MEDLINE</td>\n",
       "      <td>DYNC1674H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62.0</td>\n",
       "      <td>B000QF7Y76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>health-care-products</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Incontinence, Urology &amp; Ostomy &gt; Urology &gt; Dra...</td>\n",
       "      <td>Health &amp; Beauty &gt; Health Care</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>80008C35-1438901283</td>\n",
       "      <td>1.450322e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BAG,DRAINAGE,UROLOGY,2000ML,ANTI REFLUX</td>\n",
       "      <td>&lt;ul&gt;&lt;li&gt;  Only Medline drain bags have a slide...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Urinary Drain Bags | MEDLINE - DYNC1674H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Urinary-Drain-Bags0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>EA</td>\n",
       "      <td>1 Each / Each</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 EA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rx</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://medline360.medline.com:443/irj/servlet...</td>\n",
       "      <td>508f2d75-582e-2e10-2eab-d83980a9b1d0</td>\n",
       "      <td>A4357</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>OFF sale cause it is an RX item</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PF02132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>John</td>\n",
       "      <td>Smith</td>\n",
       "      <td>Company1</td>\n",
       "      <td>1386089139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1437764354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9531</td>\n",
       "      <td>3</td>\n",
       "      <td>John</td>\n",
       "      <td>Smith</td>\n",
       "      <td>Company1</td>\n",
       "      <td>9531</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>manual</td>\n",
       "      <td>0|Standard Shipping</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.449604e+09</td>\n",
       "      <td>genlee166</td>\n",
       "      <td>authorize.net</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1449603652</td>\n",
       "      <td>1.450213e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>test order</td>\n",
       "      <td>Test</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11655</td>\n",
       "      <td>9531</td>\n",
       "      <td>1.0</td>\n",
       "      <td>SensiCare Nitrile Exam Gloves, Blue, XX-Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>68.78</td>\n",
       "      <td>52.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sub-product-detail.html</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>SensiCare Nitrile Exam Gloves,Blue,XX-Large</td>\n",
       "      <td>SensiCare Nitrile Exam Gloves, Blue, XX-Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.29</td>\n",
       "      <td>68.78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.50</td>\n",
       "      <td>32896.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.463163e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.008020e+13</td>\n",
       "      <td>MEDLINE</td>\n",
       "      <td>484805</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Blue</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62.0</td>\n",
       "      <td>B002209AOI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>health-care-products</td>\n",
       "      <td>NaN</td>\n",
       "      <td>generic/online%3Aen%3AUS%3A1</td>\n",
       "      <td>Apparel &gt; Gloves &gt; Nonsterile PF LF Synthetic ...</td>\n",
       "      <td>Health &amp; Beauty &gt; Health Care</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>800087BB-1438898332</td>\n",
       "      <td>1.450321e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GLOVE,EXAM,NITRILE,BLUE,FINGRTIP,TXT,XXL</td>\n",
       "      <td>&lt;ul&gt;&lt;li&gt; SensiCare&amp;reg; nitrile exam gloves fe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nitrile Exam Gloves, Blue, XX-Large | MEDLINE ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SensiCare-Nitrile-Exam-GlovesBlueXX-Large</td>\n",
       "      <td>0.0</td>\n",
       "      <td>CS</td>\n",
       "      <td>800 Each / Case</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 CS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NO GOVERNMENT OR SUPPLIER HCPCS CODE VERIFICATION</td>\n",
       "      <td>800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.23</td>\n",
       "      <td>10.04</td>\n",
       "      <td>10.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 x Extra large</td>\n",
       "      <td>Nitrile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PF00342</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>James</td>\n",
       "      <td>Anderson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1386780263</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1437762646</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>James</td>\n",
       "      <td>Anderson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ebay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11|Ground</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.96468E+14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.386780e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>29.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1386780263</td>\n",
       "      <td>1.440529e+09</td>\n",
       "      <td>1.386800e+09</td>\n",
       "      <td>ebay order\\rpaid by pay pal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1816</td>\n",
       "      <td>29</td>\n",
       "      <td>983.0</td>\n",
       "      <td>Basket for 2-Button Walkers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>19.56</td>\n",
       "      <td>12.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>983.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sub-product-detail.html</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Basket for 2-Button Walkers</td>\n",
       "      <td>Basket for 2-Button Walkers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.38</td>\n",
       "      <td>19.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.462595e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MEDLINE</td>\n",
       "      <td>MDS86615KH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62.0</td>\n",
       "      <td>B00083DG00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>health-care-products</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Walking Aids &gt; Rollators, &amp; Walkers &gt; Walkers ...</td>\n",
       "      <td>Health &amp; Beauty &gt; Health Care</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>8000065E-1434298780</td>\n",
       "      <td>1.450323e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BASKET,WALKER,FOR 2 BUTTON WALK</td>\n",
       "      <td>&lt;ul&gt;&lt;li&gt; This wire basket attaches to almost a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basket for 2-Button Walkers | MEDLINE - MDS866...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basket-for-2-Button-Walkers-2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>EA</td>\n",
       "      <td>1 Each / Each</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 EA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>8.019675e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A9270</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.60</td>\n",
       "      <td>7.80</td>\n",
       "      <td>18.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PF04970</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Abraham</td>\n",
       "      <td>Pollak</td>\n",
       "      <td>Company3</td>\n",
       "      <td>1386861599</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1437764316</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>Abraham</td>\n",
       "      <td>Pollak</td>\n",
       "      <td>Company3</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fedex</td>\n",
       "      <td>11|Ground</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.87398E+14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.386862e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>46.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1386861599</td>\n",
       "      <td>1.440529e+09</td>\n",
       "      <td>1.386876e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40</td>\n",
       "      <td>30</td>\n",
       "      <td>991.0</td>\n",
       "      <td>Tens Units</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>36.05</td>\n",
       "      <td>25.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>991.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sub-product-detail.html</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>TENS 3000 Analog Unit</td>\n",
       "      <td>TENS 3000 Analog Unit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.47</td>\n",
       "      <td>36.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.462370e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ROSCOE MEDICAL INC</td>\n",
       "      <td>MDS86710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>health-care-products</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Physical Therapy &gt; Electronic Muscle Stimulation</td>\n",
       "      <td>Health &amp; Beauty &gt; Health Care</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>Health &amp; Beauty &gt; Medical Supplies &gt; Medical Aids</td>\n",
       "      <td>80008B12-1438900627</td>\n",
       "      <td>1.450323e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEVICE,TENS UNIT,TENS 1000,DUAL CH</td>\n",
       "      <td>&lt;ul&gt;&lt;li&gt; The TENS 3000&lt;sup&gt;TM&lt;/sup&gt; analog uni...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TENS 3000 Analog Unit | ROSCOE MEDICAL INC - M...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tens-Units</td>\n",
       "      <td>0.0</td>\n",
       "      <td>EA</td>\n",
       "      <td>1 Each / Each</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 EA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rx</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E0730</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>OFF sale cause it is an RX item</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.50</td>\n",
       "      <td>2.75</td>\n",
       "      <td>12.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PF03045</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Customers.id Customers.fname Customers.lname Customers.company  \\\n",
       "0           797         Christy            Dill          Company0   \n",
       "1             3            John           Smith          Company1   \n",
       "2             3            John           Smith          Company1   \n",
       "3             4           James        Anderson               NaN   \n",
       "4             5         Abraham          Pollak          Company3   \n",
       "\n",
       "   Customers.create_date  Customers.status  Customers.mailing  \\\n",
       "0             1426018724               NaN                NaN   \n",
       "1             1386089139               NaN                NaN   \n",
       "2             1386089139               NaN                NaN   \n",
       "3             1386780263               NaN                NaN   \n",
       "4             1386861599               0.0                0.0   \n",
       "\n",
       "   Customers.reminders  Customers.tax_exempt  Customers.account_id  \\\n",
       "0                  NaN                   NaN                   NaN   \n",
       "1                  NaN                   NaN                   NaN   \n",
       "2                  NaN                   NaN                   NaN   \n",
       "3                  NaN                   NaN                   NaN   \n",
       "4                  NaN                   NaN                   NaN   \n",
       "\n",
       "   Customers.sales_rep  Customers.rewards  Customers.profile_id  \\\n",
       "0                  NaN                NaN                   NaN   \n",
       "1                  NaN                NaN                   NaN   \n",
       "2                  NaN                NaN                   NaN   \n",
       "3                  NaN                NaN                   NaN   \n",
       "4                  NaN                NaN                   NaN   \n",
       "\n",
       "   Customers.last_modified  Customers.customer_type  Orders.id  \\\n",
       "0               1437764306                      0.0       3758   \n",
       "1               1437764354                      0.0         23   \n",
       "2               1437764354                      0.0       9531   \n",
       "3               1437762646                      0.0         29   \n",
       "4               1437764316                      0.0         30   \n",
       "\n",
       "   Orders.customer_id Orders.fname Orders.lname Orders.company  \\\n",
       "0                 797      Christy         Dill       Company0   \n",
       "1                   3         John        Smith       Company1   \n",
       "2                   3         John        Smith       Company1   \n",
       "3                   4        James     Anderson            NaN   \n",
       "4                   5      Abraham       Pollak       Company3   \n",
       "\n",
       "  Orders.order_number  Orders.reorder_id Orders.external_source  \\\n",
       "0                3758                NaN                    NaN   \n",
       "1                  23                NaN                    NaN   \n",
       "2                9531                NaN                    NaN   \n",
