Data Analysis on Flipkart.ipynb

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"
    }
   },
   "cell_type": "markdown",
   "id": "fb3c947b",
   "metadata": {},
   "source": [
    "# Flipkart Product Analysis\n",
    "![flipkart_1523448806588.webp](attachment:flipkart_1523448806588.webp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4cbe523",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e184c830",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import math\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9f65d56f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('D:\\\\PGP IN DATA SCIENCE with Careerera\\\\Files\\\\flipkart_com-ecommerce_sample.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f9853d04",
   "metadata": {
    "scrolled": false
   },
   "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>uniq_id</th>\n",
       "      <th>crawl_timestamp</th>\n",
       "      <th>product_url</th>\n",
       "      <th>product_name</th>\n",
       "      <th>product_category_tree</th>\n",
       "      <th>pid</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>discounted_price</th>\n",
       "      <th>image</th>\n",
       "      <th>is_FK_Advantage_product</th>\n",
       "      <th>description</th>\n",
       "      <th>product_rating</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_specifications</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
       "      <td>2016-03-25 22:59:23 +0000</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
       "      <td>SRTEH2FF9KEDEFGF</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
       "      <td>2016-03-25 22:59:23 +0000</td>\n",
       "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>[\"Furniture &gt;&gt; Living Room Furniture &gt;&gt; Sofa B...</td>\n",
       "      <td>SBEEH3QGU7MFYJFY</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
       "      <td>False</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
       "      <td>2016-03-25 22:59:23 +0000</td>\n",
       "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>[\"Footwear &gt;&gt; Women's Footwear &gt;&gt; Ballerinas &gt;...</td>\n",
       "      <td>SHOEH4GRSUBJGZXE</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of AW Bellies Sandals Wedges Heel...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>AW</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
       "      <td>2016-03-25 22:59:23 +0000</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
       "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
       "      <td>2016-03-25 22:59:23 +0000</td>\n",
       "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>[\"Pet Supplies &gt;&gt; Grooming &gt;&gt; Skin &amp; Coat Care...</td>\n",
       "      <td>PSOEH3ZYDMSYARJ5</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Specifications of Sicons All Purpose Arnica Do...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19995</th>\n",
       "      <td>7179d2f6c4ad50a17d014ca1d2815156</td>\n",
       "      <td>2015-12-01 10:15:43 +0000</td>\n",
       "      <td>http://www.flipkart.com/walldesign-small-vinyl...</td>\n",
       "      <td>WallDesign Small Vinyl Sticker</td>\n",
       "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
       "      <td>STIE7KFJAKSTDY9G</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>730.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/wall-decorat...</td>\n",
       "      <td>False</td>\n",
       "      <td>Buy WallDesign Small Vinyl Sticker for Rs.730 ...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>WallDesign</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19996</th>\n",
       "      <td>71ac419198359d37b8fe5e3fffdfee09</td>\n",
       "      <td>2015-12-01 10:15:43 +0000</td>\n",
       "      <td>http://www.flipkart.com/wallmantra-large-vinyl...</td>\n",
       "      <td>Wallmantra Large Vinyl Stickers Sticker</td>\n",
       "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
       "      <td>STIE9F5URNQGJCGH</td>\n",
       "      <td>1429.0</td>\n",
       "      <td>1143.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sticker/z/g/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Buy Wallmantra Large Vinyl Stickers Sticker fo...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Wallmantra</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19997</th>\n",
       "      <td>93e9d343837400ce0d7980874ece471c</td>\n",
       "      <td>2015-12-01 10:15:43 +0000</td>\n",
       "      <td>http://www.flipkart.com/elite-collection-mediu...</td>\n",
       "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
       "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
       "      <td>STIE7VAYDKQZEBSD</td>\n",
       "      <td>1299.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/sticker/b/s/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Elite Collection</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19998</th>\n",
       "      <td>669e79b8fa5d9ae020841c0c97d5e935</td>\n",
       "      <td>2015-12-01 10:15:43 +0000</td>\n",
       "      <td>http://www.flipkart.com/elite-collection-mediu...</td>\n",
       "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
       "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
       "      <td>STIE8YSVEPPCZ42Y</td>\n",
       "      <td>1499.0</td>\n",
       "      <td>1199.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/sticker/4/2/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Elite Collection</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19999</th>\n",
       "      <td>cb4fa87a874f715fff567f7b7b3be79c</td>\n",
       "      <td>2015-12-01 10:15:43 +0000</td>\n",
       "      <td>http://www.flipkart.com/elite-collection-mediu...</td>\n",
       "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
       "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
       "      <td>STIE88KN9ZDSGZKY</td>\n",
       "      <td>1499.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sticker/z/k/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Elite Collection</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20000 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                uniq_id            crawl_timestamp  \\\n",
       "0      c2d766ca982eca8304150849735ffef9  2016-03-25 22:59:23 +0000   \n",
       "1      7f7036a6d550aaa89d34c77bd39a5e48  2016-03-25 22:59:23 +0000   \n",
       "2      f449ec65dcbc041b6ae5e6a32717d01b  2016-03-25 22:59:23 +0000   \n",
       "3      0973b37acd0c664e3de26e97e5571454  2016-03-25 22:59:23 +0000   \n",
       "4      bc940ea42ee6bef5ac7cea3fb5cfbee7  2016-03-25 22:59:23 +0000   \n",
       "...                                 ...                        ...   \n",
       "19995  7179d2f6c4ad50a17d014ca1d2815156  2015-12-01 10:15:43 +0000   \n",
       "19996  71ac419198359d37b8fe5e3fffdfee09  2015-12-01 10:15:43 +0000   \n",
       "19997  93e9d343837400ce0d7980874ece471c  2015-12-01 10:15:43 +0000   \n",
       "19998  669e79b8fa5d9ae020841c0c97d5e935  2015-12-01 10:15:43 +0000   \n",
       "19999  cb4fa87a874f715fff567f7b7b3be79c  2015-12-01 10:15:43 +0000   \n",
       "\n",
       "                                             product_url  \\\n",
       "0      http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "1      http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
       "2      http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
       "3      http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "4      http://www.flipkart.com/sicons-all-purpose-arn...   \n",
       "...                                                  ...   \n",
       "19995  http://www.flipkart.com/walldesign-small-vinyl...   \n",
       "19996  http://www.flipkart.com/wallmantra-large-vinyl...   \n",
       "19997  http://www.flipkart.com/elite-collection-mediu...   \n",
       "19998  http://www.flipkart.com/elite-collection-mediu...   \n",
       "19999  http://www.flipkart.com/elite-collection-mediu...   \n",
       "\n",
       "                                  product_name  \\\n",
       "0          Alisha Solid Women's Cycling Shorts   \n",
       "1          FabHomeDecor Fabric Double Sofa Bed   \n",
       "2                                   AW Bellies   \n",
       "3          Alisha Solid Women's Cycling Shorts   \n",
       "4        Sicons All Purpose Arnica Dog Shampoo   \n",
       "...                                        ...   \n",
       "19995           WallDesign Small Vinyl Sticker   \n",
       "19996  Wallmantra Large Vinyl Stickers Sticker   \n",
       "19997  Elite Collection Medium Acrylic Sticker   \n",
       "19998  Elite Collection Medium Acrylic Sticker   \n",
       "19999  Elite Collection Medium Acrylic Sticker   \n",
       "\n",
       "                                   product_category_tree               pid  \\\n",
       "0      [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2FF9KEDEFGF   \n",
       "1      [\"Furniture >> Living Room Furniture >> Sofa B...  SBEEH3QGU7MFYJFY   \n",
       "2      [\"Footwear >> Women's Footwear >> Ballerinas >...  SHOEH4GRSUBJGZXE   \n",
       "3      [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2F6HUZMQ6SJ   \n",
       "4      [\"Pet Supplies >> Grooming >> Skin & Coat Care...  PSOEH3ZYDMSYARJ5   \n",
       "...                                                  ...               ...   \n",
       "19995  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE7KFJAKSTDY9G   \n",
       "19996  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE9F5URNQGJCGH   \n",
       "19997  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE7VAYDKQZEBSD   \n",
       "19998  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE8YSVEPPCZ42Y   \n",
       "19999  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE88KN9ZDSGZKY   \n",
       "\n",
       "       retail_price  discounted_price  \\\n",
       "0             999.0             379.0   \n",
       "1           32157.0           22646.0   \n",
       "2             999.0             499.0   \n",
       "3             699.0             267.0   \n",
       "4             220.0             210.0   \n",
       "...             ...               ...   \n",
       "19995        1500.0             730.0   \n",
       "19996        1429.0            1143.0   \n",
       "19997        1299.0             999.0   \n",
       "19998        1499.0            1199.0   \n",
       "19999        1499.0             999.0   \n",
       "\n",
       "                                                   image  \\\n",
       "0      [\"http://img5a.flixcart.com/image/short/u/4/a/...   \n",
       "1      [\"http://img6a.flixcart.com/image/sofa-bed/j/f...   \n",
       "2      [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...   \n",
       "3      [\"http://img5a.flixcart.com/image/short/6/2/h/...   \n",
       "4      [\"http://img5a.flixcart.com/image/pet-shampoo/...   \n",
       "...                                                  ...   \n",
       "19995  [\"http://img6a.flixcart.com/image/wall-decorat...   \n",
       "19996  [\"http://img6a.flixcart.com/image/sticker/z/g/...   \n",
       "19997  [\"http://img5a.flixcart.com/image/sticker/b/s/...   \n",
       "19998  [\"http://img5a.flixcart.com/image/sticker/4/2/...   \n",
       "19999  [\"http://img6a.flixcart.com/image/sticker/z/k/...   \n",
       "\n",
       "       is_FK_Advantage_product  \\\n",
       "0                        False   \n",
       "1                        False   \n",
       "2                        False   \n",
       "3                        False   \n",
       "4                        False   \n",
       "...                        ...   \n",
       "19995                    False   \n",
       "19996                    False   \n",
       "19997                    False   \n",
       "19998                    False   \n",
       "19999                    False   \n",
       "\n",
       "                                             description       product_rating  \\\n",
       "0      Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
       "1      FabHomeDecor Fabric Double Sofa Bed (Finish Co...  No rating available   \n",
       "2      Key Features of AW Bellies Sandals Wedges Heel...  No rating available   \n",
       "3      Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
       "4      Specifications of Sicons All Purpose Arnica Do...  No rating available   \n",
       "...                                                  ...                  ...   \n",
       "19995  Buy WallDesign Small Vinyl Sticker for Rs.730 ...  No rating available   \n",
       "19996  Buy Wallmantra Large Vinyl Stickers Sticker fo...  No rating available   \n",
       "19997  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
       "19998  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
       "19999  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
       "\n",
       "            overall_rating             brand  \\\n",
       "0      No rating available            Alisha   \n",
       "1      No rating available      FabHomeDecor   \n",
       "2      No rating available                AW   \n",
       "3      No rating available            Alisha   \n",
       "4      No rating available            Sicons   \n",
       "...                    ...               ...   \n",
       "19995  No rating available        WallDesign   \n",
       "19996  No rating available        Wallmantra   \n",
       "19997  No rating available  Elite Collection   \n",
       "19998  No rating available  Elite Collection   \n",
       "19999  No rating available  Elite Collection   \n",
       "\n",
       "                                  product_specifications  \n",
       "0      {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "1      {\"product_specification\"=>[{\"key\"=>\"Installati...  \n",
       "2      {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  \n",
       "3      {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "4      {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  \n",
       "...                                                  ...  \n",
       "19995  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "19996  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "19997  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "19998  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "19999  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
       "\n",
       "[20000 rows x 15 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82d19782",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eac7321a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "uniq_id                       0\n",
       "crawl_timestamp               0\n",
       "product_url                   0\n",
       "product_name                  0\n",
       "product_category_tree         0\n",
       "pid                           0\n",
