Untitled2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sqlite3\n",
    "\n",
    "con = sqlite3.connect(\"shop/test.db\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "addproduct=pd.read_sql_query(\"SELECT * from addproduct\", con)\n",
    "specsvalues=pd.read_sql_query(\"SELECT * from specsvalues\", con)\n",
    "category=pd.read_sql_query(\"SELECT * from category\", con)\n",
    "subcategories=pd.read_sql_query(\"SELECT * from subcategories\", con)\n",
    "specs=pd.read_sql_query(\"SELECT * from specs\", con)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>price</th>\n",
       "      <th>discount</th>\n",
       "      <th>stock</th>\n",
       "      <th>colors</th>\n",
       "      <th>desc</th>\n",
       "      <th>pub_date</th>\n",
       "      <th>category_id</th>\n",
       "      <th>subcategory_id</th>\n",
       "      <th>brand_id</th>\n",
       "      <th>image_1</th>\n",
       "      <th>image_2</th>\n",
       "      <th>image_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Allen Solly Men's Plain Slim Fit Casual Shirt</td>\n",
       "      <td>699</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Purple, Black</td>\n",
       "      <td>Allen solly Mens Cotton Full sleeve Overdyed s...</td>\n",
       "      <td>2020-07-08 15:54:29.990947</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
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       "      <td>d2bfc40b87bceda78823.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Park Avenue Men's Solid Slim Fit Formal Shirt</td>\n",
       "      <td>563</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>White, Blue, Khaki</td>\n",
       "      <td>This classic shirt from Park Avenue is a versa...</td>\n",
       "      <td>2020-07-08 15:57:00.755305</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>52e5a9ab0ec7bb30a1d8.jpg</td>\n",
       "      <td>6bc2786d351652afcfaf.jpg</td>\n",
       "      <td>b0fe79b775b77d9f15fb.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Park Avenue Men's Plain Slim Fit Formal Shirt</td>\n",
       "      <td>654</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>White, Blue, Black</td>\n",
       "      <td>Be noticed at work by enhancing your looks wit...</td>\n",
       "      <td>2020-07-08 15:58:57.811980</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>53a09ec68d5f5ab9627c.jpg</td>\n",
       "      <td>896324c13cde4988b3be.jpg</td>\n",
       "      <td>4537b9a61d8f4013fe9c.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Wrangler Men's Relaxed Fit Jeans</td>\n",
       "      <td>1198</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Wrangler is the everyday performance denim bra...</td>\n",
       "      <td>2020-07-08 16:02:12.713819</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>5a0acb1668f251563de0.jpg</td>\n",
       "      <td>7c21749eb23b984a2409.jpg</td>\n",
       "      <td>45c87ee10d8d3db36728.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Casio G-Shock Analog-Digital Blue Dial Men's W...</td>\n",
       "      <td>6396</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Mineral Glass Magnetic Resistant Shock Resista...</td>\n",
       "      <td>2020-07-08 16:05:11.097813</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>68618c07e20b3374a091.jpg</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                                               name  price  discount  \\\n",
       "0   1      Allen Solly Men's Plain Slim Fit Casual Shirt    699         0   \n",
       "1   2      Park Avenue Men's Solid Slim Fit Formal Shirt    563         0   \n",
       "2   3      Park Avenue Men's Plain Slim Fit Formal Shirt    654         0   \n",
       "3   4                   Wrangler Men's Relaxed Fit Jeans   1198         5   \n",
       "4   5  Casio G-Shock Analog-Digital Blue Dial Men's W...   6396         0   \n",
       "\n",
       "   stock               colors  \\\n",
       "0     25  Blue, Purple, Black   \n",
       "1     15   White, Blue, Khaki   \n",
       "2     15   White, Blue, Black   \n",
       "3     25          Blue, Black   \n",
       "4     25          Blue, Black   \n",
       "\n",
       "                                                desc  \\\n",
       "0  Allen solly Mens Cotton Full sleeve Overdyed s...   \n",
       "1  This classic shirt from Park Avenue is a versa...   \n",
       "2  Be noticed at work by enhancing your looks wit...   \n",
       "3  Wrangler is the everyday performance denim bra...   \n",
       "4  Mineral Glass Magnetic Resistant Shock Resista...   \n",
       "\n",
       "                     pub_date  category_id  subcategory_id  brand_id  \\\n",
       "0  2020-07-08 15:54:29.990947            1               2         8   \n",
       "1  2020-07-08 15:57:00.755305            1               2        11   \n",