       "3                  29                NaN                   Ebay   \n",
       "4                  30                NaN                    NaN   \n",
       "\n",
       "   Orders.external_id Orders.currency  Orders.sales_rep  Orders.subtotal  \\\n",
       "0                 NaN             USD               NaN            57.20   \n",
       "1                 NaN             USD               NaN            20.00   \n",
       "2                 NaN             USD               NaN            68.78   \n",
       "3                 NaN             USD               NaN            19.56   \n",
       "4                 NaN             USD               NaN            36.05   \n",
       "\n",
       "   Orders.tax  Orders.shipping  Orders.coupon_id  Orders.coupon_amount  \\\n",
       "0         0.0             9.95              13.0                  2.86   \n",
       "1         NaN             9.99               NaN                   NaN   \n",
       "2         0.0             9.95               NaN                   NaN   \n",
       "3         0.0             9.95               NaN                   NaN   \n",
       "4         NaN             9.95               NaN                   NaN   \n",
       "\n",
       "   Orders.gift_id  Orders.gift_amount Orders.fee_name  Orders.fee_amount  \\\n",
       "0             NaN                 NaN             NaN                NaN   \n",
       "1             NaN                 NaN             NaN                NaN   \n",
       "2             NaN                 NaN             NaN                NaN   \n",
       "3             NaN                 NaN             NaN               0.04   \n",
       "4             NaN                 NaN             NaN                NaN   \n",
       "\n",
       "  Orders.discount_name  Orders.discount_amount  Orders.total  \\\n",
       "0                  NaN                     NaN         64.29   \n",
       "1                  NaN                     NaN         29.99   \n",
       "2                  NaN                     NaN         78.73   \n",
       "3                  NaN                     NaN         29.55   \n",
       "4                  NaN                     NaN         46.00   \n",
       "\n",
       "   Orders.balance_due Orders.shipping_carrier Orders.shipping_method  \\\n",
       "0                 NaN                   fedex              11|Ground   \n",
       "1                 NaN                   fedex              11|Ground   \n",
       "2                 NaN                  manual    0|Standard Shipping   \n",
       "3                 NaN                     NaN              11|Ground   \n",
       "4                 NaN                   fedex              11|Ground   \n",
       "\n",
       "   Orders.shipping_trans  Orders.shipping_flags  Orders.weight  \\\n",
       "0                    NaN                    NaN            NaN   \n",
       "1                    NaN                    NaN            NaN   \n",
       "2                    NaN                    NaN            NaN   \n",
       "3                    NaN                    NaN            NaN   \n",
       "4                    NaN                    NaN            NaN   \n",
       "\n",
       "  Orders.tracking  Orders.payment_status  Orders.payment_date  \\\n",
       "0      5.7204E+14                    3.0         1.426019e+09   \n",
       "1     1.28597E+14                    3.0         1.386090e+09   \n",
       "2             NaN                    3.0         1.449604e+09   \n",
       "3     7.96468E+14                    3.0         1.386780e+09   \n",
       "4     6.87398E+14                    3.0         1.386862e+09   \n",
       "\n",
       "  Orders.payment_user Orders.payment_type Orders.payment_method  \\\n",
       "0                 NaN       authorize.net                   NaN   \n",
       "1                 NaN       authorize.net                   NaN   \n",
       "2           genlee166       authorize.net                   NaN   \n",
       "3                 NaN                 NaN           Credit Card   \n",
       "4                 NaN                 NaN           Credit Card   \n",
       "\n",
       "   Orders.payment_amount  Orders.purchase_order Orders.payment_id  \\\n",
       "0                  64.29                    NaN        6993607863   \n",
       "1                  29.99                    NaN                 0   \n",
       "2                  78.73                    NaN                 0   \n",
       "3                  29.55                    NaN               NaN   \n",
       "4                  46.00                    NaN               NaN   \n",
       "\n",
       "  Orders.payment_code  Orders.payment_ref  Orders.status  Orders.placed_date  \\\n",
       "0              510142                 NaN              1          1426019099   \n",
       "1                   0                 NaN              1          1386090455   \n",
       "2                   0                 NaN              3          1449603652   \n",
       "3                 NaN                 NaN              1          1386780263   \n",
       "4                 NaN                 NaN              1          1386861599   \n",
       "\n",
       "   Orders.updated_date  Orders.shipped_date              Orders.comments  \\\n",
       "0         1.438868e+09         1.426101e+09                          NaN   \n",
       "1         1.440529e+09         1.386103e+09                          NaN   \n",
       "2         1.450213e+09                  NaN                   test order   \n",
       "3         1.440529e+09         1.386800e+09  ebay order\\rpaid by pay pal   \n",
       "4         1.440529e+09         1.386876e+09                          NaN   \n",
       "\n",
       "           Orders.notes  Orders.registry_id  Orders.gift_message  \\\n",
       "0  Insured By Eye4Fraud                 NaN                  NaN   \n",
       "1                   NaN                 NaN                  NaN   \n",
       "2                  Test                 NaN                  NaN   \n",
       "3                   NaN                 NaN                  NaN   \n",
       "4                   NaN                 NaN                  NaN   \n",
       "\n",
       "   Orders.website  Orders.mailing  Orders.flags  Orders.partial_ship  \\\n",
       "0             NaN             NaN           NaN                  NaN   \n",
       "1             NaN             NaN           NaN                  NaN   \n",
       "2             NaN             NaN           NaN                  NaN   \n",
       "3             NaN             NaN           NaN                  NaN   \n",
       "4             NaN             NaN           NaN                  NaN   \n",
       "\n",
       "   Orders.customer_type  Order_Items.id  Order_Items.parent  \\\n",
       "0                   0.0            5284                3758   \n",
       "1                   0.0              31                  23   \n",
       "2                   0.0           11655                9531   \n",
       "3                   0.0            1816                  29   \n",
       "4                   0.0              40                  30   \n",
       "\n",
       "   Order_Items.product_id                       Order_Items.product_name  \\\n",
       "0                  2310.0                         Basic Rollators, Green   \n",
       "1                   177.0                       Urinary Drain Bags,0.000   \n",
       "2                     1.0  SensiCare Nitrile Exam Gloves, Blue, XX-Large   \n",
       "3                   983.0                    Basket for 2-Button Walkers   \n",
       "4                   991.0                                     Tens Units   \n",
       "\n",
       "   Order_Items.attributes Order_Items.attribute_names  \\\n",
       "0                     NaN                         NaN   \n",
       "1                     NaN                         NaN   \n",
       "2                     NaN                         NaN   \n",
       "3                     NaN                         NaN   \n",
       "4                     NaN                         NaN   \n",
       "\n",
       "   Order_Items.attribute_prices  Order_Items.qty  Order_Items.price  \\\n",
       "0                           NaN                1              57.20   \n",
       "1                           NaN                4               5.00   \n",
       "2                           NaN                1              68.78   \n",
       "3                           NaN                1              19.56   \n",
       "4                           NaN                1              36.05   \n",
       "\n",
       "   Order_Items.cost  Order_Items.registry_item  Order_Items.related_id  \\\n",
       "0             44.00                        NaN                     NaN   \n",
       "1              1.87                        NaN                     NaN   \n",
       "2             52.50                        NaN                     NaN   \n",
       "3             12.62                        NaN                     NaN   \n",
       "4             25.75                        NaN                     NaN   \n",
       "\n",
       "   Order_Items.reorder_frequency  Order_Items.account_id  Order_Items.flags  \\\n",
       "0                            NaN                     NaN                NaN   \n",
       "1                            NaN                     NaN                2.0   \n",
       "2                            NaN                     NaN                NaN   \n",
       "3                            NaN                     NaN                NaN   \n",
       "4                            NaN                     NaN                NaN   \n",
       "\n",
       "   Products.id  Products.status  Products.product_type  \\\n",
       "0       2310.0              0.0                    NaN   \n",
       "1        177.0              1.0                    NaN   \n",
       "2          1.0              0.0                    NaN   \n",
       "3        983.0              0.0                    NaN   \n",
       "4        991.0              1.0                    NaN   \n",
       "\n",
       "         Products.template  Products.vendor  Products.import_id  \\\n",
       "0  sub-product-detail.html              1.0                 3.0   \n",
       "1  sub-product-detail.html              1.0                 3.0   \n",
       "2  sub-product-detail.html              1.0                 3.0   \n",
       "3  sub-product-detail.html              1.0                 3.0   \n",
       "4  sub-product-detail.html              1.0                 3.0   \n",
       "\n",
       "                                 Products.name  \\\n",
       "0                  Basic Steel Rollators,Green   \n",
       "1                           Urinary Drain Bags   \n",
       "2  SensiCare Nitrile Exam Gloves,Blue,XX-Large   \n",
       "3                  Basket for 2-Button Walkers   \n",
       "4                        TENS 3000 Analog Unit   \n",
       "\n",
       "                               Products.display_name  Products.menu_name  \\\n",
       "0  Basic Lightweight Rollators For Adults, With S...                 NaN   \n",
       "1                                 Urinary Drain Bags                 NaN   \n",
       "2      SensiCare Nitrile Exam Gloves, Blue, XX-Large                 NaN   \n",
       "3                        Basket for 2-Button Walkers                 NaN   \n",
       "4                              TENS 3000 Analog Unit                 NaN   \n",
       "\n",
       "   Products.list_price  Products.price  Products.sale_price  Products.cost  \\\n",
       "0                80.70           57.64                  NaN          44.00   \n",
       "1                14.41           10.29                  5.0           1.87   \n",
       "2                96.29           68.78                  NaN          52.50   \n",
       "3                27.38           19.56                  NaN          12.62   \n",
       "4                50.47           36.05                  NaN          25.75   \n",
       "\n",
       "   Products.flags  Products.left_flag  Products.right_flag  \\\n",
       "0             0.0                 NaN                  NaN   \n",
       "1            65.0                 NaN                  NaN   \n",
       "2         32896.0                 NaN                  NaN   \n",
       "3             0.0                 NaN                  NaN   \n",
       "4             0.0                 NaN                  NaN   \n",
       "\n",
       "   Products.last_modified  Products.taxable  Products.shopping_gtin  \\\n",
       "0            1.463163e+09               1.0            1.088440e+13   \n",
       "1            1.462370e+09               1.0            1.008020e+13   \n",
       "2            1.463163e+09               1.0            4.008020e+13   \n",
       "3            1.462595e+09               1.0                     NaN   \n",
       "4            1.462370e+09               1.0                     NaN   \n",
       "\n",
       "  Products.shopping_brand Products.shopping_mpn Products.shopping_gender  \\\n",
       "0                 MEDLINE           MDS86850EGS                      NaN   \n",
       "1                 MEDLINE             DYNC1674H                      NaN   \n",
       "2                 MEDLINE                484805                      NaN   \n",
       "3                 MEDLINE            MDS86615KH                      NaN   \n",