       "retail_price                 78\n",
       "discounted_price             78\n",
       "image                         3\n",
       "is_FK_Advantage_product       0\n",
       "description                   2\n",
       "product_rating                0\n",
       "overall_rating                0\n",
       "brand                      5864\n",
       "product_specifications       14\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()\n",
    "##df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "391c567a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['uniq_id', 'crawl_timestamp', 'product_url', 'product_name',\n",
       "       'product_category_tree', 'pid', 'retail_price', 'discounted_price',\n",
       "       'image', 'is_FK_Advantage_product', 'description', 'product_rating',\n",
       "       'overall_rating', 'brand', 'product_specifications'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1dec46cc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6bdd4488",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## brand column has lot of null values it can be shown by colormap\n",
    "plt.figure(figsize=(8,6))\n",
    "sns.heatmap(df.isnull(), yticklabels=False, cmap='plasma', cbar=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c402763d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1361bfbb",
   "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>uniq_id</th>\n",
       "      <th>crawl_timestamp</th>\n",
       "      <th>product_url</th>\n",
       "      <th>product_name</th>\n",
       "      <th>product_category_tree</th>\n",
       "      <th>pid</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>discounted_price</th>\n",
       "      <th>image</th>\n",
       "      <th>is_FK_Advantage_product</th>\n",
       "      <th>description</th>\n",
       "      <th>product_rating</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_specifications</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
       "      <td>SRTEH2FF9KEDEFGF</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>[\"Furniture &gt;&gt; Living Room Furniture &gt;&gt; Sofa B...</td>\n",
       "      <td>SBEEH3QGU7MFYJFY</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
       "      <td>False</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>[\"Footwear &gt;&gt; Women's Footwear &gt;&gt; Ballerinas &gt;...</td>\n",
       "      <td>SHOEH4GRSUBJGZXE</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of AW Bellies Sandals Wedges Heel...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>AW</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
       "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>[\"Pet Supplies &gt;&gt; Grooming &gt;&gt; Skin &amp; Coat Care...</td>\n",
       "      <td>PSOEH3ZYDMSYARJ5</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Specifications of Sicons All Purpose Arnica Do...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            uniq_id           crawl_timestamp  \\\n",
       "0  c2d766ca982eca8304150849735ffef9 2016-03-25 22:59:23+00:00   \n",
       "1  7f7036a6d550aaa89d34c77bd39a5e48 2016-03-25 22:59:23+00:00   \n",
       "2  f449ec65dcbc041b6ae5e6a32717d01b 2016-03-25 22:59:23+00:00   \n",
       "3  0973b37acd0c664e3de26e97e5571454 2016-03-25 22:59:23+00:00   \n",
       "4  bc940ea42ee6bef5ac7cea3fb5cfbee7 2016-03-25 22:59:23+00:00   \n",
       "\n",
       "                                         product_url  \\\n",
       "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
       "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
       "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
       "\n",
       "                            product_name  \\\n",
       "0    Alisha Solid Women's Cycling Shorts   \n",
       "1    FabHomeDecor Fabric Double Sofa Bed   \n",
       "2                             AW Bellies   \n",
       "3    Alisha Solid Women's Cycling Shorts   \n",
       "4  Sicons All Purpose Arnica Dog Shampoo   \n",
       "\n",
       "                               product_category_tree               pid  \\\n",
       "0  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2FF9KEDEFGF   \n",
       "1  [\"Furniture >> Living Room Furniture >> Sofa B...  SBEEH3QGU7MFYJFY   \n",
       "2  [\"Footwear >> Women's Footwear >> Ballerinas >...  SHOEH4GRSUBJGZXE   \n",
       "3  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2F6HUZMQ6SJ   \n",
       "4  [\"Pet Supplies >> Grooming >> Skin & Coat Care...  PSOEH3ZYDMSYARJ5   \n",
       "\n",
       "   retail_price  discounted_price  \\\n",
       "0         999.0             379.0   \n",
       "1       32157.0           22646.0   \n",
       "2         999.0             499.0   \n",
       "3         699.0             267.0   \n",
       "4         220.0             210.0   \n",
       "\n",
       "                                               image  is_FK_Advantage_product  \\\n",
       "0  [\"http://img5a.flixcart.com/image/short/u/4/a/...                    False   \n",
       "1  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...                    False   \n",
       "2  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...                    False   \n",
       "3  [\"http://img5a.flixcart.com/image/short/6/2/h/...                    False   \n",
       "4  [\"http://img5a.flixcart.com/image/pet-shampoo/...                    False   \n",
       "\n",
       "                                         description       product_rating  \\\n",
       "0  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  No rating available   \n",
       "2  Key Features of AW Bellies Sandals Wedges Heel...  No rating available   \n",
       "3  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
       "4  Specifications of Sicons All Purpose Arnica Do...  No rating available   \n",
       "\n",
       "        overall_rating         brand  \\\n",
       "0  No rating available        Alisha   \n",
       "1  No rating available  FabHomeDecor   \n",
       "2  No rating available            AW   \n",
       "3  No rating available        Alisha   \n",
       "4  No rating available        Sicons   \n",
       "\n",
       "                              product_specifications        date  year  month  \n",
       "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016      3  \n",
       "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  2016-03-25  2016      3  \n",
       "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  2016-03-25  2016      3  \n",
       "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016      3  \n",
       "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  2016-03-25  2016      3  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## convering object column to datetime fo future use\n",
    "df['crawl_timestamp']=pd.to_datetime(df['crawl_timestamp'])\n",
    "df['date']=df['crawl_timestamp'].dt.date\n",
    "df['year']=df['crawl_timestamp'].dt.year\n",
    "df['month']=df['crawl_timestamp'].dt.month\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "74575ebf",
   "metadata": {},
   "outputs": [],
   "source": [
    "##df[['main_category','primary_category', 'secondary_category','tirnaty_category']] = df.product_category_tree.str.split(expand=True)\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f94c7fab",
   "metadata": {},
   "outputs": [],
   "source": [
    "##Separating product category tree to different level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "56711af5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['main_category']=df['product_category_tree'].apply(lambda x :x.split('>>')[0][2:len(x.split('>>')[0])-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "27f8c628",
   "metadata": {},
   "outputs": [],
   "source": [
    "def primary_category(value):\n",
    "    try:\n",
    "        return value.split('>>')[1][1:len(value.split('>>')[1])-1]\n",
    "    except IndexError:\n",
    "        return 'None'       \n",
    "def secondary_category(value):\n",
    "    try:\n",
    "        return value.split('>>')[2][1:len(value.split('>>')[2])-1]\n",
    "    except IndexError:\n",
    "        return 'None'\n",
    "def tertiary_category(value):\n",
    "    try:\n",
    "        return value.split('>>')[3][1:len(value.split('>>')[3])-1]\n",
    "    except IndexError:\n",
    "        return 'None'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7984f328",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['primary_category']=df['product_category_tree'].apply(primary_category)\n",
    "df['secondary_category']=df['product_category_tree'].apply(secondary_category)\n",
    "df['tertiary_category']=df['product_category_tree'].apply(tertiary_category)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "294bc4e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "        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>uniq_id</th>\n",
       "      <th>crawl_timestamp</th>\n",
       "      <th>product_url</th>\n",
       "      <th>product_name</th>\n",
       "      <th>product_category_tree</th>\n",
       "      <th>pid</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>discounted_price</th>\n",
       "      <th>image</th>\n",
       "      <th>is_FK_Advantage_product</th>\n",
       "      <th>...</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_specifications</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
       "      <td>SRTEH2FF9KEDEFGF</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>[\"Furniture &gt;&gt; Living Room Furniture &gt;&gt; Sofa B...</td>\n",
       "      <td>SBEEH3QGU7MFYJFY</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>[\"Footwear &gt;&gt; Women's Footwear &gt;&gt; Ballerinas &gt;...</td>\n",
       "      <td>SHOEH4GRSUBJGZXE</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>AW</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Footwear</td>\n",
       "      <td>Women's Footwear</td>\n",
       "      <td>Ballerinas</td>\n",
       "      <td>AW Bellies\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
       "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>[\"Pet Supplies &gt;&gt; Grooming &gt;&gt; Skin &amp; Coat Care...</td>\n",
       "      <td>PSOEH3ZYDMSYARJ5</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Pet Supplies</td>\n",
       "      <td>Grooming</td>\n",
       "      <td>Skin &amp; Coat Care</td>\n",
       "      <td>Shampoo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            uniq_id           crawl_timestamp  \\\n",
       "0  c2d766ca982eca8304150849735ffef9 2016-03-25 22:59:23+00:00   \n",
       "1  7f7036a6d550aaa89d34c77bd39a5e48 2016-03-25 22:59:23+00:00   \n",
       "2  f449ec65dcbc041b6ae5e6a32717d01b 2016-03-25 22:59:23+00:00   \n",
       "3  0973b37acd0c664e3de26e97e5571454 2016-03-25 22:59:23+00:00   \n",
       "4  bc940ea42ee6bef5ac7cea3fb5cfbee7 2016-03-25 22:59:23+00:00   \n",
       "\n",
       "                                         product_url  \\\n",
       "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
       "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
       "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
       "\n",
       "                            product_name  \\\n",
       "0    Alisha Solid Women's Cycling Shorts   \n",
       "1    FabHomeDecor Fabric Double Sofa Bed   \n",
       "2                             AW Bellies   \n",
       "3    Alisha Solid Women's Cycling Shorts   \n",
       "4  Sicons All Purpose Arnica Dog Shampoo   \n",
       "\n",
       "                               product_category_tree               pid  \\\n",
       "0  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2FF9KEDEFGF   \n",
       "1  [\"Furniture >> Living Room Furniture >> Sofa B...  SBEEH3QGU7MFYJFY   \n",
       "2  [\"Footwear >> Women's Footwear >> Ballerinas >...  SHOEH4GRSUBJGZXE   \n",
       "3  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2F6HUZMQ6SJ   \n",
       "4  [\"Pet Supplies >> Grooming >> Skin & Coat Care...  PSOEH3ZYDMSYARJ5   \n",
       "\n",
       "   retail_price  discounted_price  \\\n",
       "0         999.0             379.0   \n",
       "1       32157.0           22646.0   \n",
       "2         999.0             499.0   \n",
       "3         699.0             267.0   \n",
       "4         220.0             210.0   \n",
       "\n",
       "                                               image  is_FK_Advantage_product  \\\n",
       "0  [\"http://img5a.flixcart.com/image/short/u/4/a/...                    False   \n",
       "1  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...                    False   \n",
       "2  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...                    False   \n",
       "3  [\"http://img5a.flixcart.com/image/short/6/2/h/...                    False   \n",
       "4  [\"http://img5a.flixcart.com/image/pet-shampoo/...                    False   \n",
       "\n",
       "   ...       overall_rating         brand  \\\n",
       "0  ...  No rating available        Alisha   \n",
       "1  ...  No rating available  FabHomeDecor   \n",
       "2  ...  No rating available            AW   \n",
       "3  ...  No rating available        Alisha   \n",
       "4  ...  No rating available        Sicons   \n",
       "\n",
       "                              product_specifications        date  year month  \\\n",
       "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016     3   \n",
       "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  2016-03-25  2016     3   \n",
       "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  2016-03-25  2016     3   \n",
       "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016     3   \n",
       "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  2016-03-25  2016     3   \n",
       "\n",
       "   main_category       primary_category          secondary_category  \\\n",
       "0       Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "1      Furniture  Living Room Furniture          Sofa Beds & Futons   \n",
       "2       Footwear       Women's Footwear                  Ballerinas   \n",
       "3       Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "4   Pet Supplies               Grooming            Skin & Coat Care   \n",
       "\n",
       "                                   tertiary_category  \n",
       "0                                             Shorts  \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  \n",
       "2                                        AW Bellies\"  \n",
       "3                                             Shorts  \n",
       "4                                            Shampoo  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbe31b86",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "71bbea71",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('product_category_tree', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e04d2e8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>uniq_id</th>\n",