       "2  2020-07-08 15:58:57.811980            1               2        11   \n",
       "3  2020-07-08 16:02:12.713819            1               3        12   \n",
       "4  2020-07-08 16:05:11.097813            1               4        13   \n",
       "\n",
       "                    image_1                   image_2  \\\n",
       "0  58a16e6bee54bb2cddbf.jpg  a983bf257c13c61f6600.jpg   \n",
       "1  52e5a9ab0ec7bb30a1d8.jpg  6bc2786d351652afcfaf.jpg   \n",
       "2  53a09ec68d5f5ab9627c.jpg  896324c13cde4988b3be.jpg   \n",
       "3  5a0acb1668f251563de0.jpg  7c21749eb23b984a2409.jpg   \n",
       "4  68618c07e20b3374a091.jpg  703665b9363046d63afa.jpg   \n",
       "\n",
       "                    image_3  \n",
       "0  d2bfc40b87bceda78823.jpg  \n",
       "1  b0fe79b775b77d9f15fb.jpg  \n",
       "2  4537b9a61d8f4013fe9c.jpg  \n",
       "3  45c87ee10d8d3db36728.jpg  \n",
       "4  e19c74bdbb6bbc914094.jpg  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addproduct.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>price</th>\n",
       "      <th>desc</th>\n",
       "      <th>category_id</th>\n",
       "      <th>subcategory_id</th>\n",
       "      <th>brand_id</th>\n",
       "      <th>spec_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Allen Solly Men's Plain Slim Fit Casual Shirt</td>\n",
       "      <td>699</td>\n",
       "      <td>Allen solly Mens Cotton Full sleeve Overdyed s...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Allen Solly Men's Plain Slim Fit Casual Shirt</td>\n",
       "      <td>699</td>\n",
       "      <td>Allen solly Mens Cotton Full sleeve Overdyed s...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Park Avenue Men's Solid Slim Fit Formal Shirt</td>\n",
       "      <td>563</td>\n",
       "      <td>This classic shirt from Park Avenue is a versa...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>Park Avenue Men's Solid Slim Fit Formal Shirt</td>\n",
       "      <td>563</td>\n",
       "      <td>This classic shirt from Park Avenue is a versa...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>Park Avenue Men's Solid Slim Fit Formal Shirt</td>\n",
       "      <td>563</td>\n",
       "      <td>This classic shirt from Park Avenue is a versa...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>191</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>192</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>193</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>194</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>195</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>196 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     id                                           name  price  \\\n",
       "0     1  Allen Solly Men's Plain Slim Fit Casual Shirt    699   \n",
       "1     1  Allen Solly Men's Plain Slim Fit Casual Shirt    699   \n",
       "2     2  Park Avenue Men's Solid Slim Fit Formal Shirt    563   \n",
       "3     2  Park Avenue Men's Solid Slim Fit Formal Shirt    563   \n",
       "4     2  Park Avenue Men's Solid Slim Fit Formal Shirt    563   \n",
       "..   ..                                            ...    ...   \n",
       "191  33           Men Brown Printed Round Neck T-shirt    350   \n",
       "192  33           Men Brown Printed Round Neck T-shirt    350   \n",
       "193  33           Men Brown Printed Round Neck T-shirt    350   \n",
       "194  33           Men Brown Printed Round Neck T-shirt    350   \n",
       "195  33           Men Brown Printed Round Neck T-shirt    350   \n",
       "\n",
       "                                                  desc  category_id  \\\n",
       "0    Allen solly Mens Cotton Full sleeve Overdyed s...            1   \n",
       "1    Allen solly Mens Cotton Full sleeve Overdyed s...            1   \n",
       "2    This classic shirt from Park Avenue is a versa...            1   \n",
       "3    This classic shirt from Park Avenue is a versa...            1   \n",
       "4    This classic shirt from Park Avenue is a versa...            1   \n",
       "..                                                 ...          ...   \n",
       "191  Brown printed T-shirt, has a round neck, short...            1   \n",
       "192  Brown printed T-shirt, has a round neck, short...            1   \n",
       "193  Brown printed T-shirt, has a round neck, short...            1   \n",
       "194  Brown printed T-shirt, has a round neck, short...            1   \n",
       "195  Brown printed T-shirt, has a round neck, short...            1   \n",
       "\n",
       "     subcategory_id  brand_id  spec_id  \n",
       "0                 2         8        1  \n",
       "1                 2         8        2  \n",
       "2                 2        11        2  \n",
       "3                 2        11        3  \n",