       "4      ROSCOE MEDICAL INC              MDS86710                      NaN   \n",
       "\n",
       "  Products.shopping_color Products.shopping_age  Products.shopping_flags  \\\n",
       "0                   Green                   NaN                     62.0   \n",
       "1                     NaN                   NaN                     62.0   \n",
       "2                    Blue                   NaN                     62.0   \n",
       "3                     NaN                   NaN                     62.0   \n",
       "4                     NaN                   NaN                     62.0   \n",
       "\n",
       "  Products.amazon_asin  Products.amazon_type Products.amazon_item_type  \\\n",
       "0           B00I6GQE0A                   NaN      health-care-products   \n",
       "1           B000QF7Y76                   NaN      health-care-products   \n",
       "2           B002209AOI                   NaN      health-care-products   \n",
       "3           B00083DG00                   NaN      health-care-products   \n",
       "4                  NaN                   NaN      health-care-products   \n",
       "\n",
       "   Products.amazon_price      Products.google_shopping_id  \\\n",
       "0                    NaN  generic/online%3Aen%3AUS%3A2310   \n",
       "1                    NaN                              NaN   \n",
       "2                    NaN     generic/online%3Aen%3AUS%3A1   \n",
       "3                    NaN                              NaN   \n",
       "4                    NaN                              NaN   \n",
       "\n",
       "                       Products.google_shopping_type  \\\n",
       "0    Walking Aids > Rollators, & Walkers > Rollators   \n",
       "1  Incontinence, Urology & Ostomy > Urology > Dra...   \n",
       "2  Apparel > Gloves > Nonsterile PF LF Synthetic ...   \n",
       "3  Walking Aids > Rollators, & Walkers > Walkers ...   \n",
       "4   Physical Therapy > Electronic Muscle Stimulation   \n",
       "\n",
       "    Products.google_shopping_cat  Products.google_adwords  \\\n",
       "0  Health & Beauty > Health Care                      NaN   \n",
       "1  Health & Beauty > Health Care                      NaN   \n",
       "2  Health & Beauty > Health Care                      NaN   \n",
       "3  Health & Beauty > Health Care                      NaN   \n",
       "4  Health & Beauty > Health Care                      NaN   \n",
       "\n",
       "   Products.shopping_cat Products.shopping_type  \\\n",
       "0                    NaN                    NaN   \n",
       "1                  199.0          Miscellaneous   \n",
       "2                  199.0          Miscellaneous   \n",
       "3                  199.0          Miscellaneous   \n",
       "4                  199.0          Miscellaneous   \n",
       "\n",
       "                           Products.pricegrabber_cat  Products.shopzilla_cat  \\\n",
       "0                                                NaN                     NaN   \n",
       "1  Health & Beauty > Medical Supplies > Medical Aids                 22005.0   \n",
       "2  Health & Beauty > Medical Supplies > Medical Aids                 22005.0   \n",
       "3  Health & Beauty > Medical Supplies > Medical Aids                 22005.0   \n",
       "4  Health & Beauty > Medical Supplies > Medical Aids                 22005.0   \n",
       "\n",
       "                                Products.thefind_cat Products.quickbooks_id  \\\n",
       "0                                                NaN    8000064C-1434298761   \n",
       "1  Health & Beauty > Medical Supplies > Medical Aids    80008C35-1438901283   \n",
       "2  Health & Beauty > Medical Supplies > Medical Aids    800087BB-1438898332   \n",
       "3  Health & Beauty > Medical Supplies > Medical Aids    8000065E-1434298780   \n",
       "4  Health & Beauty > Medical Supplies > Medical Aids    80008B12-1438900627   \n",
       "\n",
       "   Products.qb_edit_sequence  Products.price_break_type  \\\n",
       "0               1.450325e+09                        NaN   \n",
       "1               1.450322e+09                        NaN   \n",
       "2               1.450321e+09                        NaN   \n",
       "3               1.450323e+09                        NaN   \n",
       "4               1.450323e+09                        NaN   \n",
       "\n",
       "   Products.price_breaks                Products.short_description  \\\n",
       "0                    NaN             ROLLATOR,BASIC,STEEL,6\",GREEN   \n",
       "1                    NaN   BAG,DRAINAGE,UROLOGY,2000ML,ANTI REFLUX   \n",
       "2                    NaN  GLOVE,EXAM,NITRILE,BLUE,FINGRTIP,TXT,XXL   \n",
       "3                    NaN           BASKET,WALKER,FOR 2 BUTTON WALK   \n",
       "4                    NaN        DEVICE,TENS UNIT,TENS 1000,DUAL CH   \n",
       "\n",
       "                           Products.long_description  Products.websites  \\\n",
       "0  <ul><li>  Classically designed, value priced</...                NaN   \n",
       "1  <ul><li>  Only Medline drain bags have a slide...                NaN   \n",
       "2  <ul><li> SensiCare&reg; nitrile exam gloves fe...                NaN   \n",
       "3  <ul><li> This wire basket attaches to almost a...                NaN   \n",
       "4  <ul><li> The TENS 3000<sup>TM</sup> analog uni...                NaN   \n",
       "\n",
       "  Products.video  Products.audio  \\\n",
       "0            NaN             NaN   \n",
       "1            NaN             NaN   \n",
       "2            NaN             NaN   \n",
       "3            NaN             NaN   \n",
       "4            NaN             NaN   \n",
       "\n",
       "                                  Products.seo_title Products.seo_description  \\\n",
       "0  Basic Lightweight Rollators For Adults, With S...                      NaN   \n",
       "1           Urinary Drain Bags | MEDLINE - DYNC1674H                      NaN   \n",
       "2  Nitrile Exam Gloves, Blue, XX-Large | MEDLINE ...                      NaN   \n",
       "3  Basket for 2-Button Walkers | MEDLINE - MDS866...                      NaN   \n",
       "4  TENS 3000 Analog Unit | ROSCOE MEDICAL INC - M...                      NaN   \n",
       "\n",
       "  Products.seo_keywords Products.seo_header  Products.seo_footer  \\\n",
       "0                   NaN                 NaN                  NaN   \n",
       "1                   NaN                 NaN                  NaN   \n",
       "2                   NaN                 NaN                  NaN   \n",
       "3                   NaN                 NaN                  NaN   \n",
       "4                   NaN                 NaN                  NaN   \n",
       "\n",
       "                                    Products.seo_url  Products.seo_category  \\\n",
       "0  Basic-Rollators-For-Adults-With-Seat-Green-6-W...                    0.0   \n",
       "1                             Urinary-Drain-Bags0000                    0.0   \n",
       "2          SensiCare-Nitrile-Exam-GlovesBlueXX-Large                    0.0   \n",
       "3                      Basket-for-2-Button-Walkers-2                    0.0   \n",
       "4                                         Tens-Units                    0.0   \n",
       "\n",
       "  Products.unit Products.packaging Products.display_packaging  \\\n",
       "0            EA      1 Each / Each                        NaN   \n",
       "1            EA      1 Each / Each                        NaN   \n",
       "2            CS    800 Each / Case                        NaN   \n",
       "3            EA      1 Each / Each                        NaN   \n",
       "4            EA      1 Each / Each                        NaN   \n",
       "\n",
       "  Products.multiple  Products.length  Products.width  Products.height  \\\n",
       "0              1 EA              NaN             NaN              NaN   \n",
       "1              1 EA              NaN             NaN              NaN   \n",
       "2              1 CS              NaN             NaN              NaN   \n",
       "3              1 EA              NaN             NaN              NaN   \n",
       "4              1 EA              NaN             NaN              NaN   \n",
       "\n",
       "  Products.rx Products.latex  Products.upc Products.msds_link  \\\n",
       "0         NaN            NaN           NaN                NaN   \n",
       "1          Rx            Yes           NaN                NaN   \n",
       "2         NaN            NaN           NaN                NaN   \n",
       "3         NaN            Yes  8.019675e+10                NaN   \n",
       "4          Rx            NaN           NaN                NaN   \n",
       "\n",
       "  Products.msds_label                                  Products.lit_link  \\\n",
       "0                 NaN                                                NaN   \n",
       "1                 NaN  https://medline360.medline.com:443/irj/servlet...   \n",
       "2                 NaN                                                NaN   \n",
       "3                 NaN                                                NaN   \n",
       "4                 NaN                                                NaN   \n",
       "\n",
       "                     Products.lit_label  \\\n",
       "0                                   NaN   \n",
       "1  508f2d75-582e-2e10-2eab-d83980a9b1d0   \n",
       "2                                   NaN   \n",
       "3                                   NaN   \n",
       "4                                   NaN   \n",
       "\n",
       "                                      Products.hcpcs  Products.case_qty  \\\n",
       "0                                       E0149 +E0156                1.0   \n",
       "1                                              A4357                1.0   \n",
       "2  NO GOVERNMENT OR SUPPLIER HCPCS CODE VERIFICATION              800.0   \n",
       "3                                              A9270                1.0   \n",
       "4                                              E0730                1.0   \n",
       "\n",
       "   Products.markup  Products.override_markup                   Products.notes  \\\n",
       "0              NaN                       0.0                              NaN   \n",
       "1              NaN                       0.0  OFF sale cause it is an RX item   \n",
       "2              NaN                       0.0                              NaN   \n",
       "3              NaN                       0.0                              NaN   \n",
       "4              NaN                       0.0  OFF sale cause it is an RX item   \n",
       "\n",
       "   Products.import_flags  Products.map_price Products.features_title  \\\n",
       "0                  136.0                 NaN                     NaN   \n",
       "1                    0.0                 NaN                     NaN   \n",
       "2                    NaN                 NaN                     NaN   \n",
       "3                    NaN                 NaN                     NaN   \n",
       "4                    NaN                 NaN                     NaN   \n",
       "\n",
       "  Products.warranty  Products.hygienic  Products.default_quantity  \\\n",
       "0               NaN                0.0                        NaN   \n",
       "1               NaN                0.0                        NaN   \n",
       "2               NaN                NaN                        NaN   \n",
       "3               NaN                NaN                        NaN   \n",
       "4               NaN                NaN                        NaN   \n",
       "\n",
       "  Products.user_size Products.assembly Products.installation  \\\n",
       "0                NaN               NaN                   NaN   \n",
       "1                NaN               NaN                   NaN   \n",
       "2                NaN               NaN                   NaN   \n",
       "3                NaN               NaN                   NaN   \n",
       "4                NaN               NaN                   NaN   \n",
       "\n",
       "   Products.shipping_length  Products.shipping_width  \\\n",
       "0                     24.80                     7.50   \n",
       "1                      8.00                     7.00   \n",
       "2                     13.23                    10.04   \n",
       "3                     10.60                     7.80   \n",
       "4                      8.50                     2.75   \n",
       "\n",
       "   Products.shipping_height  Products.shipping_weight Products.handling_time  \\\n",
       "0                     30.40                       NaN                    NaN   \n",
       "1                      1.50                       NaN                    NaN   \n",
       "2                     10.24                       NaN                    NaN   \n",
       "3                     18.50                       NaN                    NaN   \n",
       "4                     12.00                       NaN                    NaN   \n",
       "\n",
       "  Products.rotation_link  Products.google_shopping_label  \\\n",
       "0                    NaN                             NaN   \n",
       "1                    NaN                             NaN   \n",
       "2                    NaN                             NaN   \n",
       "3                    NaN                             NaN   \n",
       "4                    NaN                             NaN   \n",