       "      <th>crawl_timestamp</th>\n",
       "      <th>product_url</th>\n",
       "      <th>product_name</th>\n",
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       "      <th>description</th>\n",
       "      <th>...</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_specifications</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>SRTEH2FF9KEDEFGF</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
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       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
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       "      <td>Shorts</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>SBEEH3QGU7MFYJFY</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
       "      <td>False</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>SHOEH4GRSUBJGZXE</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of AW Bellies Sandals Wedges Heel...</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>AW</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Footwear</td>\n",
       "      <td>Women's Footwear</td>\n",
       "      <td>Ballerinas</td>\n",
       "      <td>AW Bellies\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>PSOEH3ZYDMSYARJ5</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Specifications of Sicons All Purpose Arnica Do...</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Pet Supplies</td>\n",
       "      <td>Grooming</td>\n",
       "      <td>Skin &amp; Coat Care</td>\n",
       "      <td>Shampoo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            uniq_id           crawl_timestamp  \\\n",
       "0  c2d766ca982eca8304150849735ffef9 2016-03-25 22:59:23+00:00   \n",
       "1  7f7036a6d550aaa89d34c77bd39a5e48 2016-03-25 22:59:23+00:00   \n",
       "2  f449ec65dcbc041b6ae5e6a32717d01b 2016-03-25 22:59:23+00:00   \n",
       "3  0973b37acd0c664e3de26e97e5571454 2016-03-25 22:59:23+00:00   \n",
       "4  bc940ea42ee6bef5ac7cea3fb5cfbee7 2016-03-25 22:59:23+00:00   \n",
       "\n",
       "                                         product_url  \\\n",
       "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
       "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
       "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
       "\n",
       "                            product_name               pid  retail_price  \\\n",
       "0    Alisha Solid Women's Cycling Shorts  SRTEH2FF9KEDEFGF         999.0   \n",
       "1    FabHomeDecor Fabric Double Sofa Bed  SBEEH3QGU7MFYJFY       32157.0   \n",
       "2                             AW Bellies  SHOEH4GRSUBJGZXE         999.0   \n",
       "3    Alisha Solid Women's Cycling Shorts  SRTEH2F6HUZMQ6SJ         699.0   \n",
       "4  Sicons All Purpose Arnica Dog Shampoo  PSOEH3ZYDMSYARJ5         220.0   \n",
       "\n",
       "   discounted_price                                              image  \\\n",
       "0             379.0  [\"http://img5a.flixcart.com/image/short/u/4/a/...   \n",
       "1           22646.0  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...   \n",
       "2             499.0  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...   \n",
       "3             267.0  [\"http://img5a.flixcart.com/image/short/6/2/h/...   \n",
       "4             210.0  [\"http://img5a.flixcart.com/image/pet-shampoo/...   \n",
       "\n",
       "   is_FK_Advantage_product                                        description  \\\n",
       "0                    False  Key Features of Alisha Solid Women's Cycling S...   \n",
       "1                    False  FabHomeDecor Fabric Double Sofa Bed (Finish Co...   \n",
       "2                    False  Key Features of AW Bellies Sandals Wedges Heel...   \n",
       "3                    False  Key Features of Alisha Solid Women's Cycling S...   \n",
       "4                    False  Specifications of Sicons All Purpose Arnica Do...   \n",
       "\n",
       "   ...       overall_rating         brand  \\\n",
       "0  ...  No rating available        Alisha   \n",
       "1  ...  No rating available  FabHomeDecor   \n",
       "2  ...  No rating available            AW   \n",
       "3  ...  No rating available        Alisha   \n",
       "4  ...  No rating available        Sicons   \n",
       "\n",
       "                              product_specifications        date  year  month  \\\n",
       "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016      3   \n",
       "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  2016-03-25  2016      3   \n",
       "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  2016-03-25  2016      3   \n",
       "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016      3   \n",
       "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  2016-03-25  2016      3   \n",
       "\n",
       "   main_category       primary_category          secondary_category  \\\n",
       "0       Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "1      Furniture  Living Room Furniture          Sofa Beds & Futons   \n",
       "2       Footwear       Women's Footwear                  Ballerinas   \n",
       "3       Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "4   Pet Supplies               Grooming            Skin & Coat Care   \n",
       "\n",
       "                                   tertiary_category  \n",
       "0                                             Shorts  \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  \n",
       "2                                        AW Bellies\"  \n",
       "3                                             Shorts  \n",
       "4                                            Shampoo  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aaa5ba91",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ef874569",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2016, 2015], dtype=int64)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## how many years of data\n",
    "df.year.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "216ac4de",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e4bede1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year\n",
       "2015    12009320.0\n",
       "2016    27304790.0\n",
       "Name: discounted_price, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which year the sale is maximum\n",
    "df.groupby('year').discounted_price.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ece9e5a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "32251743",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  month\n",
       "2015  12       12009320.0\n",
       "2016  1        21498650.0\n",
       "      2          264539.0\n",
       "      3         2507724.0\n",
       "      4         1391281.0\n",
       "      5          704162.0\n",
       "      6          938434.0\n",
       "Name: discounted_price, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## each year on which month the sale is high\n",
    "df.groupby(['year','month']).discounted_price.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cf976bbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x='month', y='discounted_price', data=df, hue='year')\n",
    "plt.xlabel('Month', fontsize=12)\n",
    "plt.ylabel('Sales Amount', fontsize=12)\n",
    "plt.title('Sales vs Year', fontsize=20, fontstyle='italic');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0181daff",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ec89963b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12    10315\n",
       "1      4850\n",
       "3      1634\n",
       "4      1137\n",
       "6      1046\n",
       "5       773\n",
       "2       245\n",
       "Name: month, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## in which month of the year most orders are placed\n",
    "df.month.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b00678ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22175c9ff40>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='month', hue='year', data=df)\n",
    "plt.legend(loc=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "040e9e64",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bee258c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "266"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## unique category\n",
    "df.main_category.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "86f08352",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Clothing                                                6198\n",
       "Jewellery                                               3531\n",
       "Footwear                                                1227\n",
       "Mobiles & Accessories                                   1099\n",
       "Automotive                                              1012\n",
       "                                                        ... \n",
       "Bengal Blooms Rose Artificial Plant  with Pot (3...\"       1\n",
       "Pazel Slim Fit Men's Jeans\"                                1\n",
       "SMART TRADERS Girls Bellies\"                               1\n",
       "Eternal Gandhi Super Series Crystal Paper Weight...\"       1\n",
       "Areon Luxurious Fragrance Long Lasting Car,Home,...\"       1\n",
       "Name: main_category, Length: 266, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## under which category most of the time product purchased by customer\n",
    "df['main_category'].value_counts().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f3568c92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Clothing', 'Jewellery', 'Footwear', 'Mobiles & Accessories',\n",
       "       'Automotive', 'Home Decor & Festive Needs', 'Beauty and Personal Care',\n",
       "       'Home Furnishing', 'Kitchen & Dining', 'Computers'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['main_category'].value_counts()[:10].sort_values(ascending=False).index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6ecc2033",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "sns.countplot(y='main_category', data=df,\n",
    "              order=df['main_category'].value_counts()[:10].sort_values(ascending=False).index)\n",
    "plt.ylabel('Main Category', fontsize=15)\n",
    "plt.xlabel('Count', fontsize=15);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "437ff210",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "091589ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "main_category\n",
       "Jewellery                                               19578167.0\n",
       "Clothing                                                 4408329.0\n",
       "Furniture                                                3080605.0\n",
       "Home Decor & Festive Needs                               1701745.0\n",
       "Watches                                                  1355850.0\n",
       "                                                           ...    \n",
       "Sisel Printed Poly Cotton Women's Stole\"                     128.0\n",
       "Siemens 5SL Betagard 5SL MCB (1)\"                            120.0\n",
       "INKT INKT A5 Wiro Notebook A5 Notebook Ring Boun...\"           0.0\n",
       "fourgee Slim Fit Boy's Black Jeans\"                            0.0\n",
       "Disney Printed Baby Boy's Hooded Grey T-Shirt\"                 0.0\n",
       "Name: discounted_price, Length: 266, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which main category has more sales value\n",
    "df.groupby('main_category').discounted_price.sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a2b3efef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Jewellery', 'Clothing', 'Furniture', 'Home Decor & Festive Needs',\n",
       "       'Watches', 'Footwear', 'Automotive', 'Computers',\n",
       "       'Mobiles & Accessories', 'Home Furnishing'],\n",
       "      dtype='object', name='main_category')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('main_category').discounted_price.sum().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ec869207",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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04SGeZmZm9pEpJRFDgZ2AB4HvAPdKul/SkcCiPRGcmZmZta52k4iIeDsiLoyIzYC5gX3JJo5jgNvImolNJXlNDTMzs36oQ/NERMSrEXF2RKwNzAccAtxRfj4j6ZpujNHMzMxa0FRPNhUR4yLilIhYBVgYOJpMLMzMzKwf6dSMlRHxREQcFxFLd1VAZmZm1jt0KokwMzOz/stJhJmZmTXFSYSZmZk1pUeTCEnnSnqhftVPSbNLuk7So+XnbHXbjpA0RtIjktavK19B0n1l26mSVMoHS7q4lN8maXhPvj8zM7P+pOkkQtLnJW0h6TNT8bTzgQ0ayg4HRkXEosCo8hhJSwAjgSXLc34laWB5zhnAPuSkV4vWveZewCsRsQhwMvDTqX1fZmZm1jEdSiIknSnp13WPtwfuA/4MPCzpSx15nYi4CXi5oXhz4Lfl/m+BLerKL4qI9yLiCWAMsHJZinxIRNwSEQFc0PCc2mtdCqxdq6UwMzOzrtXRmogNgJvqHv8IuBD4DHBtedysuSPieYDyc65SPgx4pm6/saVsWLnfWD7ZcyLiQ+A1YI5OxGZmZmbt6GgSMRfl5CxpUWAR4ISIGAecBSzfDbG1VYMQUyif0nM++eLSPpJGSxo9YYJXMzczM5taHU0iXibXzwBYBxhXWxacPHEPbPNZHTO+NFFQfr5QyscC89ftNx/wXCmfr43yyZ4jaRAwC59sPgEgIs6KiBUjYsWhQ4d2InwzM7P+qaNJxDXADyUdQHZ8vKRu21LAk52I4Upgt3J/N+CKuvKRZcTFQmQHyttLk8cbklYp/R12bXhO7bW2AW4o/SbMzMysiw3q4H6HkKMd9iX7RvygbtuWwN868iKSLgTWAuaUNLa8zk+ASyTtBTwNbAsQEQ9IuoRcivxD4ICImFheaj9ypMf0ZIJTWwDsHOB3ksaQNRAjO/j+zMzMbCp1KImIiNeAPdvZtnpHf1lE7NDOprXb2f844Lg2ykeTNSCN5e9SkhAzMzPrXh2tiQA+mrthBbLfwbkRMU7SIsD4iHijOwI0MzOz1tShJELSTMC5ZD+DD8rz/gaMA35MNkN8u5tiNDMzsxbU0Y6VJwFfIpsdZmbyoZRX88lZKM3MzKyP62hzxlbAwRFxY93U0zVPAQt2bVhmZmbW6jpaEzE98FI722YGJrazzczMzPqojiYRd5DzMbRlG+A/XROOmZmZ9RYdbc74HnC9pOuBP5FTSW8k6ZtkErFGN8VnZmZmLapDNRER8S+yU+Vg4DSyY+UxwGeBdSLijm6L0MzMzFpSh+eJiIh/A6tLmh6YDXg1It7utsjMzMyspU3VZFMAEfEO8E43xGJmZma9SLtJhKQTpuJ1IiIO64J4zMzMrJeYUk3E1KxBEYCTCDMzs36k3SQiIhbqyUDMzMysd+noPBFmZmZmk+lwx0pJAkYAiwHTNW6PiF91YVxmZmbW4jq6iufcwChgCbL/Q20BrqjbzUmEmZlZP9LR5oyfA68B85MJxBeB4cD3gUfJ2gkzMzPrRzranLEmcDDwfHmsiHga+LGkAWQtxPrdEJ+ZmZm1qI7WRMwKTIiIScDrwFx12/4DfKmL4zIzM7MW19Ek4glg3nL/AWCnum2bAi93ZVBmZmbW+jranPFXYD3gEuBY4ApJY4EPgAXwRFNmZmb9ToeSiIg4ou7+NZJGAFuSQz2vi4hruik+MzMza1FTvQAXQFn6u8uW/5b0OeDiuqLPAkeRfTG+Ckwo5d+NiKvLc44A9gImAgdFxLWlfAXgfGB64Grg4IioH4pqZmZmXWCqkwhJM5An788D44ALIuKpzgQREY8Ay5XXHwg8C1wO7AGcHBEnNsSwBDASWBL4DHC9pMUiYiJwBrAPcCuZRGwAuKbEzMysi7XbsVLSzyX9r6FsZuAu4BRge7K24B5JXTlPxNrAY5+SmGwOXBQR70XEE8AYYGVJ8wJDIuKWUvtwAbBFF8ZmZmZmxZRGZ3wZ+H1D2bfJiaW+GhFzkrUAT5KTTnWVkcCFdY8PlHSvpHMlzVbKhgHP1O0ztpQNK/cbyz9B0j6SRksaPWHChLZ2MTMzsymYUhIxHLizoWxr4MGIOBcgIiaQs1mO6IpgJE0LbAb8qRSdASxMNnU8X34XfDztdr2YQvknCyPOiogVI2LFoUOHdiZsMzOzfmlKScQg4N3aA0mzA4sDNzTs9yQwTxfFsyFwV0SMB4iI8RExsUxydTawctlvLDkFd818wHOlfL42ys3MzKyLTSmJ+B+wVt3jTcrPaxv2m4uum2xqB+qaMkofh5otgfvL/SuBkZIGS1oIWBS4PSKeB96QtEpZdXRX4Iouis3MzMzqTGl0xmnA2ZJmAcYDB5EzV/69Yb/1+Pjk3rQy6mNd4Gt1xSdIWo5skniyti0iHpB0CfAg8CFwQBmZAbAfHw/xvAaPzDAzM+sW7SYREXF+qQk4gJyv4S7yZP1BbR9JQ8mREsd0NpCIeBuYo6FslynsfxxwXBvlo4GlOhuPmZmZTdkU54mIiOOB46ewfQJd1x/CzMzMepGOLsBlZmZmNhknEWZmZtYUJxFmZmbWFCcRZmZm1hQnEWZmZtYUJxFmZmbWFCcRZmZm1hQnEWZmZtYUJxFmZmbWFCcRZmZm1hQnEWZmZtYUJxFmZmbWlCkuwGXNO/TQQxk3bhzzzDMPJ5xwQtXhmJmZdTknEd1k3LhxPPvss1WHYWZm1m3cnGFmZmZNcRJhZmZmTXESYWZmZk1xn4h2rPCdCzr1/JlffIOBwNMvvtHp17rzZ7t26vlmZmbdwTURZmZm1hTXRJjZFHm4spm1p2VqIiQ9Kek+SXdLGl3KZpd0naRHy8/Z6vY/QtIYSY9IWr+ufIXyOmMknSpJVbwfs76iNlx53LhxVYdiZi2mZZKI4ssRsVxErFgeHw6MiohFgVHlMZKWAEYCSwIbAL+SNLA85wxgH2DRctugB+M3MzPrN1otiWi0OfDbcv+3wBZ15RdFxHsR8QQwBlhZ0rzAkIi4JSICuKDuOT1q0rQzMnHwECZNO2MVv97MzKzbtVKfiAD+LimAMyPiLGDuiHgeICKelzRX2XcYcGvdc8eWsg/K/cbyHvfWoutV8WvNzMx6TCslESMi4rmSKFwn6eEp7NtWP4eYQvknX0Dah2z2YIEFFpjaWM3MzPq9lmnOiIjnys8XgMuBlYHxpYmC8vOFsvtYYP66p88HPFfK52ujvK3fd1ZErBgRKw4dOrQr34qZmVm/0BJJhKQZJc1cuw+sB9wPXAnsVnbbDbii3L8SGClpsKSFyA6Ut5emjzckrVJGZexa9xwzMzPrQq3SnDE3cHkZjTkI+GNE/E3SHcAlkvYCnga2BYiIByRdAjwIfAgcEBETy2vtB5wPTA9cU25mZmbWxVoiiYiIx4Fl2yh/CVi7neccBxzXRvloYKmujtHMzMwm1xLNGWZmZtb7OIkwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMDMzs6Y4iTAzM7OmtEQSIWl+STdKekjSA5IOLuVHS3pW0t3ltlHdc46QNEbSI5LWrytfQdJ9ZdupklTFezIzM+vrBlUdQPEhcEhE3CVpZuBOSdeVbSdHxIn1O0taAhgJLAl8Brhe0mIRMRE4A9gHuBW4GtgAuKaH3oeZmVm/0RJJREQ8Dzxf7r8h6SFg2BSesjlwUUS8BzwhaQywsqQngSERcQuApAuALXASYf3UaYdc1enXePXFtz762dnXO/Dnm3Y6HjNrHS3RnFFP0nBgeeC2UnSgpHslnStptlI2DHim7mljS9mwcr+xvK3fs4+k0ZJGT5gwoSvfgplZn3fooYey6667cuihh1YdilWopZIISTMBlwHfiIjXyaaJhYHlyJqKn9d2bePpMYXyTxZGnBURK0bEikOHDu1s6GZm/cq4ceN49tlnGTduXNWhWIVaJomQNA2ZQPwhIv4MEBHjI2JiREwCzgZWLruPBeave/p8wHOlfL42ys3MzKyLtUQSUUZQnAM8FBEn1ZXPW7fblsD95f6VwEhJgyUtBCwK3F76VrwhaZXymrsCV/TImzAzM+tnWqJjJTAC2AW4T9Ldpey7wA6SliObJJ4EvgYQEQ9IugR4kBzZcUAZmQGwH3A+MD3ZodKdKq1lHHrooYwbN4555pmHE044oepwzMw6pSWSiIj4F233Z7h6Cs85DjiujfLRwFJdF51Z16m1I5tV6eijj+70a7z88ssf/ezs63VFPFaNlmjOMDMzs97HSYSZmZk1pSWaM8x6g3+usWanX+OdQQNB4p2xYzv9emve9M9Ox2Nm1hmuiTAzM7OmuCbCzMym2uDBgyf7af2TkwgzM5tqSy+9dNUhWAtwEmHWg2aNmOynmVlv5iTCrAftPHFS1SGYWS/RGyancxJhZlax3nCysJ7XGyancxJhZlax3nCy6AucrHU9JxFm1uf05MnioeNu6PRrvP/yOx/97OzrLX7kVzodT1/Vk8naspde2+nXmO3NtxkIPP3m251+vXu2Wb/T8bTFSYSZtZTjdt6m06/x4Auv8c7ESbw87vlOvd6Rv7+007GY9WVOIszMKjbHdLNM9tMMYOLMs0z2sxU5iTCzPme6gQMm+9nqDlx+x6pDaHmX/GnlTr/Gm2/OCAzgzTef6dTrbbft7Z2OpSNe33S7Hvk9neEkwsymaMZph0z2szdYfo6Zqw7BrF9wEmFmUzRi4a2qDsHMWpSTiD7i6R+21hS0Cxx1X9UhmJlNZuaZJ0320zrPSYSZmfULG2/yTtUh9Dm9o9eRmZmZtRwnEWZmZtYUJxFmZmbWlD6ZREjaQNIjksZIOrzqeMzMzPqiPpdESBoInA5sCCwB7CBpiWqjMjMz63v6XBIBrAyMiYjHI+J94CJg84pjMjMz63P6YhIxDHim7vHYUmZmZmZdSBFRdQxdStK2wPoRsXd5vAuwckR8vWG/fYB9ysPPAY90QzhzAi92w+t2J8fc/XpbvOCYe0Jvixccc0/orngXjIihnX2RvjjZ1Fhg/rrH8wHPNe4UEWcBZ3VnIJJGR8SK3fk7uppj7n69LV5wzD2ht8ULjrkntHq8fbE54w5gUUkLSZoWGAlcWXFMZmZmfU6fq4mIiA8lHQhcCwwEzo2IByoOy8zMrM/pc0kEQERcDVxddRx0c3NJN3HM3a+3xQuOuSf0tnjBMfeElo63z3WsNDMzs57RF/tEmJmZWQ9wEtFCJKnqGMzMzDrKSURrmbHqAMza05eT3L783qy1NB5rvf3YcxLRIiQtCJwrac6qY5kaknrNMVT7sPb2D20VJClKBypJI9ra3vNRdY2G97a1pAWqjqmj2vu796bPZX/ScKztLmmJaJGOiZIWl7Ts1D7PB1rF6r4EBgCvUkbMtPqXgKRlJc0fEZNaPVaY/MMLzFRpML2YpAOAsyXNX1dW/8W4RVtJRiuri31zYG/gvWoj6piGv/tekr5WW7U4IiZVG1376pL5lSStUnU8Panu//V14JtApQlE3f9iOeBQ4DtTu2Bly3/59wNzAkTEE8AHwKnlcct9CdQdcEsARwK/kDSsNyQSdR/erwFnSjpM0pYVh9XyJH0G8u8naWNgL2CtiHhG0hKSZgVqx8V3gEOAlxpeo+VrKSStCuwE/Ckixrf68QyTHdMHArsC95Angf0qDexTlGNpC+AMYHD9tt5wrHSWpEWBHYH1gYclbVBuPV4LXf4XmwC/Bl4AZgMOlLR8R1+j5T8ofZmkpYHzJB0naRbg+8DjkpYs21vqA1UOuM3IcctPkpN5nSxpwd6QSJR1VHYBjgW2BVp2KtlWIGku4KyyzgzkFfrlwOaSfgT8H3A2sEipBt0sIlYnj+EvSRoJH5/sWkkbn63pgInABpIWbcUkvqb2OZM0UNIMwBfIE9KXgP+Q/7PpKgxxiiQNJ696t4iIf0r6rKT1oTWPlc5q41h7B3iKrIk4BzgI+BGwZg+HhqTBwFbAERFxGPA94HlgP0mLd+Q1WvpLvy+qu5ofARxDHjwLAkcBfwRWAkZA632gJA0CtgO+GxGHAt8mFy47XtJnSiLRUolPTUnShgIHACsArwA/KNu8ymvb3iCvUDaStDVwF3msrgn8A1ieTCyWAN4EZpL0c+Bk4FvAr0rNT0tpaAZYqSRLtwBHk+vsbCNp4QpDnKK6BGd4RLwNzEAmc6sA20XERGBPSetWFWN7ygXSMPICZFtJPwN+Dlwi6aBKg+sGDcfaGqXG6yXgD+R30KkRsRHwF2DVno4vIt4Dpgc2KY//S9ZoLQ3sXquJnBInET2sXM2vBWwAnBYRt5FVxMcAfy277TO17VI9ZABZ3fXF8ngMMJo8sRwtaY5WSXzqkxlJXwW2Jk+KVwC7R8S6ZYr0rwNbtHotShUi4h3yCv0V4DByNdy9gV0iYhSwOpn0vgm8CxxIHh/nRsQ2wHdowVlxG5oBfgl8AzidrM49m0w295C0UFUxTonSAsCtyg7ZVwM7AD+IiHck7QjsCzxaZZw1dRdOnyf/vg8DPyVrT24EtiGbkmZs1YuQZtUdawcAPwE2Bp4Abo+In0TE3ZJ2BrYn/zbdqu5/sZikFUrxT4EZJO1dHj8OPAYMJxewnCJ/cfaguhPVLmSfglrb8aSIeD0ifgnsDowC5ur5CCdXd8AtXqp43yev3r8saafyARkH/BeYhlxSvSXUfXg3AxYDriO/bG8GbpQ0i6SdyATuxlauvq6KpH2Bw8mrpFHAAZJ2K4nwNmT/nTfIZOJ84KmI2DMi7iyJ2zeBGyoJ/lMoO1FuD3wFmB1YDriAPJ4vIK+UX68qvvbUrmwj4mnyCn79iLiAvAi5QtLZZFK0Y0Q8WV2kHyvHy6rAxeSF00sR8Wdg47JEwRrkieyuVrkI6SxJQ+vur0Be6a8DjCdrbyeUbUuSzQk7RMQj3R1X+V9sQH6mfyfpJ2Qz3ihgpKSryQuto8lmjaU68qK+dfONj6cXn6Ou7Ezgobpt09Zt+y1wcovEvB555XAHcAQft78+UuJ8GliSvJLbqVX+1uX+jOSIl1vqyjYBfkZeAf0NWLrqmFv1RvYdWa/cn5282q1dOS5HJl+QycRl5EXJzGTS9k9gqarfQ+NxQXYCHUD2HxgGfA24vty/qtyfo/7zWPUNmL/u/oi6+xtSFhosj1cCFgWGVR1zG+9hevLq9oaGskWA24BNq46xC9/rAmTfgunL43nIxO6HwN+BwaV8J7KmbsZujqf+O3GpcpwPB2YBLiqxLlg+u2uU+6uX7/iFP/X1q/6D9/Vb3ZfXhuWf92Ngz1L2h3Jyrn0JDCKvgC5shZMb2fHwUmAhst37l2QiMZysKVkN+Gz5Qr6vIwdcD8a+dPm5IJn1H9WwfRZghqrjbJVb/RdNXdnRJWkYUE6+w8tJ689kk9bpZDPHX4HpynM2AoZ09xdjs++tfKHPVPf4V8Cy5f7PyY5u8/dUbB2IfV7gu+V4nR64vcS4XfmfnAz8ouo42/ubA8uUY2VGYFryguTshn3nae8Y7I03sjlsCNmvYGtySPltwMN1++wI/AuYq5tjmbsc4wPL/+B4slP858v2+cm+eCdRks8S9186eg7yAlw9QNLKwLnkAXUc+Q/dKiJC0p+AJSJiSUkDooxyiAqq10v76iERcVDp3f1j8upz8Yh4VdIXyOaWN4ELIuJhScuQTRw/jIh7ejrmRqXJaG4yEbsyIk4qbdv/AU6PiGMrDbAFNXT+2pns1zCO7Gz4TbIW4mtkgrAF8O2IeLFUfS4CfK4cy18lvxy3iohXev6dTFnpuLch8CLwUkR8Q9KlZBv1U2QNy/YRMb7CMCcjqTaL7cJkUn8BmUCsQp6c/0g2yewRES9XEmQ7lMM4jwBuJS9Evkf207gVeCAidqwuuq7X8Dlakfz/fJGsqRtPfp7+SCaDXyL7Zt3XzTFNQ/7t3+fjIZxHkSNETouIMco5X04CvhelSaX0b3upnZed/Hc4ieh65aQ1X0TcXB5vRWaj/yMPqO0i4skyouE5ScvWn4DrD8YKYv8C+QX7VOm1fjrwFvD1iHijtO99FTixHIDTk9V2LfEFJmlQZIfJtcgT4KiIOFU5rOx/5MiSEysMsWVJ+hbZ8esCchTLb8jOs98kx/MvTp5w7yITzC8AW5JfTHeQ1bM7R8T9PR78p5C0HZkI1RL5z0bEhqWD4iHArMBJrZAIw0ejiSZGxJtlpMjqwFrAdRHxh7LPPmT184Zk09HzVcXbSNK8ZHPnlmQfsN3JIZ3jynfG3eQw6/uq+q7rLpJ2I0fY/YL8v32x3B9P9ouYEbg+Isb0YEy/JmsY1iUvsvYha4bOjIj/SRocEe9JGhg5uqfjr93H/n8toXQ6OxvYOiJuKDURvwUmkRP1TFBO8LEBeVX3boXhAjnmvHbwSLoFeC8i1ipfBkeSJ5FDIuJ1STOXhKKSGpP2SPoi+aX1o4h4S9LqZNZ9Y0T8uJwwpouI/1UaaAuSNBPw84j4mqRvA2uTV+bfJtt4HwA2JZsvfgDcT15VTSBPEi8DN0fEwxWE/6lKR8oXgJXJGpVNIuIDSYuUZLhljmVJ05LDaJciTzgzkE2Jq5Enobsj4oyy72xkf7lXq4k21U5C5f4QcuK8X5DHzbbkVfcYSWtHxKgqL5S6k6TVyFlPfxgRj5fvnI3JhPvPEXFND8WhUjv40XEt6Vdk8/OWZCJxMFkrfhj5fd/U8e/RGV1I0jBJK0XEpcD+5PTAawN3AteQIwQWKj2VjwWubZEEYkBETFTOA0FErJrFuqpc3RxHHiu/lDSQrJmg6i9dSXOUD2mtyWgR8kv3m5JmKjVBZwFHSNo9Ip52ApFqI2/qBDC7pGvIk9VmEfFWKX+brDK/NCJuJ5sshgK7kbVQP42Is1sxgZC0W2lye5fsz7FBRKxfEoi9yBkeZ6j6WK4XOQpqLDCSrD35S/kcXk+Odlmq1BoREa+0QAIxANhV0k7KmQ5/TV50vAt8HTiwJBBfAU6StFhfSSBqnyNJA5QTN40k509ZvdSKPg1cCTxITmQ2Uxufva6MZxZJ85QEYiPgOEk/AIiI/clmuz+RCfUvySbedzpz/Lsmogsp5xzYEfhWRNyiHEJ4DDkl7QtkteNIcujM7yLiioqbLmYjr8yfV84YtybwQkScUrbfTDZtbKGcdGS2iHigiljbopx3f2/yy2oIOcHR8uTf+bWIOKY0a+xL1viMrSjUltLQdjuCrE2YQFaNHwMcGhF/l7Q7OcRzL3IY2vLk3/GuUnNxLtm88b2I+KDn38knNX6eysl2NfJz912yOWNnSj8CcmhdSxzTbcT+a3Lo9DPAeaWJcTpyaOoSwE9ape9JqX0YR15gjChV5BuSo7vmJ0fr7EceW/9XXaRdp+FzNGdkP6GBZN+P2YA/lqS7Nn38292Z8ClnL/052cl9DHAKORLta+T3+mZlvwvIDrvrd0Xy7CSiiynXD1ibrM76j3Kq5aPIjk//UnaUioh4u+IEYkbyS/V1smr6BDIzPQy4JHIKVCTdBYyPiA2riLMtktYhe3k/R2bVawH7R8TF5Ut2dfKksRQ5WdK2roH4JEmHkFWtD5HDu35HduD7Btn5bT3y2Ni4lG8NfAb4TUT8txxDQ1qpLb5G0g5kzYPIL9H7IuIqSceS69XMCPw4Ih6qMMyPNJyQViQ7vj1KVj/vTtYEHk4Op54XuDUiKp/Hor7anKz124z8u55Stn8W+DJZM/FgRPyjrzVlSNqf7Oz6AvBoRBwp6Tjyu+fPEfHvHoxlC7K54i3ymK81e/2H/B7fsjxeKrqo75KTiC7QxhXEQWT78Q9KIrEjmRXuFBHXVRTmJyg7fH6RrJr+d0Sco5wC+mLgXxFxeNlv1Yi4pcJQJyNpT7Ja92nyRPdFYFmyam5U2WcOcr6C5yLiqapibUWlOnU54PiI2KBc8c4eEduVK6kFyKvd7cjRCo+W5y1JHtdLkP0nWqITInziJDyEnADtaXI45KrA6xFxRN3+U92BrCeU7469yNhnIWvXpiNHxaxEJhDrlGrylqDsjL00OUmRyKr7MyPi6NKU9GZEPF5ljN1F0qZk7d3OZD+QC8mRYAeTQytfBI7r7mZrTd6nbRUy4XwRODbKpGOS7gGejZxmu8u03JS0vU1dJr4GeeX7BDmiYSJwlKSjI+KP5cv5wypjBShX6guUK/P/kL3S5wPWlTQqctTItsA1kqaNiG+1UgIBEBHnKheHeQtYMiL+Julgsi/EBHJI4vCIOL/KOFuJsh/OIRGxTTlepwEelXQkmTRsU3ZdizwuJgFHR8SjkmaMiLci4gFJQR7bLTMMEiaboXTJEucPgc3JpoAtyLUkpo+Ib5T9WzGBWIpM3r4cES8rl/X+LtmT/hiyCebBVkogilnI/jGzRI6E+hJwp7JT9ppkk2OfSCLaqEWZCPxfRDxYtq9CNt0sTQ5vHdwDCYQi+7StRx47R0g6jazBWlfStZH9wZYt/5uuFS0wOUdvv5FXZ3eQnSlvIvtEQA4du5nJZ5mrdEIV8uA+nGy+uJas2l2HrCn5BmWiHbLaetWq/7ZT+ruRi5c9Sw7Xg1y74U6yen6xqmNutRs5A92F5f5AcpKou8gkchmy78iD5LjynwB/a3j+9mT79sCq30tdTNPV3V+AbN46iUwk/15ino/slHgNMGvVMdfFq4bHQ8mJvBavK/s9WWNUebxtxL8wZVIxsgnxKuDg8ng+cqXONaqOszv+X2SyPZScvfcBsr9YbdtZwJo9HNuG5BD2r9SVfZFsovw6sGB3/W6PzugEpWnIdsANyDb66YBLACLi5+TMXx91Oovy363Qk+QsjvuRTRgvRsT15MyECwA7KZf2fi5apAaioap67dLeTUR8HzgNuEXSwhFxGlmtuF64DwTw0WQzAETE54DFJF0aeSV+LjmT3qnkEOTjyYlwXiGHcT4n6SxJs5a+PUeTV1YtcRVfOpJtL2np0r/jMGBP8uR2ILkewHbkGjU7A7tGxSMZahqO6WHKHvUTgNeAVSTNXXb9D/n/aCmlufCbwHeVo1tuJjvxfV05GuCliDghIm6qNNAuVPf/OoQc9j5zRFxLfsffJWkT5aJuK5HNUd1G0rySRiiXg5+OnBRwr8gpBTaTdC553jmFnLOi20YfuU9EJ0iaLyLGljblGchpgXePHB+8MflBurXSIIuGL60NyElHBpLrSlxcykeSs+KdHhFPVBZsO5TLSn+D/IDOQU5eM1bSoeQJcHEnDx9TzpPxO3LI3UMRcUUp/we5WNZuyonRdib7SKwPfD8iTi7Nb8PIq/pBZG/z/aNFRjLUKJcoP4XsILx1lGGmpd/MomRisXdEnFtZkFNQmiy2IpdUP5VM6k4jO+m9T+kk3Ap/94bvEJFX45uRSc7JkXPHnEDOprlDRDxbWbDdRDlM9ViyhuVDSYuQtaEbkCfrz5D9EB7s5jh2JldQHhs5Idm3yKTuVnJ48IfAuhGxnMrIke6KxX0imqQcHnmCpF+S44BP4uMJRtYgv9h2rTDEj9T121iFbL54lWxr3Q34iqSXyRqKQeT69i3R5trwpbUyOUrgi5ETXv0SOF85/8MJkt6vNNjWNC85/HUdYG9Ja5by3YHbJP0sIr4D/Eg5BG0F8kryNeAP5TjYBnI0T+S8EZVraJe+hjwJLwQMkTQkckXcc8u+L5JX8y2h4ZiegYx7c7J28GqySWkk2ZdgMbID62MVhTuZ8h2yITllM8CJ5KiLtYGfSvo/clbT7/SVBKKNPhCDyHlTNiv9jFYhmwKXiYjL1UMddiPi98qVQk+TdFnk9P5PkRcLDyqXMFhW0izdmUDUgvFt6tufZi0/v0N2GhpKVp/eTV71PUguc9sKsdYW91qX7Nx0DHklvx+5dPdXgcvJnrzrVB1vXdz17Y8bkW309wCb15X/gszGW27Vwla4kcMCdyWrXg8hR7D8grziHU1WcY4ihyBvUJ6zOtkxbPvyvEvJL86WWByp4bhYmrKgFlmL8g9y7DvkSbhlVuJsI/a9yv/i92S1OGQ1+ATgoKpjbSf+FcpncEdyBdyzySGny5AXTTeSM4FWHms3/L+2q30/kqMurqj7zPys7n63fk4aX5+saTuHrAmprQ66JXAvuYZN9/+dqv5H9bZb+eL6DzlsbOXyhbts2bYUmZm2wgqcw+ruDykngy3K4yXLl8DetX1r76HVbuR6DBeWL9hjyc6Uq9VtP4EcbVJ5rK104+OmykFk7/6TS2KwcLm/Fnnle1c5od1Z/r6zktWyZ5FX+ctX/V7aeX8HkInQ74D/I6/kNyE7UJ5CJsULVh1nO7F/uSQ8x5W/8b6U1RzL98oTZMfQAVXHWhfzMuVkdUhd2S/I2TRrj2etP/b6yo2PLxAXaWPbSHLOmuE9GM9q5XtxgfJ4P+A8snPl7OV42rSn/hfuEzGVSpPAxeREMMeSNRHzkQsPtcSMiMrpq48FVoqItUvZSeTBfkFEvKucqfAEMoN+o7po21eGI32bXMb7/rohcAJuiIgbKg2wxenjVWEHkk0Yy5PT3m5ALin9DlklvTf5pXQ78AbZvj2hdJh7u5Lgp0A5L8F5ZA3VB5QhnGRtxDJkovSfaMH+MaUt+3Bgx4i4VzmHzBfJz+afI2K86tahaBXK6fsPI9dIOTJKE0vpX7NP5AyVfWoSKfhobpTzgQ0jZ6TchByh9HdgLnKRuu2im/us1DVJf4k89v9H9pu5LiIuUi7G9mWyZutvkUM+e+T/4dEZHSTp85L2IKuJDiLbAhckk4k1yDaygRWGCICkz5H9My4BXpD0l7LpLrKWZOHy+C2yb0Tlc1dMwdLk33g75ZwVtUWfZgBGKFcDND6ew79eSSAGRbbR/oNsZvs8uSTxV8ljdyGyhuqLwL/IxZK+JmmaVkkgau+t7j1+CNwf2e7+IvlFfgewduQogd+2SgLRxv/lJrKvykEAEfFH8v+xIrCpcubHyvv31P3Nlymdb/9NTqA0CdhQ0grlBDuMEm9fSCDa+H89Qv7PLpR0Bvm5WZkcDXEnOaSy2zu9lgRiFXLY7BYRsSn5eR0haWREnFUeP1M+7z32/3DHyo5bpNyuIGeRu5CcK/535KiMe6LioW+SliBrSc4nq0S/CvxK0h8jYsfyZfD98jlZjFzt8p2q4m2PcuGYlSNnvHuTrOLdWtKfIuIhSWcCL7di7FVo6Ky3OZkcDoqIUZE9yBcjj4v/kfOW/Al4jLxy/ww5sgFyhMBNwFnROmth1K+uOYQcAvk/YAlJ34uIY8t+QV4htszJrOH/sjzwYUTcp5wo7S5Jx0fEEeVK8kNyFdSWWAisnLS+TF6MXE2u4fFd4Kfk8N8dyPUZDoqcoK7X10I0/L/WJi8Ux5B/g/FkTdEYSQeQzRfv00OTrpWLw4XJ0TB/IufC+RO5QN665WLh9J6I5ROx9fL/e7eoZaPlg7Qy2VzxENkhcXuy+vc14JWI2LH+eVV9kJRT/V5O9qo/t6H8DGBSROxSeu0uRg4/vasVPvyNMSjXDjiWbLI4QTlcb1myXfJ3EdHKtSeVUc7auQ2Z2B5CVjP/szRv/ZasMbuBTChmIo+De8jOtm+QnRS3iBZZT6Jeqa7dipyB8r/ksX4lWcP2KNnZ76MpuluJcj2dzcnZDR8iT0r3kM1H/xcRB1cY3mTqqs1nJb/r7iUnU9qb7EdzMHnx+SOyb9h5rdoc2ixJ3yb71zxIXjgeFWWofvku2h/YrSdqIMrvXIHsj7I+mUR8k1wZ9Qbl+jUjybVUKhkG7OaMNkRR2r/OJU9gfyRHBpxL/hPvIq+OP19rxqj4ZPwOOV75MvioXwSRi/R8FZhW0lXA0xFxXUTcVbZXnUDMU5f9z1GK/0tOGTtC0qHlb/4/cvjYDNVE2nrqqpwHSBpOVuevTtYuPAw8qZwG+kPyy/9cMhGen6yS3ZLsjLUqORJj3VZJICTNU3d/G/KL+wdkArQpuajWOuQxP4jsk9QSCUR9lXipBdqSPAGPBK4jr+KnJduw15M0tK3mqCqU770NyRE8e5BLvb8OXECOvjibbNI4nZyGe9vad01fIOnz5Ey9a5GflYnA7ZKmK803q5CLKfZUArEc+b84IiLGR8TZ5Ei1EyWtHzns+ryqEgjAozPqb2T73lXl/kDyC2so+WG5B5inbt9pKD2qW+FG9qq/j7qhpZTe3eQKjSuSw09XqjrWuvg2Jq/G5gG+QJ4QvlC2DSI7nN1CjjuHnJu/8rhb7UbWKkxD1kD8iLxCn4P8wr8J+FrZbzfy6nI2coTOX8kTwqlVv4d2jouh5fEOlGGPZKfaBSgjMqqOta3/Rd39Wcn+D/cAM5SyeYA/kFeykM1OlcddF/NK5MitTcvxcTrwmbJtKDmsfYXyeK3att5645NDJuchT9q/oTTjlPJNyTl2pu/JmMhh+GPJGub6ffYia0rmoOJRPJX/E1vtRnYguq7c/w7Zv+AWyhCe8gW3SMNzWmJIEzmU71xgufK4NkfE1sCZ1K0zUPWNHCFwM2V8dSnbl0yElqkrO698mc1edcyteCNrFG4haxXPI3tsT1u2HUS26T5PDgNbl6ypqp0E5ga+33g8t+BxsRHZx2doXdlFtffRKjcykfsGOVpkb+CyUv5r4IeUJJhsPjqSTIhaaRjnvGRtwynl8YxkwnMaH6+pM03VcXbh+60/We9B1gwNJYcI3wwsVLbtSTbrzN2DsX0J+Ga5/3kyqT62YZ+WmB+n8gBa5Vb/YSYz8VvIKtNRwEalfFWyt+7KVcfbznsYSo49/zVZeyJyzP+DtffQCjdyLPMkPp63YjGySg6y9/F9Jf59ypfY0CribMUbH/djqv2cqXzJ13rKX0DWPhxL9h5fiqzlua78ba8gR2osXJ7fSiexxuNiEeD8cv+4clx8kZxA63ZacH4Qcqrt18ihtLWalDXIobS3kMM7HwMWrTrWNmKfuRwjj/Lx5EnTk/1PzqRMZtTXbuTFyz2UZJpsJjuDXAztNLJPyJI9EEd9UrN8+T/UauA+TyZ4J1b99/pE3FUH0Eq3hkTiMrLn7c/JGcp+V07GLT0jG3l1+XWyA9cfyLnUtyjbWqLGpMSyMdmvZBkyUaufxGZ/sjrxJlpg4q5WuVHXnMPHV0kiZ8w7u27bnjTUmJGdg/cmq6cnkf16BrTSMdGB4+IIMkm6vFWPC3LugOPJ2WF3LWUDysl4F/LC5HNVx1k7dsrP5cnanqXIETC7kityrle2T0+p3exLt/J/mZOcoGzJhm2LkzV329c+a90Yx1BKU3n5nM5R7i9H9g+rrQq9BJmILtZKn9vKA2i1W0Mi8UeyOnhpsqpr5VLeMv/AKbyPucvBOV+rxkxWXU8CDi+Pp6nbNi090P7YW25k2+j+5e8ynExov01WQQ8iaxh2/JTXmIa82jyrVU5kHTwuBtVtEy1apU5Otf2d8rn7LHkl+fWybdPaZ7HqWzmGagnEBmRT0elkTc9XyY7ku5NXvutXHW8Xv/f6q/3B5TPxt7rvydrU0Qv3UDyLA9eSU4oPBX5JdoKuTyQmkCNEoCy93ko3D/FsQ/3Y9DKiYUBEbFweVz4ksi+RtC75wfliRLxWJpWqfLKdVqNcLfBl8kp3VnIuiG+RV1OTyCrXGSLi+IpC7FK94bhoY2jyOuRQ04fJk/JCZJX4P8mT9Vei4hEkZb6BQ8janIfJeR9+HTlc8Ctk/H8lO+fuDdwZEaOrircrNcwDsQvZz+oXks4im87WiZygbVeyNmaLiHizG+P5PFnD/auIOK+U7U5etD5KzkvxgqQfkyN7Vo8WXNjMSUQ7GhKJy8k5C35ZcVh9UhlSdgo5tOrlisNpKaqbelrSMLL2YSJ5gn2GrI79IVn1Ois5w+dbfSHR7S3HhaTVI2fKrC2/viPZJ+KnZPX0qsAdEfFEdVFONhnd2cBF5QRVWzDw9MipkncmayPWIeeWqXQCve4gaX8yQdo5ypLdks4nm9BuIheh2z0i7uvGGGYlE7l7o8wTIulEcmTICHKUzGtk7dC25GquLZnM9ZnxvV2tZKS1ROJ2sq3QukFEXCNpWuD6MtFU9IWTYGdJmglYrczauRzwEjk3/pZk2/qfyxfLvmU8+YvdeeXU01r1uJA0d0SML/dnBg6UtGNE7BcRN5d5E04hh9KeGhGXVBgu8NGkc78k10U5t25eitFkjckq5Mi0e8kRPoOij80IW97zELKj6/YR8ajKOiURsbuk9ci1WE6NiMe7OZzXyMm6BpQarG8CT0XE08DTkl4jk89DyVEZLZlAgGsiPpWkweQkN7+vZa3WPSTN1JdOgp0laRpyBspvkSMX1omIJyQtS3b4+pAcjnxzhWF2u1Y6LkoV9INkkvBARJwjaRly3P4Asjd9KNdZGAgcFhGvVBZwUY6lc8g+Gq8p10b5QNJs5PG1FDlh3VLA0RHx5wrD7TKSZgDejbrpxCVdRM7c+pu62uYvkbUC3X6c6eOF8QYAR5G1iM9FxLZt7DtL+X+1bDO6Z6z8FJGr6R3lBKL7tcqJomq1q8TI9Stu5uM1LT4nabqIuIeskZgZWF3SdJUF2wNa7Lh4i+whPx7YXtI5ZCfKy4E3gSslfZUckndcKyQQxYzkKIzVII+tkki8Qna0vYqcjnu3iPhzq8yg2RnKlYrvAQ4rM4fWjCKbmUaU/bYn5+3okdlwG2q5f0j2P3lO0ojaZ7kkGFDWtWnVBAKcRHRIeK0G6yENnb/2JL/oNiarmjci12CA7Fj5F3Jo57s9H2n/FBHPkM2bXyD/H6OAncl5LP5MJhJLklf8T1UVZ6OIeJVszti6NH1BdsiFbCobAVwTEf8t+7fsSWsqvESuMLoAMErS/pJWJdeRCeBgSVeTC4sdHhEvdHdAdRcIkyQNLInEz4BXyJlZVyvJ3aSyX8v/H9ycYdaClIs2bQHsFxH3Kpc935U8Qc1FDvlcNyJerC7K/qWW4JV+GheQs1N+npwp9DqyZmg82Ybdcv8XSUPJmOcgax1uJGdGPBv4dkRcXV10XU/SLOT/6SyyE/IKwIHke/8r8C45ZPjNiHi+m2OpHTsD6zurKlff/LDUPBxH9qP5bit3JG7kJMKsxZRRGL+JiA2Vi5KtTiYNJ5OdrdYgO1VWt+hOP1WuJKclpwv/LFkjcXhE/KUMn3yhhZowPkHS3MB25Jwjd5HLSx8fEVe0crt7syStSc4Wuir5Ofo9ORx6AvBqRBzQAzHUEoh1gZ3Iv/vTEfGXsr2+j8TC0SILyXWUkwizirUx38AQsg/Eo2R/iJfJJo0LIuKYaqK0eiVhuBn4ZUT8qOp4plZJJiaRkyuN7aMJhMjOrUeQtURbAQdExLXKFTlf7u4aiLpY1iFnPz6UHFn1OrBPlLlPGmsoehMP8TSrUEMfiK3JNvUJZI/tPYC/RMT/JN1IdqIc5D461YuIRyQdBixYP5dHb1Ebolr3uE8lEPDRe/pQ0jNkk832EXFt2dbTtXiLks2RMwPzA1tFxPuSPhMRz/XWBAKcRJhVqi6BOJhcbfV8cvGfnSLihLpte5HTWjuBaB23kFe3VqH2ruJrCXpEnC9pBWDRnrrib6NmR8CfyA6UG0dO9LUBsLCks6PFZmOdGh6dYVYBSV8pQ9CQ9BlgrYhYgxx6dh9wu6TpS9PG6mQCcX91EVujiHiYvLrtVbUQfYmkTYDvS5pF0sD6baUfQu0cdzcwD7lWRrcrv3tlSTsoJ427HLgDuK0kEKuRfZwe680JBLhPhFmPKx2szgR2iYh/S5qLnO72SXJBnpER8Y5yfv+/Ay+5BsJscpLWINco+TY56Vpt4qh1gX+W5oJap