       "4                 2        11        4  \n",
       "..              ...       ...      ...  \n",
       "191              24        17        3  \n",
       "192              24        17       12  \n",
       "193              24        17       15  \n",
       "194              24        17       16  \n",
       "195              24        17       17  \n",
       "\n",
       "[196 rows x 8 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product=pd.read_sql_query(\"SELECT addproduct.id,name,addproduct.price,addproduct.desc,addproduct.category_id,addproduct.subcategory_id,addproduct.brand_id,specsvalues.spec_id FROM addproduct INNER JOIN specsvalues ON addproduct.id=specsvalues.product_id\",con)\n",
    "product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "1                                  [1, 2]\n",
       "2                 [2, 3, 4, 5, 6, 10, 19]\n",
       "3                    [2, 3, 5, 6, 10, 20]\n",
       "4                [21, 22, 23, 24, 25, 26]\n",
       "5                [27, 28, 29, 30, 31, 32]\n",
       "6                [27, 28, 29, 30, 31, 32]\n",
       "7                    [33, 34, 35, 36, 37]\n",
       "8                [38, 39, 40, 41, 42, 43]\n",
       "9                    [43, 44, 46, 47, 48]\n",
       "10                  [1, 3, 5, 12, 17, 50]\n",
       "11                   [51, 52, 53, 54, 55]\n",
       "12                   [51, 52, 53, 54, 55]\n",
       "13       [56, 57, 58, 59, 60, 61, 62, 63]\n",
       "14               [64, 65, 66, 67, 68, 69]\n",
       "15           [70, 71, 72, 73, 74, 75, 76]\n",
       "16               [71, 72, 73, 74, 75, 76]\n",
       "17       [77, 78, 79, 80, 81, 82, 83, 84]\n",
       "18           [85, 86, 87, 88, 89, 90, 91]\n",
       "19           [85, 86, 87, 88, 89, 90, 91]\n",
       "20           [91, 92, 93, 94, 95, 96, 97]\n",
       "21               [92, 93, 94, 95, 96, 97]\n",
       "22           [98, 99, 100, 101, 102, 103]\n",
       "23           [98, 99, 100, 101, 102, 103]\n",
       "24               [92, 93, 94, 95, 96, 97]\n",
       "25    [104, 105, 106, 107, 108, 109, 110]\n",
       "26         [104, 106, 107, 108, 109, 110]\n",
       "27         [104, 106, 107, 108, 109, 110]\n",
       "28         [104, 106, 107, 108, 109, 110]\n",
       "29                   [111, 112, 113, 114]\n",
       "30                   [111, 112, 113, 114]\n",
       "31                   [1, 2, 3, 8, 12, 13]\n",
       "32                   [1, 2, 3, 8, 11, 14]\n",
       "33                 [1, 3, 12, 15, 16, 17]\n",
       "Name: spec_id, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product.groupby('id')['spec_id'].apply(list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category=con.execute(\"SELECT category_id from addproduct WHERE id=\"+str(product_id)+\" LIMIT 1\").fetchone()[0]\n",
    "category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "ename": "DatabaseError",
     "evalue": "Execution failed on sql 'SELECT * from addproduct WHERE category_id= SELECT category_id from addproduct where product_id=2': near \"SELECT\": syntax error",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1594\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1595\u001b[1;33m                 \u001b[0mcur\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1596\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mcur\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mOperationalError\u001b[0m: near \"SELECT\": syntax error",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mDatabaseError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-13-2a2117345336>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mproduct_id\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_sql_query\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"SELECT * from addproduct WHERE category_id= SELECT category_id from addproduct where product_id=\"\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mproduct_id\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcon\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mread_sql_query\u001b[1;34m(sql, con, index_col, coerce_float, params, parse_dates, chunksize)\u001b[0m\n\u001b[0;32m    330\u001b[0m         \u001b[0mcoerce_float\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcoerce_float\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    331\u001b[0m         \u001b[0mparse_dates\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparse_dates\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 332\u001b[1;33m         \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mchunksize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    333\u001b[0m     )\n\u001b[0;32m    334\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mread_query\u001b[1;34m(self, sql, index_col, coerce_float, params, parse_dates, chunksize)\u001b[0m\n\u001b[0;32m   