       "\n",
       "  Products.product_option    Products.size Products.material  \\\n",
       "0                     NaN              NaN               NaN   \n",
       "1                     NaN              NaN               NaN   \n",
       "2                     NaN  2 x Extra large           Nitrile   \n",
       "3                     NaN              NaN               NaN   \n",
       "4                     NaN              NaN               NaN   \n",
       "\n",
       "  Products.arm_style  Products.leg_style Products.seat_size  \\\n",
       "0                NaN                 NaN                NaN   \n",
       "1                NaN                 NaN                NaN   \n",
       "2                NaN                 NaN                NaN   \n",
       "3                NaN                 NaN                NaN   \n",
       "4                NaN                 NaN                NaN   \n",
       "\n",
       "  Products.family_id  Products.saved_status  Products.freight_cost  \n",
       "0            PF61071                    0.0                    NaN  \n",
       "1            PF02132                    NaN                    NaN  \n",
       "2            PF00342                    0.0                    NaN  \n",
       "3            PF04970                    NaN                    NaN  \n",
       "4            PF03045                    NaN                    NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "55e42a19",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4194 entries, 0 to 4193\n",
      "Columns: 181 entries, Customers.id to Products.freight_cost\n",
      "dtypes: float64(98), int64(10), object(73)\n",
      "memory usage: 5.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "74555e03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customers.id</th>\n",
       "      <th>Customers.create_date</th>\n",
       "      <th>Customers.status</th>\n",
       "      <th>Customers.mailing</th>\n",
       "      <th>Customers.reminders</th>\n",
       "      <th>Customers.tax_exempt</th>\n",
       "      <th>Customers.account_id</th>\n",
       "      <th>Customers.sales_rep</th>\n",
       "      <th>Customers.rewards</th>\n",
       "      <th>Customers.profile_id</th>\n",
       "      <th>Customers.last_modified</th>\n",
       "      <th>Customers.customer_type</th>\n",
       "      <th>Orders.id</th>\n",
       "      <th>Orders.customer_id</th>\n",
       "      <th>Orders.reorder_id</th>\n",
       "      <th>Orders.external_id</th>\n",
       "      <th>Orders.sales_rep</th>\n",
       "      <th>Orders.subtotal</th>\n",
       "      <th>Orders.tax</th>\n",
       "      <th>Orders.shipping</th>\n",
       "      <th>Orders.coupon_id</th>\n",
       "      <th>Orders.coupon_amount</th>\n",
       "      <th>Orders.gift_id</th>\n",
       "      <th>Orders.gift_amount</th>\n",
       "      <th>Orders.fee_amount</th>\n",
       "      <th>Orders.discount_amount</th>\n",
       "      <th>Orders.total</th>\n",
       "      <th>Orders.balance_due</th>\n",
       "      <th>Orders.shipping_trans</th>\n",
       "      <th>Orders.shipping_flags</th>\n",
       "      <th>Orders.weight</th>\n",
       "      <th>Orders.payment_status</th>\n",
       "      <th>Orders.payment_date</th>\n",
       "      <th>Orders.payment_amount</th>\n",
       "      <th>Orders.purchase_order</th>\n",
       "      <th>Orders.payment_ref</th>\n",
       "      <th>Orders.status</th>\n",
       "      <th>Orders.placed_date</th>\n",
       "      <th>Orders.updated_date</th>\n",
       "      <th>Orders.shipped_date</th>\n",
       "      <th>Orders.registry_id</th>\n",
       "      <th>Orders.gift_message</th>\n",
       "      <th>Orders.website</th>\n",
       "      <th>Orders.mailing</th>\n",
       "      <th>Orders.flags</th>\n",
       "      <th>Orders.partial_ship</th>\n",
       "      <th>Orders.customer_type</th>\n",
       "      <th>Order_Items.id</th>\n",
       "      <th>Order_Items.parent</th>\n",
       "      <th>Order_Items.product_id</th>\n",
       "      <th>Order_Items.attributes</th>\n",
       "      <th>Order_Items.attribute_prices</th>\n",
       "      <th>Order_Items.qty</th>\n",
       "      <th>Order_Items.price</th>\n",
       "      <th>Order_Items.cost</th>\n",
       "      <th>Order_Items.registry_item</th>\n",
       "      <th>Order_Items.related_id</th>\n",
       "      <th>Order_Items.reorder_frequency</th>\n",
       "      <th>Order_Items.account_id</th>\n",
       "      <th>Order_Items.flags</th>\n",
       "      <th>Products.id</th>\n",
       "      <th>Products.status</th>\n",
       "      <th>Products.product_type</th>\n",
       "      <th>Products.vendor</th>\n",
       "      <th>Products.import_id</th>\n",
       "      <th>Products.menu_name</th>\n",
       "      <th>Products.list_price</th>\n",
       "      <th>Products.price</th>\n",
       "      <th>Products.sale_price</th>\n",
       "      <th>Products.cost</th>\n",
       "      <th>Products.flags</th>\n",
       "      <th>Products.left_flag</th>\n",
       "      <th>Products.right_flag</th>\n",
       "      <th>Products.last_modified</th>\n",
       "      <th>Products.taxable</th>\n",
       "      <th>Products.shopping_gtin</th>\n",
       "      <th>Products.shopping_flags</th>\n",
       "      <th>Products.amazon_type</th>\n",
       "      <th>Products.amazon_price</th>\n",
       "      <th>Products.google_adwords</th>\n",
       "      <th>Products.shopping_cat</th>\n",
       "      <th>Products.shopzilla_cat</th>\n",
       "      <th>Products.qb_edit_sequence</th>\n",
       "      <th>Products.price_break_type</th>\n",
       "      <th>Products.price_breaks</th>\n",
       "      <th>Products.websites</th>\n",
       "      <th>Products.audio</th>\n",
       "      <th>Products.seo_footer</th>\n",
       "      <th>Products.seo_category</th>\n",
       "      <th>Products.length</th>\n",
       "      <th>Products.width</th>\n",
       "      <th>Products.height</th>\n",
       "      <th>Products.upc</th>\n",
       "      <th>Products.case_qty</th>\n",
       "      <th>Products.markup</th>\n",
       "      <th>Products.override_markup</th>\n",
       "      <th>Products.import_flags</th>\n",
       "      <th>Products.map_price</th>\n",
       "      <th>Products.hygienic</th>\n",
       "      <th>Products.default_quantity</th>\n",
       "      <th>Products.shipping_length</th>\n",
       "      <th>Products.shipping_width</th>\n",
       "      <th>Products.shipping_height</th>\n",
       "      <th>Products.shipping_weight</th>\n",
       "      <th>Products.google_shopping_label</th>\n",
       "      <th>Products.leg_style</th>\n",
       "      <th>Products.saved_status</th>\n",
       "      <th>Products.freight_cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4.194000e+03</td>\n",
       "      <td>101.0</td>\n",
       "      <td>2114.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.194000e+03</td>\n",
       "      <td>3771.000000</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>3737.000000</td>\n",
       "      <td>3999.000000</td>\n",
       "      <td>882.000000</td>\n",
       "      <td>882.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>278.000000</td>\n",
       "      <td>364.000000</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>351.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4189.000000</td>\n",
       "      <td>4.176000e+03</td>\n",
       "      <td>4176.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4.194000e+03</td>\n",
       "      <td>4.171000e+03</td>\n",
       "      <td>3.848000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>4011.000000</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4151.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4194.000000</td>\n",
       "      <td>4191.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1008.000000</td>\n",
       "      <td>4037.000000</td>\n",
       "      <td>4037.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4037.000000</td>\n",
       "      <td>4037.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4017.000000</td>\n",
       "      <td>4036.000000</td>\n",
       "      <td>1160.000000</td>\n",
       "      <td>4037.000000</td>\n",
       "      <td>2987.000000</td>\n",
       "      <td>1239.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.037000e+03</td>\n",
       "      <td>2959.000000</td>\n",
       "      <td>3.130000e+03</td>\n",
       "      <td>3917.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>592.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>3.728000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2837.0</td>\n",
       "      <td>998.000000</td>\n",
       "      <td>996.000000</td>\n",
       "      <td>996.000000</td>\n",
       "      <td>2.127000e+03</td>\n",
       "      <td>2638.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2920.000000</td>\n",
       "      <td>2786.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>2080.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3998.000000</td>\n",
       "      <td>3998.000000</td>\n",
       "      <td>3998.000000</td>\n",
       "      <td>659.000000</td>\n",
       "      <td>387.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3930.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1796.518121</td>\n",
       "      <td>1.440971e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.979659</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>7.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.450401e+09</td>\n",
       "      <td>0.137364</td>\n",
       "      <td>9142.984025</td>\n",
       "      <td>1796.518121</td>\n",
       "      <td>7389.158537</td>\n",
       "      <td>6.018061e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>131.925196</td>\n",
       "      <td>0.800838</td>\n",
       "      <td>7.141263</td>\n",
       "      <td>20.403628</td>\n",
       "      <td>9.972676</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.752590</td>\n",
       "      <td>13.086676</td>\n",
       "      <td>137.192818</td>\n",
       "      <td>47.981396</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>2.958940</td>\n",
       "      <td>1.443104e+09</td>\n",
       "      <td>134.842263</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.326180</td>\n",
       "      <td>1.443054e+09</td>\n",
       "      <td>1.449607e+09</td>\n",
       "      <td>1.442167e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.010417</td>\n",
       "      <td>0.124159</td>\n",
       "      <td>11156.068670</td>\n",
       "      <td>9142.984025</td>\n",
       "      <td>4451.426162</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.858846</td>\n",
       "      <td>67.349132</td>\n",
       "      <td>51.112718</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.916667</td>\n",
       "      <td>4518.398068</td>\n",
       "      <td>0.987119</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.629676</td>\n",
       "      <td>3.400297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>121.683321</td>\n",
       "      <td>74.266043</td>\n",
       "      <td>70.754095</td>\n",
       "      <td>52.318192</td>\n",
       "      <td>9549.464680</td>\n",
       "      <td>5.811138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.462428e+09</td>\n",
       "      <td>0.940858</td>\n",
       "      <td>2.865179e+13</td>\n",
       "      <td>61.543528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.727855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>1.450329e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.292014</td>\n",
       "      <td>19.191185</td>\n",
       "      <td>13.587992</td>\n",
       "      <td>5.504591e+11</td>\n",
       "      <td>162.885140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.166438</td>\n",
       "      <td>65.059943</td>\n",
       "      <td>181.696967</td>\n",
       "      <td>0.064423</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.208216</td>\n",
       "      <td>10.872750</td>\n",
       "      <td>11.592447</td>\n",
       "      <td>15.487041</td>\n",
       "      <td>3.863049</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.876336</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1065.679090</td>\n",
       "      <td>1.887681e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.141196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.447214</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.021334e+07</td>\n",
       "      <td>0.391842</td>\n",
       "      <td>5276.541078</td>\n",
       "      <td>1065.679090</td>\n",
       "      <td>3818.085460</td>\n",
       "      <td>1.342831e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>231.156869</td>\n",
       "      <td>4.859280</td>\n",
       "      <td>4.531500</td>\n",
       "      <td>11.850291</td>\n",
       "      <td>14.617203</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.755244</td>\n",
       "      <td>51.296654</td>\n",
       "      <td>222.898475</td>\n",
       "      <td>209.843126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.928203</td>\n",
       "      <td>0.312482</td>\n",
       "      <td>1.809258e+07</td>\n",
       "      <td>213.804804</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.508683</td>\n",
       "      <td>1.814291e+07</td>\n",
       "      <td>9.118822e+06</td>\n",
       "      <td>1.793374e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.102062</td>\n",
       "      <td>0.375087</td>\n",
       "      <td>5802.466202</td>\n",
       "      <td>5276.541078</td>\n",
       "      <td>5577.392427</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.821959</td>\n",
       "      <td>95.571793</td>\n",
       "      <td>74.155515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.916831</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.399851</td>\n",
       "      <td>5614.454744</td>\n",
       "      <td>1.386196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.420626</td>\n",
       "      <td>2.248065</td>\n",
       "      <td>NaN</td>\n",
       "      <td>245.856090</td>\n",
       "      <td>98.829781</td>\n",
       "      <td>72.405928</td>\n",
       "      <td>74.691642</td>\n",
       "      <td>16246.897822</td>\n",
       "      <td>1.236169</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.586206e+06</td>\n",
       "      <td>0.235929</td>\n",
       "      <td>1.794757e+13</td>\n",
       "      <td>5.086931</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.097197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.029036e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.334049</td>\n",
       "      <td>51.129537</td>\n",
       "      <td>14.010066</td>\n",
       "      <td>3.583533e+11</td>\n",
       "      <td>508.461157</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.372537</td>\n",
       "      <td>94.714484</td>\n",
       "      <td>312.357568</td>\n",
       "      <td>0.245564</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.508782</td>\n",
       "      <td>6.781847</td>\n",
       "      <td>10.250909</td>\n",
       "      <td>22.256617</td>\n",
       "      <td>2.098446</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.364374</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.386089e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.437559e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>6.638000e+01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.890000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>2.890000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.386090e+09</td>\n",
       "      <td>2.890000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.386090e+09</td>\n",
       "      <td>1.438868e+09</td>\n",
       "      <td>1.386103e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.120000</td>\n",
       "      <td>0.280000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.020000</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>2.890000</td>\n",
       "      <td>0.280000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.452269e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.542161e+10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.990000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>1.442503e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>8.019674e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.190000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>865.250000</td>\n",
       "      <td>1.427323e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.437763e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4258.000000</td>\n",
       "      <td>865.250000</td>\n",
       "      <td>4537.250000</td>\n",
       "      <td>1.698485e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.765000</td>\n",
       "      <td>3.430000</td>\n",
       "      <td>44.110000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.431858e+09</td>\n",
       "      <td>44.015000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.431802e+09</td>\n",
       "      <td>1.440529e+09</td>\n",
       "      <td>1.430999e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5847.250000</td>\n",
       "      <td>4258.000000</td>\n",
       "      <td>1009.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>24.030000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1012.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.110000</td>\n",
       "      <td>24.400000</td>\n",
       "      <td>32.660000</td>\n",
       "      <td>15.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.462370e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.008020e+13</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.820000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>1.450323e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.019673e+10</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.775000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1747.500000</td>\n",
       "      <td>1.446412e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.456954e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9641.000000</td>\n",
       "      <td>1747.500000</td>\n",
       "      <td>6887.000000</td>\n",
       "      <td>1.698485e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>74.740000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.950000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.705000</td>\n",
       "      <td>6.710000</td>\n",
       "      <td>80.510000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.449678e+09</td>\n",
       "      <td>79.990000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.449675e+09</td>\n",
       "      <td>1.450214e+09</td>\n",
       "      <td>1.448039e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11770.000000</td>\n",
       "      <td>9641.000000</td>\n",
       "      <td>1867.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>43.460000</td>\n",
       "      <td>32.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1867.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.330000</td>\n",
       "      <td>48.245000</td>\n",
       "      <td>54.100000</td>\n",
       "      <td>31.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.463163e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.008020e+13</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69.990000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>1.450324e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>15.630000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>7.797090e+11</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>104.995000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.500000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>8.645000</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2698.750000</td>\n",
       "      <td>1.456955e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.456956e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14011.750000</td>\n",
       "      <td>2698.750000</td>\n",
       "      <td>10832.000000</td>\n",
       "      <td>1.698485e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>139.960000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.950000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>12.245000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.250000</td>\n",
       "      <td>9.950000</td>\n",
       "      <td>143.855000</td>\n",
       "      <td>8.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.457913e+09</td>\n",
       "      <td>142.810000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.457727e+09</td>\n",
       "      <td>1.457976e+09</td>\n",
       "      <td>1.456894e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16482.750000</td>\n",
       "      <td>14011.750000</td>\n",
       "      <td>4345.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>74.990000</td>\n",
       "      <td>59.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4371.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>134.390000</td>\n",
       "      <td>83.360000</td>\n",
       "      <td>119.990000</td>\n",
       "      <td>59.990000</td>\n",
       "      <td>32896.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.463163e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.088440e+13</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>124.740000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>1.450337e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.500000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>8.223840e+11</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>155.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.500000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3736.000000</td>\n",
       "      <td>1.463418e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.463418e+09</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>17437.000000</td>\n",
       "      <td>3736.000000</td>\n",
       "      <td>16201.000000</td>\n",
       "      <td>3.003935e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5163.040000</td>\n",
       "      <td>132.930000</td>\n",
       "      <td>32.810000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>109.900000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>449.000000</td>\n",
       "      <td>588.040000</td>\n",
       "      <td>4627.950000</td>\n",
       "      <td>2017.920000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.463419e+09</td>\n",
       "      <td>4627.950000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>1.463419e+09</td>\n",
       "      <td>1.463422e+09</td>\n",
       "      <td>1.463422e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20202.000000</td>\n",
       "      <td>17437.000000</td>\n",
       "      <td>26175.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>1899.000000</td>\n",
       "      <td>1350.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>26175.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8439.000000</td>\n",
       "      <td>1899.000000</td>\n",
       "      <td>659.990000</td>\n",
       "      <td>1350.000000</td>\n",
       "      <td>98433.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.463420e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.089010e+13</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>736.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>22005.0</td>\n",
       "      <td>1.450712e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>900.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>8.931690e+11</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>418.000000</td>\n",
       "      <td>1899.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>175.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Customers.id  Customers.create_date  Customers.status  \\\n",
       "count   4194.000000           4.194000e+03             101.0   \n",
       "mean    1796.518121           1.440971e+09               0.0   \n",
       "std     1065.679090           1.887681e+07               0.0   \n",
       "min        3.000000           1.386089e+09               0.0   \n",
       "25%      865.250000           1.427323e+09               0.0   \n",
       "50%     1747.500000           1.446412e+09               0.0   \n",
       "75%     2698.750000           1.456955e+09               0.0   \n",
       "max     3736.000000           1.463418e+09               0.0   \n",
       "\n",
       "       Customers.mailing  Customers.reminders  Customers.tax_exempt  \\\n",
       "count        2114.000000                  0.0              5.000000   \n",
       "mean            0.979659                  NaN              0.200000   \n",
       "std             0.141196                  NaN              0.447214   \n",
       "min             0.000000                  NaN              0.000000   \n",
       "25%             1.000000                  NaN              0.000000   \n",
       "50%             1.000000                  NaN              0.000000   \n",
       "75%             1.000000                  NaN              0.000000   \n",
       "max             1.000000                  NaN              1.000000   \n",
       "\n",
       "       Customers.account_id  Customers.sales_rep  Customers.rewards  \\\n",
       "count              3.000000                  0.0                0.0   \n",
       "mean               7.333333                  NaN                NaN   \n",
       "std                0.577350                  NaN                NaN   \n",
       "min                7.000000                  NaN                NaN   \n",
       "25%                7.000000                  NaN                NaN   \n",
       "50%                7.000000                  NaN                NaN   \n",
       "75%                7.500000                  NaN                NaN   \n",
       "max                8.000000                  NaN                NaN   \n",
       "\n",
       "       Customers.profile_id  Customers.last_modified  Customers.customer_type  \\\n",
       "count                   0.0             4.194000e+03              3771.000000   \n",
       "mean                    NaN             1.450401e+09                 0.137364   \n",
       "std                     NaN             1.021334e+07                 0.391842   \n",
       "min                     NaN             1.437559e+09                 0.000000   \n",
       "25%                     NaN             1.437763e+09                 0.000000   \n",
       "50%                     NaN             1.456954e+09                 0.000000   \n",
       "75%                     NaN             1.456956e+09                 0.000000   \n",
       "max                     NaN             1.463418e+09                 2.000000   \n",
       "\n",
       "          Orders.id  Orders.customer_id  Orders.reorder_id  \\\n",
       "count   4194.000000         4194.000000          82.000000   \n",
       "mean    9142.984025         1796.518121        7389.158537   \n",
       "std     5276.541078         1065.679090        3818.085460   \n",
       "min       23.000000            3.000000          30.000000   \n",
       "25%     4258.000000          865.250000        4537.250000   \n",