8Uh5OJVPdUHYq0S2/PkiJ3zy6aRZCfpgcCPI+KqnoinO7kmwqwHSdoMOIFsE60lEK8B48glvHcuCcRu5Gp+A5xAmLVpZXJNo2vrEohpyBmGt4Gcj6H8fL0nhnGWn4PJBb32iIh1yA7SmwAfRsRewGbAZhFxVV+Y1Mt9Isx61qbA/BFxt3LdhauBHwHHk0MHb5A0ClgP2LWnrpzMeqE7gBWVq3DeRY54eJ6c9GtVSW9Qmg96IpjShLEpORpkOnImytuBY4DvAXuUPhnX1z+nJ2LrTm7OMOthki4ml/t9FTgrIs6v2zYSeBF4IiIeqyRAs16gNFGsSNY8PEheFM9JTk2+AjnSaYvooeWzleuq/JjsGD0bOZfIyRFxbtl+DPCnvta3yUmEWQ+p7xlerp62jog5yuPpwtNXm001ST8BbqwN35S0BTmJ1uk99ZmStCBwEjmd9nalH8Y6wE+AcyLijJ6IowpOIsx6UEMicQn5ZbdyREz0HBBmbZvSZFhlqOTh5HTWQc6vskd3zwXRxiRxe5J9MX5FJjVvldhOBDYgV+qc1Par9V7uE2HWg0qyMDAiJkbEdpL+QHa8+qwTCLNPapiQbfb45LoS/wSmB3YDXgD27KkEoozCWIZsQvktuR7HdkBI+kdE/E3SHRHxUnfGUyXXRJh1A0kbAgtGxK/18bK/9dvrayTOIRdteqKKWM16A0mHkMuZ7x8Rr7exfQB8PCKjB+JZl6xlqPVxWpRc0GxbcgTG74G/9sXah3oe4mnWxUpb6E+BcfUJhKQv1fapNV+U+3s5gTBrn6SvAVsC34mI1yXNWIZzfiQiJnXnCVvS3PWfYTJROCUifhwRO5AjMf4UEX8AbgOe6usJBDiJMOsOGwJ/jIi/1CUQswN/lLR+bSc3X5h12DzkDI+flfQN4Brg65Jm7Ym5FkrCvyVwoHJlUIC3gdnrdjsceK1cOJwUEfd2d1ytwH0izLrefcBKkg4FRpOrJY4lqz6HS/oiMLo3L7pj1l0a+kBMExEfAE8D2wNzA+eRTQjLAhN7Yq6FiPhQ0j/Iz/JOksYBFwKjJI2JiCvIvhFLAPNIer4vzAHREe4TYdbFJC1ALt19MLmk9/zAjOQiPEOBD4G1o2ElRbP+riGBOBgYTk7C9hNyqugXI+JNSRuR80Ns2p2TSUmaJSJeq/VhkrQomcA8SM4DMQ9wDvBvYFXgsIj4a3fF04qcRJh1obpe24PIufNPr1VrlrUwpgf+EBFvVRmnWSuTtDs52mIL4DHgtIg4ukwpvTPwTXKNmW6buKn8rgeBMyLixNJx81JyZszbgS+QM82+BMwKzBARD05pOGpf5OYMs05oZ8nfKNWftwPfKjNUzgkcAOzmBMJscpK+QC6QdXMpWgQ4BNiRnN762NLX4D1JzwCbd/eMruV37QRcKeltYAQ5k+whkoaRU1sfA5wdEf+se16/SSDASYRZ0xqqXvcg5+l/sG6XfwJDyFUGXwW+GhGP9HigZq3vS8DWkn4QETeRU1b/pPzcrCTlP5D0akT8oqeCiohbS9PJdcDDEbFTKX9W0pXkRUOfnQOiI9ycYdZJZdGd/YG925qnX9J05AXKez0enFkLK0MmxwDvkx0nNyUXq3ofuIIc8XAjsG65v2NEPFRBnMsC/wC+HRHn1JVPHxHv9HQ8rcQ1EWadIGkZ4OvAP8rVyUeTSNV4TQyzdi0NPAm8GhFnSpoWOI7s87AXcBAwEpgF2KWKBAIgIu4pk0tdLWnGiDi1lPfrBAJcE2E2VdqYL38hYF+yvfTQiPhPZcGZ9UKSFieX714vIp6RdBCwPnnV/5CkGYDBEfFKpYECZXj29cCSwNj+MJnUp3ESYdZBDX0g1iOHnj1OLt29M7AYcH5E3FpdlGatrTY5VEMyfjywOrBDSSQOIGsgDo+If1cTadskDWlr2u3+yjNWmnVQXQKxH7ns71pku+0I4FqybfcgSStVFaNZK5M0axSSvixpC0mzkv0grgIulTR/RJxOLmj1dJXxtuMN+DgZ6u/cJ8Ksg8qXxjBygZ3NI+IxSdeTHb6OIr/03geeqS5Ks9YkaRFgrzLkeXlyCOfj5NDns4AzyHPSdZLWjojfVBbsFNQuJvrbUM72OIkwm4L6Jozyc6ykp4FFJD0TudTvQsC+EbGjpDPKNL1mNrlB5bY98DlgRJkNcg9yvZn7I+I4SZOAaabwOtZC3JxhNgX1U/BKOrIM1xwHrAYsWHZ7E3ijJBxOIMzq1PWBeJicInoS2TFxg1J+HvAu8I3y+PiIeLKKWG3quWOl2acofSB2JeeBeEDSbGSfiIHkrHWfBfbsL6v2mXVUQ2fk6SPiHUnTk+teBHB9RIyStCfZxPGNxiHS1tqcRJh9CklnAb+KiLslzRARb0saAiwELADcGxFPVRulWWtpSCAOAtYmZ3D9FXAzOb/KOuSqt58D9o+I+yoK15rkPhFmddqYB2Iach7/tYG7I+LtsmnpMvTsngrCNGt5dQnEVsBOwC5krd3pwJHkuhNDgHfIoZ1jKwrVOsE1EWZFw5XThsArwHhgNuDH5BwQF5VFeY4kl/N+vrKAzVqQpHWAVSPiR+XxbsBiEXFkebwyObnUGmS/vNciYkJV8VrnuCbCrKhLIL4FbEYuurMecDRwGnBqWYxnGWAbJxBmHysdKAcBpwLzSxocEd8DJgBblMfvRcTtkq4Cpo+IB6qM2TrPNRHWrzXUPgwgq1tPiYhNJJ0ALBIRW5Xts5MdKSdGxPjKgjZrYZI2BrYjR2G8FBHflnQeMD1wPtmP6BvA+hHhOVV6OQ/xtP5uGkmDAMo8+O8Ar0n6EbA42ZaLpK2BaSPiOScQZpOTNHfdw6fIvg6XAyHpRxGxB3A3WbO3MVmT5wSiD3BNhPVbktYnO3vNS05l+2vgJuBEcgGg5SLiDUl7AV8FNomIF6uK16wVlT4QF5JzQJwGPAvsQDYJnkp+dp6JiKPK/v1++ey+xEmE9UslgTiJnLP/GWAb4DPAncD/yKFnXwBuBLYGdoqI+6uJ1qx1SVoGuIWsxTsSWAm4jPz8nE/WSvwQeCwiDm8cAWW9m5MI63ckrQZcAHw1IkbVle9BriT4R3Ic+57AC+Q8EI9WEatZb1CW8/4HOQfENWSCviS5CueZkpYEXnZn5L7HozOsP1qVnN9hfK3HOOT0u5K+AHwtIq4nFwQys08REQ+VkUujyKR7NUkjyAXp8CiMvssdK60/+jnZyWt/YESZUKrmUsBL/JpNpYi4k+w4eZ6kvSLi3xFxR9VxWfdyEmH9iqQBZRTGj8imim2A1esSiWWBVyQNrC0cZGYdExG3k7O7nl2aB62Pc58I63dqiUSZF+IoYC6yLXcl4FvA9hHxYJUxmvVmkpYH3o6IR6qOxbqXkwjr09rrCS5pmoj4oCQS3wdGAPOR49edQJiZdYCTCOuzGmajXJ+cfpeIuKuU1ddI7Af8LSIeqyxgM7NexkmE9XmSvglsAVwPfJkcdnZ72TYwIiZWGJ6ZWa/ljpXWp0laDFg3ItYEZgFeBUZLmg7ACYSZWfOcRFif0saIigHAC5J+AHwe2LGMzlivYb5/MzObSk4irM9o6AMxH0BEPAxMQ66RsW1EvFvWwjgM+LCyYM3M+gD3ibA+R9KBwK7AQ+QCQLMDG5HT8P6TXKbYa2GYmXWSkwjr9eomkELSIsDJwMHAAWRt27XAf8lVBd8E7oyI/1UUrplZn+EkwvoMSSOBwcCyEfEtSYPIVTrnBK4AbnBHSjOzruM+EdYnSNoWOBpYHNhL0h4R8WFEHA28RTZnDK4uQjOzvsereFqvJ2kdYFOyn8Odkq4HTpRERJwXEYdJmjMi3q44VDOzPsU1Edbr1IZx1g3nXApYDFhT0sxlGe9DgGMk7QIQES9WEqyZWR/mPhHWqzQM4/wc8HxEvC5pG7I24hLgxoh4W9JawNMR8XhlAZuZ9WFuzrBepS6B2B/YE3hU0uxkAjEtubT3YEl/i4h/VBaomVk/4OYM6xUkzVZ3f3VgHzJh2A0YA9wMXAzcQ66P0ThzpZmZdTEnEdbyJC0InCDpK6XoFeCWiHgS+CAiDgCeADaNiFOAH0TEW5UEa2bWjziJsN5gIJkkbC1pBPAyufbFJvFxp57ngNkAIuLlasI0M+tf3LHSegVJM5MjLhYDDgeGAVcCPyeTjK2BkZ6J0sys57gmwlqSpLUl7VdXND2wFbmY1veBccBawCRgCDlHhBMIM7Me5JoIa0mSVgJuJZfuvljSv4Dfl9s+wOeA8yLi1grDNDPr15xEWMuStCJwHTAR+HpEXFjKFwZGkmtiHAm8Ez6Qzcx6nOeJsJYVEaMlrQHcBNTmhxgQEY9J+j3whqeyNjOrjpMIa2kRcZ+k9YC/S5o1In5dyp+qODQzs37PSYS1vIi4oyyydYek9yLivKpjMjMz94mwXkTS8sDbEfFI1bGYmZmTCDMzM2uS54kwMzOzpjiJMDMzs6Y4iTAzM7OmOIkwMzOzpjiJMOsFJB0tKSQ92s72MWX70VP5uruX583URXEOkLS3pP9Iel3Su5Lul/SdqfkdkqYt73m5rojLzLqHkwiz3uNdYKEyHfhHyjojC5btU+uvwKpAp2f+lDQAuBg4DbgF2A7YCDgP2B/40VS83LTAD4DlOhuXmXUfTzZl1nu8BdxFrhsyuq58JHADsMLUvmBETAAmdEl0cAC5JPt6EXF9XfkNkk4HRnTR76mUpOkj4p2q4zBrBa6JMOtdLgK2kySA8nO7Uj4ZSatKulLSc5LeknS3pJ0a9pmsOUPS8PJ4O0lnSnpN0lhJx5Sahin5JnB5QwIBQES8GxGjyu+YUdJpkh6R9LakJySdLmlI3VPeKD/PK/GEpOHl+dNJOkHSM5Lek3SPpI0a3tdgSWdIelXSS5J+JukbkqJhv4Uk/aU0vbwh6SpJizTsE5K+JekUSROA+yQdUPafqWHfL5f9l/mUv5VZn+Akwqx3+TMwN7Baebw6MBS4vI19FwT+DewNbApcRp6Ud+jA7zkBeBPYhlx+/ahyv02S5gcWAv7WgdeeARhIrsC6IfB94CvAn+r2+Ur5eSzZ3LIq8HwpuxTYHfgx+b7uAK5s6D9xQtnnGGAnYAHgkIaYBwOjgMWBr5b9FwL+KWn2hpi/A8wL7AIcBPyBrMlt/JvsDtwVEfdO8S9g1ke4OcOsF4mIVyX9jWzCuLn8/Fspb9z3o9qJUmNxEzAfecK88FN+1U0RUTvpXidpA2Ar4JJ29h9Wfj7dgfcwAdivLrZBwBPAvyQtEBFPk4kBwGMRcWvdvmsDGwNrRcQ/S/HfJS1GJiXbSpoD2Ac4KiJOLs+7Fri/IZQ9yORisYh4vOx3G/A48DXg+Lp9x0XE9vVPlnRZeY3zy+OZyOacwz/tb2DWV7gmwqz3uQjYplxJb0MbTRkAkmaTdKqkp4APym0fYLEO/I6/Nzx+kExAPk2H5tGXtIuk/0p6s8T1r7Lp02JbBxgH/FvSoNqNrFGodThdGpgOuPKjoHJ+/6saXmtlstbg8br9xpK1N6s17PvXNmI5B1hd0mfL4+3IC7M/fsp7MOsznESY9T5XAjMBxwEz8smTY835wPbAz4D1gJWAc8kT7Kd5teHx+5/yvGfLzwU+7YUlbQlcQI7g2BZYBdiybP602OYE5uHjpKh2OxqYv+wzT/nZ2GG08fG8wPg2fsd4oLE5o639/kHWWuxeHu8BXBERL08hfrM+xc0ZZr1MRLwl6f/Ijox/ioi3GveRNB1Z7X9gRPy6rrxbLhwi4hlJjwPrA7/5lN23BW6LiP3r4lqzg7/qZTJh2WIK+4wrP4eW/al7XO95YMk2nj93w/OgjRqWiAhJ5wL7SPodWXux4RTiMutzXBNh1judQdZA/Lqd7YPJzovv1QokzQxs1o0xnQJsJenLjRvKiIpaZ8np6+Mqdmp4/H752VgzMYqsaXgzIkY33so+95FzZmxe9/tFdsKsdxuwgqSF6vYbBnyJj5tXPs35ZDPPuWRyc10Hn2fWJ7gmwqwXioh/kNXp7W1/TdIdwFGSXgcmkR3+XgOGtPe8TjodWAO4uswLcR2ZDCwLHEgmPTeU8tMlHUmeyDcC1m6I/31JT5DDWe8nk4J7y3OvJTt7/hR4oLyf5YDpIuKIiHhJ0tnAMZI+AB4imxqGMHmNwvnAYcA1ko4CJpLNIi8CZ3bkDUfEc6Wj68bA8RExsWN/KrO+wUmEWd+1I3AW2f/gJXImyRnIE3qXi4hJkrYH9iSHle5Lfsc8CvyOrKmAPEF/FjiYrGm4rsR6a8NL7gucCFxP1qwsFBFPStoK+C7wDbIPxsvA3cAv6557KDANmRRMKr//nPKcWrzvSVoHOKlsE5mYbTWV/Rr+QiYR503Fc8z6BGWnZTOzvk3S9cA0EdHR/hcdfd1LgHkjYvWufF2z3sA1EWbW55R+GV8kpwmfhhylsjbZqbOrfsfS5LDSrcj5Osz6HScRZtYXvUmO4DiCbDJ5FNg9Ii7twt9xFTnk9Fdd/LpmvYabM8zMzKwpHuJpZmZmTXESYWZmZk1xEmFmZmZNcRJhZmZmTXESYWZmZk1xEmFmZmZN+X9f0wuCk4hzJQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "sns.barplot(x='main_category', y='discounted_price', data=df,\n",
    "              order=df.groupby('main_category').discounted_price.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Main Category', fontsize=15)\n",
    "plt.ylabel('Sales Anount', fontsize=15)\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52e2dfef",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3590069f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e61157a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Women's Clothing                 3901\n",
       "Men's Clothing                   1773\n",
       "Necklaces & Chains               1606\n",
       "Accessories & Spare parts         925\n",
       "Tablet Accessories                801\n",
       "                                 ... \n",
       "Elligator Aviator Sunglasses\"       1\n",
       "sovam Home Furnishing               1\n",
       "Strollers & Activity Gear           1\n",
       "Naaz Toys & School Supplies         1\n",
       "Home Utilities                      1\n",
       "Name: primary_category, Length: 223, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##how many primary categories are there in each main category\n",
    "df.primary_category.value_counts().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e18952da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Women's Clothing', 'Men's Clothing', 'Necklaces & Chains',\n",
       "       'Accessories & Spare parts', 'Tablet Accessories', 'Women's Footwear',\n",
       "       'Bangles, Bracelets & Armlets', 'Rings\"', 'Wrist Watches',\n",
       "       'Kids' Clothing'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.primary_category.value_counts().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "53baa514",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,5))\n",
    "sns.countplot(y='primary_category', data=df,\n",
    "              order=df.primary_category.value_counts().sort_values(ascending=False)[:10].index)\n",
    "plt.ylabel('Primary Category', fontsize=12)\n",
    "plt.xlabel('Shopping Count', fontsize=12);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47d2c38c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ca901e4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "primary_category\n",
       "Rings\"                             17724243.0\n",
       "Living Room                         2491621.0\n",
       "Women's Clothing                    2325067.0\n",
       "Men's Clothing                      1663213.0\n",
       "Wrist Watches                       1352941.0\n",
       "                                      ...    \n",
       "Elligator Aviator Sunglasses\"           219.0\n",
       "Aligatorr Aviator Sunglasses\"           180.0\n",
       "Mikado Aviator Sunglasses\"              179.0\n",
       "Wind Spinner Toys                       129.0\n",
       "Dark Image Wayfarer Sunglasses\"         117.0\n",
       "Name: discounted_price, Length: 223, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which primary category earning more\n",
    "df.groupby('primary_category').discounted_price.sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "36f482b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Rings\"', 'Living Room', 'Women's Clothing', 'Men's Clothing',\n",
       "       'Wrist Watches', 'Accessories & Spare parts', 'Women's Footwear',\n",
       "       'Tablet Accessories', 'Network Components',\n",
       "       'Bangles, Bracelets & Armlets'],\n",
       "      dtype='object', name='primary_category')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('primary_category').discounted_price.sum().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "889a3638",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,8))\n",
    "sns.barplot(x='primary_category', y='discounted_price', data=df,\n",
    "              order=df.groupby('primary_category').discounted_price.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Primary Category', fontsize=12)\n",
    "plt.ylabel('Discounted_price', fontsize=12)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Sales of Primary Category', fontsize=25);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da30c705",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12fb3199",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "79e22435",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Western Wear                                            1981\n",
       "Necklaces\"                                              1567\n",
       "None                                                    1457\n",
       "Lingerie, Sleep & Swimwear                              1208\n",
       "T-Shirts                                                 903\n",
       "                                                        ... \n",
       "Manirathnum Manirathnum Tourquise Original Gemst...\"       1\n",
       "Shoperite Office Supplies\"                                 1\n",
       "Timex Wrist Watches\"                                       1\n",
       "RKDEAL Ride Ons                                            1\n",
       "Shaving Creams, Foams, and Gels                            1\n",
       "Name: secondary_category, Length: 899, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which secondary category sold most\n",
    "df.secondary_category.value_counts().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "9392e615",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Western Wear', 'Necklaces\"', 'None', 'Lingerie, Sleep & Swimwear',\n",
       "       'T-Shirts', 'Cases & Covers', 'Car Interior & Exterior', 'Ethnic Wear',\n",
       "       'Casual Shoes', 'Bangles\"'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.secondary_category.value_counts().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6d897a65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,5))\n",
    "sns.countplot(y='secondary_category', data=df,\n",
    "              order=df.secondary_category.value_counts().sort_values(ascending=False)[:10].index)\n",
    "plt.ylabel('Secondary Category', fontsize=12)\n",
    "plt.xlabel('Shopping Count', fontsize=12);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4092683d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f5e8c211",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "secondary_category\n",
       "None                                18481425.0\n",
       "Sofas & Sectionals\"                  2486122.0\n",
       "Western Wear                         1270978.0\n",
       "Car Interior & Exterior               901118.0\n",
       "Cases & Covers                        791467.0\n",
       "                                       ...    \n",
       "Bento Role Play Toys                     143.0\n",
       "Supports                                 140.0\n",
       "Yijun Wind Spinner Toys\"                 129.0\n",
       "Bento Musical Instruments & Toys         126.0\n",
       "SIM Adapters                              99.0\n",
       "Name: discounted_price, Length: 899, dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##which secondary category has more sell\n",
    "df.groupby('secondary_category').discounted_price.sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "32a26379",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['None', 'Sofas & Sectionals\"', 'Western Wear',\n",
       "       'Car Interior & Exterior', 'Cases & Covers', 'Routers', 'Casual Shoes',\n",
       "       'Necklaces\"', 'Breitling Wrist Watches\"', 'T-Shirts'],\n",
       "      dtype='object', name='secondary_category')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('secondary_category').discounted_price.sum().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "cc3d650a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,8))\n",
    "sns.barplot(x='secondary_category', y='discounted_price', data=df,\n",
    "              order=df.groupby('secondary_category').discounted_price.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Secondary Category', fontsize=12)\n",
    "plt.ylabel('Discounted_price', fontsize=12)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Sales of Secondary Category', fontsize=25);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dbebfa8f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "494fe9b1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "72d1cc9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None                                                    5876\n",
       "Shirts, Tops & Tunics                                   1249\n",
       "Bras                                                    1036\n",
       "Car Interior                                             659\n",
       "Dresses & Skirts                                         620\n",
       "                                                        ... \n",
       "Space Women Heels\"                                         1\n",
       "Ts4U Casual Shoes\"                                         1\n",
       "Lowe Alpine Rucksack Raincover Raincover M Lugga...\"       1\n",
       "Seastar Casual Shoes\"                                      1\n",
       "Fun To See Stickers\"                                       1\n",
       "Name: tertiary_category, Length: 2371, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##which tertiary categories shopping count is more\n",
    "df.tertiary_category.value_counts().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "479477fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['None', 'Shirts, Tops & Tunics', 'Bras', 'Car Interior',\n",
       "       'Dresses & Skirts', 'Combos', 'Plant Containers & Sets',\n",
       "       'TheLostPuppy Cases & Covers\"', 'Leggings & Jeggings',\n",
       "       'Kurtas & Kurtis'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tertiary_category.value_counts().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "cbdce1c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,5))\n",
    "sns.countplot(y='tertiary_category', data=df,\n",
    "              order=df.tertiary_category.value_counts().sort_values(ascending=False)[:10].index)\n",
    "plt.ylabel('Tertiary Category', fontsize=12)\n",
    "plt.xlabel('Shopping Count', fontsize=12);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95f83cbf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "adb79fd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tertiary_category\n",
       "None                           25416619.0\n",
       "Car Interior                     889508.0\n",
       "Shirts, Tops & Tunics            730648.0\n",
       "Dresses & Skirts                 546129.0\n",
       "GAGA Paintings                   370060.0\n",
       "                                  ...    \n",
       "Satzuma USB Gadgets\"                  0.0\n",
       "Eurospa Baby Bath Towels              0.0\n",
       "Big Balaji Bulbs\"                     0.0\n",
       "Rock Polo Backpacks\"                  0.0\n",
       "Pearstone Battery chargers\"           0.0\n",
       "Name: discounted_price, Length: 2371, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##which tertiary category has more sell\n",
    "df.groupby('tertiary_category').discounted_price.sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "3a788ea6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['None', 'Car Interior', 'Shirts, Tops & Tunics', 'Dresses & Skirts',\n",
       "       'GAGA Paintings', 'Bras', 'Plant Containers & Sets', 'Religious Idols',\n",
       "       'DailyObjects Cases & Covers\"', 'Boots\"'],\n",
       "      dtype='object', name='tertiary_category')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('tertiary_category').discounted_price.sum().sort_values(ascending=False)[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "71671a94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "sns.barplot(x='tertiary_category', y='discounted_price', data=df,\n",
    "              order=df.groupby('tertiary_category').discounted_price.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Tertiary Category', fontsize=12)\n",
    "plt.ylabel('Discounted_price', fontsize=12)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Sales of Tertiary Category', fontsize=25);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a8287c7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46cf2cc0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "da43346d",
   "metadata": {},
   "outputs": [],
   "source": [
    "##Adding a discount amount column\n",
    "df.insert(7, 'discount_amount', df['retail_price']-df['discounted_price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c5af6f4a",
   "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>uniq_id</th>\n",
       "      <th>crawl_timestamp</th>\n",
       "      <th>product_url</th>\n",
       "      <th>product_name</th>\n",
       "      <th>pid</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>discounted_price</th>\n",
       "      <th>discount_amount</th>\n",
       "      <th>image</th>\n",
       "      <th>is_FK_Advantage_product</th>\n",
       "      <th>...</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_specifications</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>SRTEH2FF9KEDEFGF</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>SBEEH3QGU7MFYJFY</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>9511.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>SHOEH4GRSUBJGZXE</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>AW</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Footwear</td>\n",
       "      <td>Women's Footwear</td>\n",
       "      <td>Ballerinas</td>\n",
       "      <td>AW Bellies\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>PSOEH3ZYDMSYARJ5</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Pet Supplies</td>\n",
       "      <td>Grooming</td>\n",
       "      <td>Skin &amp; Coat Care</td>\n",
       "      <td>Shampoo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            uniq_id           crawl_timestamp  \\\n",
       "0  c2d766ca982eca8304150849735ffef9 2016-03-25 22:59:23+00:00   \n",
       "1  7f7036a6d550aaa89d34c77bd39a5e48 2016-03-25 22:59:23+00:00   \n",
       "2  f449ec65dcbc041b6ae5e6a32717d01b 2016-03-25 22:59:23+00:00   \n",
       "3  0973b37acd0c664e3de26e97e5571454 2016-03-25 22:59:23+00:00   \n",
       "4  bc940ea42ee6bef5ac7cea3fb5cfbee7 2016-03-25 22:59:23+00:00   \n",
       "\n",
       "                                         product_url  \\\n",
       "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
       "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
       "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
       "\n",
       "                            product_name               pid  retail_price  \\\n",
       "0    Alisha Solid Women's Cycling Shorts  SRTEH2FF9KEDEFGF         999.0   \n",
       "1    FabHomeDecor Fabric Double Sofa Bed  SBEEH3QGU7MFYJFY       32157.0   \n",
       "2                             AW Bellies  SHOEH4GRSUBJGZXE         999.0   \n",
       "3    Alisha Solid Women's Cycling Shorts  SRTEH2F6HUZMQ6SJ         699.0   \n",
       "4  Sicons All Purpose Arnica Dog Shampoo  PSOEH3ZYDMSYARJ5         220.0   \n",
       "\n",
       "   discounted_price  discount_amount  \\\n",
       "0             379.0            620.0   \n",
       "1           22646.0           9511.0   \n",
       "2             499.0            500.0   \n",
       "3             267.0            432.0   \n",
       "4             210.0             10.0   \n",
       "\n",
       "                                               image  is_FK_Advantage_product  \\\n",
       "0  [\"http://img5a.flixcart.com/image/short/u/4/a/...                    False   \n",
       "1  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...                    False   \n",
       "2  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...                    False   \n",
       "3  [\"http://img5a.flixcart.com/image/short/6/2/h/...                    False   \n",
       "4  [\"http://img5a.flixcart.com/image/pet-shampoo/...                    False   \n",
       "\n",
       "   ...       overall_rating         brand  \\\n",
       "0  ...  No rating available        Alisha   \n",
       "1  ...  No rating available  FabHomeDecor   \n",
       "2  ...  No rating available            AW   \n",
       "3  ...  No rating available        Alisha   \n",
       "4  ...  No rating available        Sicons   \n",
       "\n",
       "                              product_specifications        date  year month  \\\n",
       "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016     3   \n",
       "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  2016-03-25  2016     3   \n",
       "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  2016-03-25  2016     3   \n",
       "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016     3   \n",
       "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  2016-03-25  2016     3   \n",
       "\n",
       "   main_category       primary_category          secondary_category  \\\n",
       "0       Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "1      Furniture  Living Room Furniture          Sofa Beds & Futons   \n",
       "2       Footwear       Women's Footwear                  Ballerinas   \n",
       "3       Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "4   Pet Supplies               Grooming            Skin & Coat Care   \n",
       "\n",
       "                                   tertiary_category  \n",
       "0                                             Shorts  \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  \n",
       "2                                        AW Bellies\"  \n",
       "3                                             Shorts  \n",
       "4                                            Shampoo  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "4e87a297",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename({'discounted_price':'selling_price'}, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4d605123",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniq_id</th>\n",
       "      <th>crawl_timestamp</th>\n",
       "      <th>product_url</th>\n",
       "      <th>product_name</th>\n",
       "      <th>pid</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>discount_amount</th>\n",
       "      <th>image</th>\n",
       "      <th>is_FK_Advantage_product</th>\n",
       "      <th>description</th>\n",
       "      <th>product_rating</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_specifications</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>SRTEH2FF9KEDEFGF</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>SBEEH3QGU7MFYJFY</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>9511.0</td>\n",
       "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
       "      <td>False</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>SHOEH4GRSUBJGZXE</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of AW Bellies Sandals Wedges Heel...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>AW</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Footwear</td>\n",
       "      <td>Women's Footwear</td>\n",
       "      <td>Ballerinas</td>\n",
       "      <td>AW Bellies\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
       "      <td>2016-03-25 22:59:23+00:00</td>\n",
       "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>PSOEH3ZYDMSYARJ5</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
       "      <td>False</td>\n",
       "      <td>Specifications of Sicons All Purpose Arnica Do...</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>No rating available</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Pet Supplies</td>\n",
       "      <td>Grooming</td>\n",
       "      <td>Skin &amp; Coat Care</td>\n",
       "      <td>Shampoo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            uniq_id           crawl_timestamp  \\\n",
       "0  c2d766ca982eca8304150849735ffef9 2016-03-25 22:59:23+00:00   \n",
       "1  7f7036a6d550aaa89d34c77bd39a5e48 2016-03-25 22:59:23+00:00   \n",
       "2  f449ec65dcbc041b6ae5e6a32717d01b 2016-03-25 22:59:23+00:00   \n",
       "3  0973b37acd0c664e3de26e97e5571454 2016-03-25 22:59:23+00:00   \n",
       "4  bc940ea42ee6bef5ac7cea3fb5cfbee7 2016-03-25 22:59:23+00:00   \n",
       "\n",
       "                                         product_url  \\\n",
       "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
       "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
       "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
       "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
       "\n",
       "                            product_name               pid  retail_price  \\\n",
       "0    Alisha Solid Women's Cycling Shorts  SRTEH2FF9KEDEFGF         999.0   \n",
       "1    FabHomeDecor Fabric Double Sofa Bed  SBEEH3QGU7MFYJFY       32157.0   \n",
       "2                             AW Bellies  SHOEH4GRSUBJGZXE         999.0   \n",
       "3    Alisha Solid Women's Cycling Shorts  SRTEH2F6HUZMQ6SJ         699.0   \n",
       "4  Sicons All Purpose Arnica Dog Shampoo  PSOEH3ZYDMSYARJ5         220.0   \n",
       "\n",
       "   selling_price  discount_amount  \\\n",
       "0          379.0            620.0   \n",
       "1        22646.0           9511.0   \n",
       "2          499.0            500.0   \n",
       "3          267.0            432.0   \n",
       "4          210.0             10.0   \n",
       "\n",
       "                                               image  is_FK_Advantage_product  \\\n",
       "0  [\"http://img5a.flixcart.com/image/short/u/4/a/...                    False   \n",
       "1  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...                    False   \n",
       "2  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...                    False   \n",
       "3  [\"http://img5a.flixcart.com/image/short/6/2/h/...                    False   \n",
       "4  [\"http://img5a.flixcart.com/image/pet-shampoo/...                    False   \n",
       "\n",
       "                                         description       product_rating  \\\n",
       "0  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  No rating available   \n",
       "2  Key Features of AW Bellies Sandals Wedges Heel...  No rating available   \n",
       "3  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
       "4  Specifications of Sicons All Purpose Arnica Do...  No rating available   \n",
       "\n",
       "        overall_rating         brand  \\\n",
       "0  No rating available        Alisha   \n",
       "1  No rating available  FabHomeDecor   \n",
       "2  No rating available            AW   \n",
       "3  No rating available        Alisha   \n",
       "4  No rating available        Sicons   \n",
       "\n",
       "                              product_specifications        date  year  month  \\\n",
       "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016      3   \n",
       "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  2016-03-25  2016      3   \n",
       "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  2016-03-25  2016      3   \n",