       "50%     9641.000000         1747.500000        6887.000000   \n",
       "75%    14011.750000         2698.750000       10832.000000   \n",
       "max    17437.000000         3736.000000       16201.000000   \n",
       "\n",
       "       Orders.external_id  Orders.sales_rep  Orders.subtotal   Orders.tax  \\\n",
       "count        5.000000e+00               0.0      4194.000000  3737.000000   \n",
       "mean         6.018061e+08               NaN       131.925196     0.800838   \n",
       "std          1.342831e+09               NaN       231.156869     4.859280   \n",
       "min          6.638000e+01               NaN         2.890000     0.000000   \n",
       "25%          1.698485e+06               NaN        36.750000     0.000000   \n",
       "50%          1.698485e+06               NaN        74.740000     0.000000   \n",
       "75%          1.698485e+06               NaN       139.960000     0.000000   \n",
       "max          3.003935e+09               NaN      5163.040000   132.930000   \n",
       "\n",
       "       Orders.shipping  Orders.coupon_id  Orders.coupon_amount  \\\n",
       "count      3999.000000        882.000000            882.000000   \n",
       "mean          7.141263         20.403628              9.972676   \n",
       "std           4.531500         11.850291             14.617203   \n",
       "min           0.000000          4.000000              0.000000   \n",
       "25%           0.000000         11.000000              0.680000   \n",
       "50%           9.950000         26.000000              5.000000   \n",
       "75%           9.950000         32.000000             12.245000   \n",
       "max          32.810000         48.000000            109.900000   \n",
       "\n",
       "       Orders.gift_id  Orders.gift_amount  Orders.fee_amount  \\\n",
       "count             0.0                 0.0         278.000000   \n",
       "mean              NaN                 NaN          14.752590   \n",
       "std               NaN                 NaN          32.755244   \n",
       "min               NaN                 NaN           0.010000   \n",
       "25%               NaN                 NaN           1.765000   \n",
       "50%               NaN                 NaN           9.705000   \n",
       "75%               NaN                 NaN          11.250000   \n",
       "max               NaN                 NaN         449.000000   \n",
       "\n",
       "       Orders.discount_amount  Orders.total  Orders.balance_due  \\\n",
       "count              364.000000   4194.000000          351.000000   \n",
       "mean                13.086676    137.192818           47.981396   \n",
       "std                 51.296654    222.898475          209.843126   \n",
       "min                  0.020000      2.890000            0.000000   \n",
       "25%                  3.430000     44.110000            0.000000   \n",
       "50%                  6.710000     80.510000            0.000000   \n",
       "75%                  9.950000    143.855000            8.250000   \n",
       "max                588.040000   4627.950000         2017.920000   \n",
       "\n",
       "       Orders.shipping_trans  Orders.shipping_flags  Orders.weight  \\\n",
       "count                    0.0                    0.0       3.000000   \n",
       "mean                     NaN                    NaN      18.000000   \n",
       "std                      NaN                    NaN       6.928203   \n",
       "min                      NaN                    NaN      10.000000   \n",
       "25%                      NaN                    NaN      16.000000   \n",
       "50%                      NaN                    NaN      22.000000   \n",
       "75%                      NaN                    NaN      22.000000   \n",
       "max                      NaN                    NaN      22.000000   \n",
       "\n",
       "       Orders.payment_status  Orders.payment_date  Orders.payment_amount  \\\n",
       "count            4189.000000         4.176000e+03            4176.000000   \n",
       "mean                2.958940         1.443104e+09             134.842263   \n",
       "std                 0.312482         1.809258e+07             213.804804   \n",
       "min                 0.000000         1.386090e+09               2.890000   \n",
       "25%                 3.000000         1.431858e+09              44.015000   \n",
       "50%                 3.000000         1.449678e+09              79.990000   \n",
       "75%                 3.000000         1.457913e+09             142.810000   \n",
       "max                 3.000000         1.463419e+09            4627.950000   \n",
       "\n",
       "       Orders.purchase_order  Orders.payment_ref  Orders.status  \\\n",
       "count                    0.0                 0.0    4194.000000   \n",
       "mean                     NaN                 NaN       1.326180   \n",
       "std                      NaN                 NaN       1.508683   \n",
       "min                      NaN                 NaN       0.000000   \n",
       "25%                      NaN                 NaN       1.000000   \n",
       "50%                      NaN                 NaN       1.000000   \n",
       "75%                      NaN                 NaN       1.000000   \n",
       "max                      NaN                 NaN      15.000000   \n",
       "\n",
       "       Orders.placed_date  Orders.updated_date  Orders.shipped_date  \\\n",
       "count        4.194000e+03         4.171000e+03         3.848000e+03   \n",
       "mean         1.443054e+09         1.449607e+09         1.442167e+09   \n",
       "std          1.814291e+07         9.118822e+06         1.793374e+07   \n",
       "min          1.386090e+09         1.438868e+09         1.386103e+09   \n",
       "25%          1.431802e+09         1.440529e+09         1.430999e+09   \n",
       "50%          1.449675e+09         1.450214e+09         1.448039e+09   \n",
       "75%          1.457727e+09         1.457976e+09         1.456894e+09   \n",
       "max          1.463419e+09         1.463422e+09         1.463422e+09   \n",
       "\n",
       "       Orders.registry_id  Orders.gift_message  Orders.website  \\\n",
       "count                 0.0                  0.0             0.0   \n",
       "mean                  NaN                  NaN             NaN   \n",
       "std                   NaN                  NaN             NaN   \n",
       "min                   NaN                  NaN             NaN   \n",
       "25%                   NaN                  NaN             NaN   \n",
       "50%                   NaN                  NaN             NaN   \n",
       "75%                   NaN                  NaN             NaN   \n",
       "max                   NaN                  NaN             NaN   \n",
       "\n",
       "       Orders.mailing  Orders.flags  Orders.partial_ship  \\\n",
       "count             0.0           1.0            96.000000   \n",
       "mean              NaN           1.0             0.010417   \n",
       "std               NaN           NaN             0.102062   \n",
       "min               NaN           1.0             0.000000   \n",
       "25%               NaN           1.0             0.000000   \n",
       "50%               NaN           1.0             0.000000   \n",
       "75%               NaN           1.0             0.000000   \n",
       "max               NaN           1.0             1.000000   \n",
       "\n",
       "       Orders.customer_type  Order_Items.id  Order_Items.parent  \\\n",
       "count           4011.000000     4194.000000         4194.000000   \n",
       "mean               0.124159    11156.068670         9142.984025   \n",
       "std                0.375087     5802.466202         5276.541078   \n",
       "min                0.000000       31.000000           23.000000   \n",
       "25%                0.000000     5847.250000         4258.000000   \n",
       "50%                0.000000    11770.000000         9641.000000   \n",
       "75%                0.000000    16482.750000        14011.750000   \n",
       "max                2.000000    20202.000000        17437.000000   \n",
       "\n",
       "       Order_Items.product_id  Order_Items.attributes  \\\n",
       "count             4151.000000                     0.0   \n",
       "mean              4451.426162                     NaN   \n",
       "std               5577.392427                     NaN   \n",
       "min                  1.000000                     NaN   \n",
       "25%               1009.000000                     NaN   \n",
       "50%               1867.000000                     NaN   \n",
       "75%               4345.500000                     NaN   \n",
       "max              26175.000000                     NaN   \n",
       "\n",
       "       Order_Items.attribute_prices  Order_Items.qty  Order_Items.price  \\\n",
       "count                           0.0      4194.000000        4194.000000   \n",
       "mean                            NaN         1.858846          67.349132   \n",
       "std                             NaN         8.821959          95.571793   \n",
       "min                             NaN         1.000000           1.120000   \n",
       "25%                             NaN         1.000000          24.030000   \n",
       "50%                             NaN         1.000000          43.460000   \n",
       "75%                             NaN         1.000000          74.990000   \n",
       "max                             NaN       500.000000        1899.000000   \n",
       "\n",
       "       Order_Items.cost  Order_Items.registry_item  Order_Items.related_id  \\\n",
       "count       4191.000000                        0.0                     0.0   \n",
       "mean          51.112718                        NaN                     NaN   \n",
       "std           74.155515                        NaN                     NaN   \n",
       "min            0.280000                        NaN                     NaN   \n",
       "25%           16.200000                        NaN                     NaN   \n",
       "50%           32.500000                        NaN                     NaN   \n",
       "75%           59.500000                        NaN                     NaN   \n",
       "max         1350.000000                        NaN                     NaN   \n",
       "\n",
       "       Order_Items.reorder_frequency  Order_Items.account_id  \\\n",
       "count                      24.000000                     0.0   \n",
       "mean                        1.666667                     NaN   \n",
       "std                         0.916831                     NaN   \n",
       "min                         1.000000                     NaN   \n",
       "25%                         1.000000                     NaN   \n",
       "50%                         1.000000                     NaN   \n",
       "75%                         2.000000                     NaN   \n",
       "max                         4.000000                     NaN   \n",
       "\n",
       "       Order_Items.flags   Products.id  Products.status  \\\n",
       "count        1008.000000   4037.000000      4037.000000   \n",
       "mean            1.916667   4518.398068         0.987119   \n",
       "std             0.399851   5614.454744         1.386196   \n",
       "min             0.000000      1.000000         0.000000   \n",
       "25%             2.000000   1012.000000         0.000000   \n",
       "50%             2.000000   1867.000000         0.000000   \n",
       "75%             2.000000   4371.000000         3.000000   \n",
       "max             2.000000  26175.000000         5.000000   \n",
       "\n",
       "       Products.product_type  Products.vendor  Products.import_id  \\\n",
       "count                    0.0      4037.000000         4037.000000   \n",
       "mean                     NaN         1.629676            3.400297   \n",
       "std                      NaN         1.420626            2.248065   \n",
       "min                      NaN         1.000000            1.000000   \n",
       "25%                      NaN         1.000000            3.000000   \n",
       "50%                      NaN         1.000000            3.000000   \n",
       "75%                      NaN         2.000000            3.000000   \n",
       "max                      NaN        11.000000           21.000000   \n",
       "\n",
       "       Products.menu_name  Products.list_price  Products.price  \\\n",
       "count                 0.0          4017.000000     4036.000000   \n",
       "mean                  NaN           121.683321       74.266043   \n",
       "std                   NaN           245.856090       98.829781   \n",
       "min                   NaN             1.020000        1.540000   \n",
       "25%                   NaN            33.110000       24.400000   \n",
       "50%                   NaN            72.330000       48.245000   \n",
       "75%                   NaN           134.390000       83.360000   \n",
       "max                   NaN          8439.000000     1899.000000   \n",
       "\n",
       "       Products.sale_price  Products.cost  Products.flags  Products.left_flag  \\\n",
       "count          1160.000000    4037.000000     2987.000000         1239.000000   \n",
       "mean             70.754095      52.318192     9549.464680            5.811138   \n",
       "std              72.405928      74.691642    16246.897822            1.236169   \n",