       "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  2016-03-25  2016      3   \n",
       "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  2016-03-25  2016      3   \n",
       "\n",
       "  main_category       primary_category          secondary_category  \\\n",
       "0      Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "1     Furniture  Living Room Furniture          Sofa Beds & Futons   \n",
       "2      Footwear       Women's Footwear                  Ballerinas   \n",
       "3      Clothing       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "4  Pet Supplies               Grooming            Skin & Coat Care   \n",
       "\n",
       "                                   tertiary_category  \n",
       "0                                             Shorts  \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  \n",
       "2                                        AW Bellies\"  \n",
       "3                                             Shorts  \n",
       "4                                            Shampoo  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.max_columns=40\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ba8be7e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "8aac2a8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['uniq_id', 'crawl_timestamp', 'product_url', 'product_name', 'pid',\n",
       "       'retail_price', 'selling_price', 'discount_amount', 'image',\n",
       "       'is_FK_Advantage_product', 'description', 'product_rating',\n",
       "       'overall_rating', 'brand', 'product_specifications', 'date', 'year',\n",
       "       'month', 'main_category', 'primary_category', 'secondary_category',\n",
       "       'tertiary_category'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "18d988d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['uniq_id','crawl_timestamp','product_url','pid','image','is_FK_Advantage_product','description','product_rating','overall_rating','product_specifications'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8fffdd1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        text-align: right;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product_name</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>discount_amount</th>\n",
       "      <th>brand</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>9511.0</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>AW</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Footwear</td>\n",
       "      <td>Women's Footwear</td>\n",
       "      <td>Ballerinas</td>\n",
       "      <td>AW Bellies\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Pet Supplies</td>\n",
       "      <td>Grooming</td>\n",
       "      <td>Skin &amp; Coat Care</td>\n",
       "      <td>Shampoo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            product_name  retail_price  selling_price  \\\n",
       "0    Alisha Solid Women's Cycling Shorts         999.0          379.0   \n",
       "1    FabHomeDecor Fabric Double Sofa Bed       32157.0        22646.0   \n",
       "2                             AW Bellies         999.0          499.0   \n",
       "3    Alisha Solid Women's Cycling Shorts         699.0          267.0   \n",
       "4  Sicons All Purpose Arnica Dog Shampoo         220.0          210.0   \n",
       "\n",
       "   discount_amount         brand        date  year  month main_category  \\\n",
       "0            620.0        Alisha  2016-03-25  2016      3      Clothing   \n",
       "1           9511.0  FabHomeDecor  2016-03-25  2016      3     Furniture   \n",
       "2            500.0            AW  2016-03-25  2016      3      Footwear   \n",
       "3            432.0        Alisha  2016-03-25  2016      3      Clothing   \n",
       "4             10.0        Sicons  2016-03-25  2016      3  Pet Supplies   \n",
       "\n",
       "        primary_category          secondary_category  \\\n",
       "0       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "1  Living Room Furniture          Sofa Beds & Futons   \n",
       "2       Women's Footwear                  Ballerinas   \n",
       "3       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "4               Grooming            Skin & Coat Care   \n",
       "\n",
       "                                   tertiary_category  \n",
       "0                                             Shorts  \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  \n",
       "2                                        AW Bellies\"  \n",
       "3                                             Shorts  \n",
       "4                                            Shampoo  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea3c123f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "09077c0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "main_category\n",
       "Watches                       571230.0\n",
       "Furniture                     250500.0\n",
       "Mobiles & Accessories         116292.0\n",
       "Pens & Stationery              71687.0\n",
       "Clothing                       69999.0\n",
       "Jewellery                      49999.0\n",
       "Home Decor & Festive Needs     47620.0\n",
       "Automotive                     44880.0\n",
       "Computers                      38890.0\n",
       "Kitchen & Dining               34168.0\n",
       "Name: retail_price, dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which main category has highest retail price\n",
    "df.groupby('main_category').retail_price.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "1f87d8df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "main_category\n",
       "Furniture                     87675.0\n",
       "Pens & Stationery             26883.0\n",
       "Jewellery                     25419.0\n",
       "Automotive                    22440.0\n",
       "Clothing                      21000.0\n",
       "Home Decor & Festive Needs    20990.0\n",
       "Beauty and Personal Care      19425.0\n",
       "Computers                     11610.0\n",
       "Bags, Wallets & Belts         10109.0\n",
       "Footwear                       9998.0\n",
       "Name: discount_amount, dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which category has given maximum discount\n",
    "df.groupby('main_category').discount_amount.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "53310932",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "primary_category\n",
       "Wrist Watches                   571230.0\n",
       "Living Room                     250500.0\n",
       "Mobile Accessories              116292.0\n",
       "Office Equipments                71687.0\n",
       "Men's Clothing                   69999.0\n",
       "Bangles, Bracelets & Armlets     49999.0\n",
       "Rings\"                           49999.0\n",
       "Table Decor & Handicrafts        47620.0\n",
       "Wall Decor & Clocks              46500.0\n",
       "Bedroom Furniture                45864.0\n",
       "Name: retail_price, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which primary category has maximum retail price\n",
    "df.groupby('primary_category').retail_price.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "8178ca32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "primary_category\n",
       "Living Room                     87675.0\n",
       "Office Equipments               26883.0\n",
       "Bangles, Bracelets & Armlets    25419.0\n",
       "Accessories & Spare parts       22440.0\n",
       "Men's Clothing                  21000.0\n",
       "Wall Decor & Clocks             20990.0\n",
       "Makeup                          19425.0\n",
       "Rings\"                          17779.0\n",
       "Bedroom Furniture               15000.0\n",
       "Women's Clothing                14997.0\n",
       "Name: discount_amount, dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which primary category gave maximum discount\n",
    "df.groupby('primary_category').discount_amount.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "fe6e9eaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "secondary_category\n",
       "Breitling Wrist Watches\"    571230.0\n",
       "Sofas & Sectionals\"         250500.0\n",
       "Cartier Wrist Watches\"      201000.0\n",
       "Headphones                  116292.0\n",
       "TAG Heuer Wrist Watches\"    107750.0\n",
       "Biometric Devices            71687.0\n",
       "Winter & Seasonal Wear       69999.0\n",
       "None                         49999.0\n",
       "Bracelets\"                   49999.0\n",
       "Showpieces                   47620.0\n",
       "Name: retail_price, dtype: float64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which secondary category has maximum retail price\n",
    "df.groupby('secondary_category').retail_price.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "cc8915ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "secondary_category\n",
       "Sofas & Sectionals\"       87675.0\n",
       "Biometric Devices         26883.0\n",
       "Bracelets\"                25419.0\n",
       "Car & Bike Care           22440.0\n",
       "Winter & Seasonal Wear    21000.0\n",
       "Paintings                 20990.0\n",
       "Vanity Boxes              19425.0\n",
       "None                      17779.0\n",
       "Beds                      15000.0\n",
       "Ethnic Wear               14997.0\n",
       "Name: discount_amount, dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which secondary category gave maximum discount\n",
    "df.groupby('secondary_category').discount_amount.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "eba686d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tertiary_category\n",
       "None                                                    571230.0\n",
       "Audeze Headphones                                       116292.0\n",
       "NITGEN Biometric Devices                                 71687.0\n",
       "Jackets                                                  69999.0\n",
       "Religious Idols                                          47620.0\n",
       "GAGA Paintings                                           46500.0\n",
       "Springwel Single Spring Mattress (1981.199999999...\"     45864.0\n",
       "Car & Bike Covers                                        44880.0\n",
       "Ethnic Handicrafts Solid Wood Queen Bed (Finish ...\"     39999.0\n",
       "Lehenga Cholis                                           39992.0\n",
       "Name: retail_price, dtype: float64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which tertiary category has maximum retail price\n",
    "df.groupby('tertiary_category').retail_price.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9b3b57ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tertiary_category\n",
       "None                                                    87675.0\n",
       "NITGEN Biometric Devices                                26883.0\n",
       "Car & Bike Covers                                       22440.0\n",
       "Jackets                                                 21000.0\n",
       "GAGA Paintings                                          20990.0\n",
       "Soulful Threads Vanity Boxes                            19425.0\n",
       "Ethnic Handicrafts Solid Wood Queen Bed (Finish ...\"    15000.0\n",
       "Lehenga Cholis                                          14997.0\n",
       "Ethnic Handicrafts Solid Wood Single Bed (Finish...\"    12000.0\n",
       "Fabric                                                  11955.0\n",
       "Name: discount_amount, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which tertiary category gave maximum discount\n",
    "df.groupby('tertiary_category').discount_amount.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d8635ac",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e8243033",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "8d70228b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "brand\n",
       "Karatcraft         5632898.0\n",
       "Radiant Bay        3601945.0\n",
       "BlueStone          2796709.0\n",
       "Durian             1480125.0\n",
       "ARRA                973097.0\n",
       "Rakam               774110.0\n",
       "Jewels5             713743.0\n",
       "Fullcutdiamond      675287.0\n",
       "Allure Auto         663819.0\n",
       "Shashvat Jewels     544387.0\n",
       "Name: selling_price, dtype: float64"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which brand has more sells \n",
    "df.groupby('brand').selling_price.sum().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "a248c07f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(y='brand', x='selling_price', data=df,\n",
    "            order=df.groupby('brand').selling_price.sum().sort_values(ascending=False)[:10].index);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a56d975",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "62b1c466",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "product_name\n",
       "Breitling AB011010/BB08 131S Chronomat 44 Analog Watch  - For Boys, Men     571230.0\n",
       "Cartier W6701005 Analog Watch  - For Boys, Men                              201000.0\n",
       "Durian Leather 2 Seater Sofa                                                162825.0\n",
       "Durian Laze/3 Leather 3 Seater Sofa                                         141375.0\n",
       "Audeze Lcd2 In Bamboo, High Quality Planar Magnetic Headphone Headphones    116292.0\n",
       "TAG Heuer CAU1116.BA0858 Formula 1 Analog Watch  - For Boys, Men            107750.0\n",
       "Durian Club/3 Leather 3 Seater Sofa                                         105300.0\n",
       "ARRA Solid Wood 7 Seater Sofa                                                86500.0\n",
       "Durian Helena Fabric 3 Seater Sofa                                           70785.0\n",
       "Durian Dream/2 Leather 2 Seater Sofa                                         70200.0\n",
       "Name: selling_price, dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which product has maximum selling price\n",
    "df.groupby('product_name').selling_price.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "8ba03088",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(y='product_name', x='selling_price', data=df,\n",
    "            order=df.groupby('product_name').selling_price.max().sort_values(ascending=False)[:10].index);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b03c21a5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "314b724b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "product_name\n",
       "Geol Wooden Wet and Dry Broom                           35.0\n",
       "Havells Havells - Oro 32 One Way Electrical Switch      36.0\n",
       "Smartcraft Generic Netted Art Cloth Pencil Box          41.0\n",