       "min               2.890000       0.280000        0.000000            0.000000   \n",
       "25%              32.660000      15.500000        0.000000            6.000000   \n",
       "50%              54.100000      31.750000        0.000000            6.000000   \n",
       "75%             119.990000      59.990000    32896.000000            6.000000   \n",
       "max             659.990000    1350.000000    98433.000000            9.000000   \n",
       "\n",
       "       Products.right_flag  Products.last_modified  Products.taxable  \\\n",
       "count                  0.0            4.037000e+03       2959.000000   \n",
       "mean                   NaN            1.462428e+09          0.940858   \n",
       "std                    NaN            1.586206e+06          0.235929   \n",
       "min                    NaN            1.452269e+09          0.000000   \n",
       "25%                    NaN            1.462370e+09          1.000000   \n",
       "50%                    NaN            1.463163e+09          1.000000   \n",
       "75%                    NaN            1.463163e+09          1.000000   \n",
       "max                    NaN            1.463420e+09          1.000000   \n",
       "\n",
       "       Products.shopping_gtin  Products.shopping_flags  Products.amazon_type  \\\n",
       "count            3.130000e+03              3917.000000                   0.0   \n",
       "mean             2.865179e+13                61.543528                   NaN   \n",
       "std              1.794757e+13                 5.086931                   NaN   \n",
       "min              1.542161e+10                 0.000000                   NaN   \n",
       "25%              1.008020e+13                62.000000                   NaN   \n",
       "50%              4.008020e+13                62.000000                   NaN   \n",
       "75%              4.088440e+13                62.000000                   NaN   \n",
       "max              5.089010e+13                63.000000                   NaN   \n",
       "\n",
       "       Products.amazon_price  Products.google_adwords  Products.shopping_cat  \\\n",
       "count             592.000000                      0.0                 2334.0   \n",
       "mean               89.727855                      NaN                  199.0   \n",
       "std                85.097197                      NaN                    0.0   \n",
       "min                 2.990000                      NaN                  199.0   \n",
       "25%                40.820000                      NaN                  199.0   \n",
       "50%                69.990000                      NaN                  199.0   \n",
       "75%               124.740000                      NaN                  199.0   \n",
       "max               736.250000                      NaN                  199.0   \n",
       "\n",
       "       Products.shopzilla_cat  Products.qb_edit_sequence  \\\n",
       "count                  2334.0               3.728000e+03   \n",
       "mean                  22005.0               1.450329e+09   \n",
       "std                       0.0               4.029036e+05   \n",
       "min                   22005.0               1.442503e+09   \n",
       "25%                   22005.0               1.450323e+09   \n",
       "50%                   22005.0               1.450324e+09   \n",
       "75%                   22005.0               1.450337e+09   \n",
       "max                   22005.0               1.450712e+09   \n",
       "\n",
       "       Products.price_break_type  Products.price_breaks  Products.websites  \\\n",
       "count                        0.0                    0.0                0.0   \n",
       "mean                         NaN                    NaN                NaN   \n",
       "std                          NaN                    NaN                NaN   \n",
       "min                          NaN                    NaN                NaN   \n",
       "25%                          NaN                    NaN                NaN   \n",
       "50%                          NaN                    NaN                NaN   \n",
       "75%                          NaN                    NaN                NaN   \n",
       "max                          NaN                    NaN                NaN   \n",
       "\n",
       "       Products.audio  Products.seo_footer  Products.seo_category  \\\n",
       "count             0.0                  0.0                 2837.0   \n",
       "mean              NaN                  NaN                    0.0   \n",
       "std               NaN                  NaN                    0.0   \n",
       "min               NaN                  NaN                    0.0   \n",
       "25%               NaN                  NaN                    0.0   \n",
       "50%               NaN                  NaN                    0.0   \n",
       "75%               NaN                  NaN                    0.0   \n",
       "max               NaN                  NaN                    0.0   \n",
       "\n",
       "       Products.length  Products.width  Products.height  Products.upc  \\\n",
       "count       998.000000      996.000000       996.000000  2.127000e+03   \n",
       "mean         21.292014       19.191185        13.587992  5.504591e+11   \n",
       "std          19.334049       51.129537        14.010066  3.583533e+11   \n",
       "min           0.500000        0.250000         0.100000  8.019674e+09   \n",
       "25%           9.000000        4.750000         2.000000  8.019673e+10   \n",
       "50%          16.000000       15.630000         6.000000  7.797090e+11   \n",
       "75%          27.500000       24.000000        28.000000  8.223840e+11   \n",
       "max         123.000000      900.000000        76.000000  8.931690e+11   \n",
       "\n",
       "       Products.case_qty  Products.markup  Products.override_markup  \\\n",
       "count        2638.000000              0.0               2920.000000   \n",
       "mean          162.885140              NaN                  0.166438   \n",
       "std           508.461157              NaN                  0.372537   \n",
       "min             1.000000              NaN                  0.000000   \n",
       "25%             1.000000              NaN                  0.000000   \n",
       "50%             5.000000              NaN                  0.000000   \n",
       "75%            64.000000              NaN                  0.000000   \n",
       "max          5000.000000              NaN                  1.000000   \n",
       "\n",
       "       Products.import_flags  Products.map_price  Products.hygienic  \\\n",
       "count            2786.000000          122.000000        2080.000000   \n",
       "mean               65.059943          181.696967           0.064423   \n",
       "std                94.714484          312.357568           0.245564   \n",
       "min                 0.000000            8.190000           0.000000   \n",
       "25%                 0.000000           65.000000           0.000000   \n",
       "50%                 0.000000          104.995000           0.000000   \n",
       "75%               128.000000          155.000000           0.000000   \n",
       "max               418.000000         1899.000000           1.000000   \n",
       "\n",
       "       Products.default_quantity  Products.shipping_length  \\\n",
       "count                        0.0               3998.000000   \n",
       "mean                         NaN                 17.208216   \n",
       "std                          NaN                 10.508782   \n",
       "min                          NaN                  0.000000   \n",
       "25%                          NaN                  9.000000   \n",
       "50%                          NaN                 15.500000   \n",
       "75%                          NaN                 23.500000   \n",
       "max                          NaN                 90.000000   \n",
       "\n",
       "       Products.shipping_width  Products.shipping_height  \\\n",
       "count              3998.000000               3998.000000   \n",
       "mean                 10.872750                 11.592447   \n",
       "std                   6.781847                 10.250909   \n",
       "min                   0.000000                  0.000000   \n",
       "25%                   5.700000                  4.000000   \n",
       "50%                  10.000000                  8.645000   \n",
       "75%                  15.000000                 15.000000   \n",
       "max                  80.000000                 58.000000   \n",
       "\n",
       "       Products.shipping_weight  Products.google_shopping_label  \\\n",
       "count                659.000000                      387.000000   \n",
       "mean                  15.487041                        3.863049   \n",
       "std                   22.256617                        2.098446   \n",
       "min                    0.020000                        0.000000   \n",
       "25%                    2.775000                        5.000000   \n",
       "50%                    8.900000                        5.000000   \n",
       "75%                   21.000000                        5.000000   \n",
       "max                  175.000000                        5.000000   \n",
       "\n",
       "       Products.leg_style  Products.saved_status  Products.freight_cost  \n",
       "count                 0.0            3930.000000                    0.0  \n",
       "mean                  NaN               0.876336                    NaN  \n",
       "std                   NaN               1.364374                    NaN  \n",
       "min                   NaN               0.000000                    NaN  \n",
       "25%                   NaN               0.000000                    NaN  \n",
       "50%                   NaN               0.000000                    NaN  \n",
       "75%                   NaN               3.000000                    NaN  \n",
       "max                   NaN               3.000000                    NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "2387c010",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Customers.id', 'Customers.fname', 'Customers.lname',\n",
       "       'Customers.company', 'Customers.create_date', 'Customers.status',\n",
       "       'Customers.mailing', 'Customers.reminders', 'Customers.tax_exempt',\n",
       "       'Customers.account_id',\n",
       "       ...\n",
       "       'Products.google_shopping_label', 'Products.product_option',\n",
       "       'Products.size', 'Products.material', 'Products.arm_style',\n",
       "       'Products.leg_style', 'Products.seat_size', 'Products.family_id',\n",
       "       'Products.saved_status', 'Products.freight_cost'],\n",
       "      dtype='object', length=181)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "f34d6fab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "8d6f6fdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "d999fd8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customers.id                0\n",
       "Customers.fname             0\n",
       "Customers.lname             0\n",
       "Customers.company        3467\n",
       "Customers.create_date       0\n",
       "                         ... \n",
       "Products.leg_style       4194\n",
       "Products.seat_size       4032\n",
       "Products.family_id        325\n",
       "Products.saved_status     264\n",
       "Products.freight_cost    4194\n",
       "Length: 181, dtype: int64"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "2082c091",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customers.id             3054\n",
       "Customers.fname          1631\n",
       "Customers.lname          2557\n",
       "Customers.company         425\n",
       "Customers.create_date    3054\n",
       "                         ... \n",
       "Products.leg_style          0\n",
       "Products.seat_size         13\n",
       "Products.family_id       1002\n",
       "Products.saved_status       2\n",
       "Products.freight_cost       0\n",
       "Length: 181, dtype: int64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "b23d9512",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 4194 entries, 0 to 4193\n",
      "Columns: 181 entries, Customers.id to Products.freight_cost\n",
      "dtypes: float64(98), int64(10), object(73)\n",
      "memory usage: 5.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "ca9254f0",
   "metadata": {},
   "source": [
    "o Customer\n",
    "o Products\n",
    "o Orders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b4a260d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "CusSegment=df[[\"Order_Items.reorder_frequency\",\"Customers.customer_type\",\"Products.price\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "af3c3baa",
   "metadata": {},
   "outputs": [],
   "source": [
    "Customer=df[[\"Customers.status\",\"Customers.customer_type\",\"Customers.tax_exempt\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "814361f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "Orders=df[[\"Orders.total\",\"Orders.payment_status\",\"Orders.payment_amount\",\"Orders.status\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cf24d732",
   "metadata": {},
   "outputs": [],
   "source": [
    "Products=df[[\"Products.status\",\"Products.price\",\"Products.sale_price\",\"Products.cost\",\"Products.saved_status\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5e2cf090",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4194 entries, 0 to 4193\n",