       "Sam Rolling Pizza Cutter                                45.0\n",
       "Khanna Jupiter Board & Art Paper Box File               47.0\n",
       "Smartcraft Angry Birds Cartoons Art Metal Pencil Box    48.0\n",
       "Smartcraft Generic Pendant Art Cloth Pencil Box         48.0\n",
       "Maped Twist and Flex Transparent Rubber Rulers          49.0\n",
       "Dhiyaa Traders Manchester united Key Chain              54.0\n",
       "Dhiyaa Traders Mario Key Chain                          54.0\n",
       "Name: selling_price, dtype: float64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which product has min selling price\n",
    "df.groupby('product_name').selling_price.min().sort_values()[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "b8c46339",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(y='product_name', x='selling_price', data=df,\n",
    "            order=df.groupby('product_name').selling_price.min().sort_values()[:10].index);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12e0f8b7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0ed14b7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "b7ece83d",
   "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>product_name</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>discount_amount</th>\n",
       "      <th>brand</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>9511.0</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          product_name  retail_price  selling_price  \\\n",
       "0  Alisha Solid Women's Cycling Shorts         999.0          379.0   \n",
       "1  FabHomeDecor Fabric Double Sofa Bed       32157.0        22646.0   \n",
       "\n",
       "   discount_amount         brand        date  year  month main_category  \\\n",
       "0            620.0        Alisha  2016-03-25  2016      3      Clothing   \n",
       "1           9511.0  FabHomeDecor  2016-03-25  2016      3     Furniture   \n",
       "\n",
       "        primary_category          secondary_category  \\\n",
       "0       Women's Clothing  Lingerie, Sleep & Swimwear   \n",
       "1  Living Room Furniture          Sofa Beds & Futons   \n",
       "\n",
       "                                   tertiary_category  \n",
       "0                                             Shorts  \n",
       "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "3e12a9db",
   "metadata": {},
   "outputs": [],
   "source": [
    "## adding discount percentage column\n",
    "df.insert(4, 'discount_percentage', (df['discount_amount']/df['retail_price'])*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "f6cebe44",
   "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>product_name</th>\n",
       "      <th>retail_price</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>discount_amount</th>\n",
       "      <th>discount_percentage</th>\n",
       "      <th>brand</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>main_category</th>\n",
       "      <th>primary_category</th>\n",
       "      <th>secondary_category</th>\n",
       "      <th>tertiary_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>999.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>62.062062</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
       "      <td>32157.0</td>\n",
       "      <td>22646.0</td>\n",
       "      <td>9511.0</td>\n",
       "      <td>29.576764</td>\n",
       "      <td>FabHomeDecor</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Living Room Furniture</td>\n",
       "      <td>Sofa Beds &amp; Futons</td>\n",
       "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AW Bellies</td>\n",
       "      <td>999.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>50.050050</td>\n",
       "      <td>AW</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Footwear</td>\n",
       "      <td>Women's Footwear</td>\n",
       "      <td>Ballerinas</td>\n",
       "      <td>AW Bellies\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
       "      <td>699.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>61.802575</td>\n",
       "      <td>Alisha</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Women's Clothing</td>\n",
       "      <td>Lingerie, Sleep &amp; Swimwear</td>\n",
       "      <td>Shorts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
       "      <td>220.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.545455</td>\n",
       "      <td>Sicons</td>\n",
       "      <td>2016-03-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>Pet Supplies</td>\n",
       "      <td>Grooming</td>\n",
       "      <td>Skin &amp; Coat Care</td>\n",
       "      <td>Shampoo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19995</th>\n",
       "      <td>WallDesign Small Vinyl Sticker</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>730.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>51.333333</td>\n",
       "      <td>WallDesign</td>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>2015</td>\n",
       "      <td>12</td>\n",
       "      <td>Baby Care</td>\n",
       "      <td>Baby &amp; Kids Gifts</td>\n",
       "      <td>Stickers</td>\n",
       "      <td>WallDesign Stickers\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19996</th>\n",
       "      <td>Wallmantra Large Vinyl Stickers Sticker</td>\n",
       "      <td>1429.0</td>\n",
       "      <td>1143.0</td>\n",
       "      <td>286.0</td>\n",
       "      <td>20.013996</td>\n",
       "      <td>Wallmantra</td>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>2015</td>\n",
       "      <td>12</td>\n",
       "      <td>Baby Care</td>\n",
       "      <td>Baby &amp; Kids Gifts</td>\n",
       "      <td>Stickers</td>\n",
       "      <td>Wallmantra Stickers\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19997</th>\n",
       "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
       "      <td>1299.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>23.094688</td>\n",
       "      <td>Elite Collection</td>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>2015</td>\n",
       "      <td>12</td>\n",
       "      <td>Baby Care</td>\n",
       "      <td>Baby &amp; Kids Gifts</td>\n",
       "      <td>Stickers</td>\n",
       "      <td>Elite Collection Stickers\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19998</th>\n",
       "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
       "      <td>1499.0</td>\n",
       "      <td>1199.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>20.013342</td>\n",
       "      <td>Elite Collection</td>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>2015</td>\n",
       "      <td>12</td>\n",
       "      <td>Baby Care</td>\n",
       "      <td>Baby &amp; Kids Gifts</td>\n",
       "      <td>Stickers</td>\n",
       "      <td>Elite Collection Stickers\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19999</th>\n",
       "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
       "      <td>1499.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>33.355570</td>\n",
       "      <td>Elite Collection</td>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>2015</td>\n",
       "      <td>12</td>\n",
       "      <td>Baby Care</td>\n",
       "      <td>Baby &amp; Kids Gifts</td>\n",
       "      <td>Stickers</td>\n",
       "      <td>Elite Collection Stickers\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20000 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  product_name  retail_price  selling_price  \\\n",
       "0          Alisha Solid Women's Cycling Shorts         999.0          379.0   \n",
       "1          FabHomeDecor Fabric Double Sofa Bed       32157.0        22646.0   \n",
       "2                                   AW Bellies         999.0          499.0   \n",
       "3          Alisha Solid Women's Cycling Shorts         699.0          267.0   \n",
       "4        Sicons All Purpose Arnica Dog Shampoo         220.0          210.0   \n",
       "...                                        ...           ...            ...   \n",
       "19995           WallDesign Small Vinyl Sticker        1500.0          730.0   \n",
       "19996  Wallmantra Large Vinyl Stickers Sticker        1429.0         1143.0   \n",
       "19997  Elite Collection Medium Acrylic Sticker        1299.0          999.0   \n",
       "19998  Elite Collection Medium Acrylic Sticker        1499.0         1199.0   \n",
       "19999  Elite Collection Medium Acrylic Sticker        1499.0          999.0   \n",
       "\n",
       "       discount_amount  discount_percentage             brand        date  \\\n",
       "0                620.0            62.062062            Alisha  2016-03-25   \n",
       "1               9511.0            29.576764      FabHomeDecor  2016-03-25   \n",
       "2                500.0            50.050050                AW  2016-03-25   \n",
       "3                432.0            61.802575            Alisha  2016-03-25   \n",
       "4                 10.0             4.545455            Sicons  2016-03-25   \n",
       "...                ...                  ...               ...         ...   \n",
       "19995            770.0            51.333333        WallDesign  2015-12-01   \n",
       "19996            286.0            20.013996        Wallmantra  2015-12-01   \n",
       "19997            300.0            23.094688  Elite Collection  2015-12-01   \n",
       "19998            300.0            20.013342  Elite Collection  2015-12-01   \n",
       "19999            500.0            33.355570  Elite Collection  2015-12-01   \n",
       "\n",
       "       year  month main_category       primary_category  \\\n",
       "0      2016      3      Clothing       Women's Clothing   \n",
       "1      2016      3     Furniture  Living Room Furniture   \n",
       "2      2016      3      Footwear       Women's Footwear   \n",
       "3      2016      3      Clothing       Women's Clothing   \n",
       "4      2016      3  Pet Supplies               Grooming   \n",
       "...     ...    ...           ...                    ...   \n",
       "19995  2015     12     Baby Care      Baby & Kids Gifts   \n",
       "19996  2015     12     Baby Care      Baby & Kids Gifts   \n",
       "19997  2015     12     Baby Care      Baby & Kids Gifts   \n",
       "19998  2015     12     Baby Care      Baby & Kids Gifts   \n",
       "19999  2015     12     Baby Care      Baby & Kids Gifts   \n",
       "\n",
       "               secondary_category  \\\n",
       "0      Lingerie, Sleep & Swimwear   \n",
       "1              Sofa Beds & Futons   \n",
       "2                      Ballerinas   \n",
       "3      Lingerie, Sleep & Swimwear   \n",
       "4                Skin & Coat Care   \n",
       "...                           ...   \n",
       "19995                    Stickers   \n",
       "19996                    Stickers   \n",
       "19997                    Stickers   \n",
       "19998                    Stickers   \n",
       "19999                    Stickers   \n",
       "\n",
       "                                       tertiary_category  \n",
       "0                                                 Shorts  \n",
       "1      FabHomeDecor Fabric Double Sofa Bed (Finish Co...  \n",
       "2                                            AW Bellies\"  \n",
       "3                                                 Shorts  \n",
       "4                                                Shampoo  \n",
       "...                                                  ...  \n",
       "19995                               WallDesign Stickers\"  \n",
       "19996                               Wallmantra Stickers\"  \n",
       "19997                         Elite Collection Stickers\"  \n",
       "19998                         Elite Collection Stickers\"  \n",
       "19999                         Elite Collection Stickers\"  \n",
       "\n",
       "[20000 rows x 13 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42f496c8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa9fa3a6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "6dd418c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "product_name\n",
       "Rajcrafts Floral Double Quilts & Comforters White                 96.533333\n",
       "FashBlush Forever New Orange Bead & Chain Alloy Necklace          95.273818\n",
       "FashBlush Forever Beautiful White Bead Alloy Necklace             94.598457\n",
       "Bling Book Case for iPad 2 / 3                                    94.548458\n",
       "FashBlush Forever New BlackBead & LongChain Alloy Necklace        94.418884\n",
       "Fashblush Alloy Choker                                            93.576350\n",
       "FashBlush Forever New BlackBead Alloy Necklace                    93.364455\n",
       "Fash Blush Forever New Gold & White Pearl Chunk Alloy Necklace    93.364455\n",
       "Mydress Mystyle Bulb Led USB Led Light                            92.492492\n",
       "Fash Blush Forever New Red & Gold Tribal Thread Alloy Necklace    92.076831\n",
       "Name: discount_percentage, dtype: float64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which product giving maximumm discount\n",
    "df.groupby('product_name').discount_percentage.max().sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "f2d1c39b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='discount_percentage', y='product_name', data=df,\n",
    "            order=df.groupby('product_name').discount_percentage.max().sort_values(ascending=False)[:10].index);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "784e8f69",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "681b07db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "product_name\n",
       "Jazma E11A835LA Casual Analog Watch  - For Men                        0.0\n",
       "Maxima 20141CMGI Attivo Analog Watch  - For Men                       0.0\n",
       "Riva Carpets Cotton Free Bath Mat Classic Loop Shag Bathmat_RI-527    0.0\n",
       "Riva Carpets Cotton Free Bath Mat Classic Shag Bathmat-RI-04          0.0\n",
       "Maxima 20020LMGI Attivo Analog Watch  - For Men                       0.0\n",
       "Bajaj Majesty Grill Ultra Open Grill                                  0.0\n",
       "Maxima 19883BMLI Swarovski Analog Watch  - For Women                  0.0\n",
       "Fab Nisa Self Design Women's Straight Kurta                           0.0\n",
       "Fab Nisa Solid Women's Straight Kurta                                 0.0\n",
       "Baggit Pouch Potli                                                    0.0\n",
       "Name: discount_percentage, dtype: float64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## which product giving minimum dicount percentage\n",
    "df.groupby('product_name').discount_percentage.min().sort_values(ascending=True)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e97c1dc4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}