      "Data columns (total 3 columns):\n",
      " #   Column                         Non-Null Count  Dtype  \n",
      "---  ------                         --------------  -----  \n",
      " 0   Order_Items.reorder_frequency  24 non-null     float64\n",
      " 1   Customers.customer_type        3771 non-null   float64\n",
      " 2   Products.price                 4036 non-null   float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 98.4 KB\n"
     ]
    }
   ],
   "source": [
    "CusSegment.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c431e528",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Items.reorder_frequency</th>\n",
       "      <th>Customers.customer_type</th>\n",
       "      <th>Products.price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>3771.000000</td>\n",
       "      <td>4036.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.137364</td>\n",
       "      <td>74.266043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.916831</td>\n",
       "      <td>0.391842</td>\n",
       "      <td>98.829781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.540000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>24.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>48.245000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>83.360000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1899.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Order_Items.reorder_frequency  Customers.customer_type  Products.price\n",
       "count                      24.000000              3771.000000     4036.000000\n",
       "mean                        1.666667                 0.137364       74.266043\n",
       "std                         0.916831                 0.391842       98.829781\n",
       "min                         1.000000                 0.000000        1.540000\n",
       "25%                         1.000000                 0.000000       24.400000\n",
       "50%                         1.000000                 0.000000       48.245000\n",
       "75%                         2.000000                 0.000000       83.360000\n",
       "max                         4.000000                 2.000000     1899.000000"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9fe9e86f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4194, 3)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7eb95795",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Order_Items.reorder_frequency    4170\n",
       "Customers.customer_type           423\n",
       "Products.price                    158\n",
       "dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "78ce76f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "CusSegment=CusSegment.dropna(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "804102e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4194, 0)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "4d8af52c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(74.2660431119918, 1.54, 1899.0, 98.82978106048357)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment[\"Products.price\"].mean(),CusSegment[\"Products.price\"].min(),df[\"Products.price\"].max(),CusSegment[\"Products.price\"].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "31c6a970",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9168313422570846"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment[\"Order_Items.reorder_frequency\"].mean(),\n",
    "CusSegment[\"Order_Items.reorder_frequency\"].min(),\n",
    "CusSegment[\"Order_Items.reorder_frequency\"].max(),\n",
    "CusSegment[\"Order_Items.reorder_frequency\"].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "130d0bd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.0\n",
       "Name: Customers.customer_type, dtype: float64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment[\"Customers.customer_type\"].mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "71fc2d23",
   "metadata": {},
   "outputs": [],
   "source": [
    "##Fillna Boş Verileri Doldur -- Update Cümleciği\n",
    "\n",
    "CusSegment[\"Products.price\"]=CusSegment[\"Products.price\"].fillna(CusSegment[\"Products.price\"].mean())\n",
    "CusSegment[\"Order_Items.reorder_frequency\"]=CusSegment[\"Order_Items.reorder_frequency\"].fillna(CusSegment[\"Order_Items.reorder_frequency\"].mean())\n",
    "CusSegment[\"Customers.customer_type\"]=CusSegment[\"Customers.customer_type\"].fillna(CusSegment[\"Customers.customer_type\"].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "cf22bf46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Order_Items.reorder_frequency    0\n",
       "Customers.customer_type          0\n",
       "Products.price                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "6e2e4ab7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Items.reorder_frequency</th>\n",
       "      <th>Customers.customer_type</th>\n",
       "      <th>Products.price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>57.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order_Items.reorder_frequency  Customers.customer_type  Products.price\n",
       "0                       1.666667                      0.0           57.64\n",
       "1                       1.666667                      0.0           10.29\n",
       "2                       1.666667                      0.0           68.78\n",
       "3                       1.666667                      0.0           19.56\n",
       "4                       1.666667                      0.0           36.05"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "16bda24c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 1.        , 0.13736409, 2.        ])"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment[\"Customers.customer_type\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "db365035",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000000    3319\n",
       "0.137364     423\n",
       "1.000000     386\n",
       "2.000000      66\n",
       "Name: Customers.customer_type, dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment[\"Customers.customer_type\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "fd92d2c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "e0146837",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "sns.histplot(CusSegment['Customers.customer_type'], bins = 20, kde = True,\n",
    " palette = 'hls')\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "e3867055",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "sns.lineplot(y = CusSegment['Products.price'], x = CusSegment['Order_Items.reorder_frequency'], data = df,\n",
    " palette = 'hls')\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "9a940204",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "sns.lineplot(y = CusSegment['Products.price'], x = CusSegment['Customers.customer_type'], data = CusSegment,\n",
    " palette = 'hls')\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a226d852",
   "metadata": {},
   "source": [
    "# Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "3acfdd85",
   "metadata": {},
   "outputs": [],
   "source": [
    "model=KMeans(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "eded21fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "model=model.fit(CusSegment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6613b29b",
   "metadata": {},
   "outputs": [],
   "source": [
    "tahmin=model.predict(CusSegment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d9ffcb42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 3, 2, 0])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tahmin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "77211bbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "CusSegment['cluster']=tahmin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d5c3fcb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Items.reorder_frequency</th>\n",
       "      <th>Customers.customer_type</th>\n",
       "      <th>Products.price</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>57.64</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.29</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.78</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.56</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.05</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order_Items.reorder_frequency  Customers.customer_type  Products.price  \\\n",
       "0                       1.666667                      0.0           57.64   \n",
       "1                       1.666667                      0.0           10.29   \n",
       "2                       1.666667                      0.0           68.78   \n",
       "3                       1.666667                      0.0           19.56   \n",
       "4                       1.666667                      0.0           36.05   \n",
       "\n",
       "   cluster  \n",
       "0        0  \n",
       "1        0  \n",
       "2        0  \n",
       "3        0  \n",
       "4        0  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CusSegment.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "b0cd358e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7412313867044075"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "silhouette_score(CusSegment,tahmin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "000ffc5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.scatter(CusSegment[\"Customers.customer_type\"],CusSegment[\"Products.price\"],c=tahmin);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "7ee2dfff",
   "metadata": {},
   "outputs": [],
   "source": [
    "allscore=[]\n",
    "allcluster=[]\n",
    "distances=[]\n",
    "def fnc_clust(kactane):\n",
    "    for i in range(1,kactane):\n",
    "        i=i+1\n",
    "        model=KMeans(i)\n",
    "        model=model.fit(CusSegment)\n",
    "        tahmin=model.predict(CusSegment)\n",
    "        score=silhouette_score(CusSegment,tahmin)\n",
    "        distance=model.inertia_\n",
    "        print(\"Cluster..:\",i,\" Score..:\", score)\n",
    "        allscore.append(score)\n",
    "        allcluster.append(i)\n",
    "        distances.append(distance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "26e9b1ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster..: 2  Score..: 0.8989798217565564\n",
      "Cluster..: 3  Score..: 0.7437601874511074\n",
      "Cluster..: 4  Score..: 0.7412313867044075\n",
      "Cluster..: 5  Score..: 0.6112612688448616\n",
      "Cluster..: 6  Score..: 0.6325753689745829\n",
      "Cluster..: 7  Score..: 0.6328685458326397\n",
      "Cluster..: 8  Score..: 0.6361031706720713\n",
      "Cluster..: 9  Score..: 0.6277714225917499\n",
      "Cluster..: 10  Score..: 0.5966905145488343\n",
      "Cluster..: 11  Score..: 0.5846000399380785\n",
      "Cluster..: 12  Score..: 0.584526803274018\n",
      "Cluster..: 13  Score..: 0.5540115455925473\n",
      "Cluster..: 14  Score..: 0.5543109099501287\n",
      "Cluster..: 15  Score..: 0.5971937730833136\n",
      "Cluster..: 16  Score..: 0.5961013574927251\n",
      "Cluster..: 17  Score..: 0.5977674788350995\n",
      "Cluster..: 18  Score..: 0.5833689462306612\n",
      "Cluster..: 19  Score..: 0.5845422443482531\n",
      "Cluster..: 20  Score..: 0.5777716801789147\n"
     ]
    }
   ],
   "source": [
    "fnc_clust(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "236b10a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(allcluster,distances,color='Red');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b14f9c12",
   "metadata": {},
   "source": [
    "# Hierarchical Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "00dcad9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.cluster.hierarchy import dendrogram, linkage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "91844a07",
   "metadata": {},
   "outputs": [],
   "source": [
    "link_data=linkage(CusSegment,method=\"ward\",metric=\"euclidean\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "74b6a141",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dendrogram(link_data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "efee6c9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import DBSCAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "3ede3a5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "clusters=DBSCAN(min_samples=4).fit(CusSegment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "9224fe8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{-1,\n",
       " 0,\n",
       " 1,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 7,\n",
       " 8,\n",
       " 9,\n",
       " 10,\n",
       " 11,\n",
       " 12,\n",
       " 13,\n",
       " 14,\n",
       " 15,\n",
       " 16,\n",
       " 17,\n",
       " 18,\n",
       " 19,\n",
       " 20,\n",
       " 21,\n",
       " 22,\n",
       " 23,\n",
       " 24,\n",
       " 25,\n",
       " 26,\n",
       " 27,\n",
       " 28,\n",
       " 29,\n",
       " 30,\n",
       " 31,\n",
       " 32,\n",
       " 33,\n",
       " 34,\n",
       " 35,\n",
       " 36,\n",
       " 37,\n",
       " 38,\n",
       " 39,\n",
       " 40,\n",
       " 41,\n",
       " 42,\n",
       " 43,\n",
       " 44,\n",
       " 45,\n",
       " 46,\n",
       " 47,\n",
       " 48,\n",
       " 49,\n",
       " 50,\n",
       " 51,\n",
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       " 80,\n",
       " 81,\n",
       " 82,\n",
       " 83,\n",
       " 84,\n",
       " 85}"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(clusters.labels_)"
   ]
  }
 ],
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