1643\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1644\u001b[0m         \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_convert_params\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msql\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1645\u001b[1;33m         \u001b[0mcursor\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1646\u001b[0m         \u001b[0mcolumns\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mcol_desc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcol_desc\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdescription\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1647\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1608\u001b[0m                 \u001b[1;34m\"Execution failed on sql '{sql}': {exc}\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msql\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mexc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1609\u001b[0m             )\n\u001b[1;32m-> 1610\u001b[1;33m             \u001b[0mraise_with_traceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1611\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1612\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\compat\\__init__.py\u001b[0m in \u001b[0;36mraise_with_traceback\u001b[1;34m(exc, traceback)\u001b[0m\n\u001b[0;32m     44\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mtraceback\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mEllipsis\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     45\u001b[0m         \u001b[0m_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtraceback\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 46\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtraceback\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     47\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     48\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1593\u001b[0m                 \u001b[0mcur\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1594\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1595\u001b[1;33m                 \u001b[0mcur\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1596\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mcur\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1597\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mDatabaseError\u001b[0m: Execution failed on sql 'SELECT * from addproduct WHERE category_id= SELECT category_id from addproduct where product_id=2': near \"SELECT\": syntax error"
     ]
    }
   ],
   "source": [
    "product_id=2\n",
    "pd.read_sql_query(\"SELECT * from addproduct WHERE category_id=\"+str(product_id), con)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "def content_based_filtering(product_id):\n",
    "    '''\n",
    "    subcategory=con.execute(\"SELECT subcategory_id from addproduct WHERE id=\"+str(product_id)+\" LIMIT 1\").fetchone()[0]\n",
    "    category=con.execute(\"SELECT category_id from addproduct WHERE id=\"+str(product_id)+\" LIMIT 1\").fetchone()[0]\n",
    "    if subcategory:\n",
    "        products=pd.read_sql_query(\"SELECT * from addproduct WHERE subcategory_id=\"+str(subcategory), con)\n",
    "    else:\n",
    "        products=pd.read_sql_query(\"SELECT * from addproduct WHERE category_id=\"+str(category), con)\n",
    "    print(products['id'])\n",
    "    '''\n",
    "    specs=pd.read_sql_query(\"SELECT product_id,spec_id from specsvalues where category_id=\"+str(category),con)\n",
    "    sp=specs.groupby('product_id')['spec_id'].apply(list).to_frame()\n",
    "    for i in specs['spec_id'].unique():\n",
    "        sp[i]=0\n",
    "    for i in sp.index:\n",
    "        for j in sp.loc[i,'spec_id']:\n",
    "            sp.loc[i,j]=1\n",
    "    sp=sp.drop('spec_id',axis='columns')\n",
    "    scores=pd.Series(index=sp.index)\n",
    "    for i in sp.index:\n",
    "        scores.loc[i]=sp.loc[product_id].dot(sp.loc[i])\n",
    "    return scores.sort_values(ascending=False)[scores>1]\n",
    "content_based_filtering(2)\n",
    "con.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>price</th>\n",
       "      <th>discount</th>\n",
       "      <th>stock</th>\n",
       "      <th>colors</th>\n",
       "      <th>desc</th>\n",
       "      <th>pub_date</th>\n",
       "      <th>category_id</th>\n",
       "      <th>subcategory_id</th>\n",
       "      <th>brand_id</th>\n",
       "      <th>image_1</th>\n",
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       "      <th>image_3</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Allen Solly Men's Plain Slim Fit Casual Shirt</td>\n",
       "      <td>699</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Purple, Black</td>\n",
       "      <td>Allen solly Mens Cotton Full sleeve Overdyed s...</td>\n",
       "      <td>2020-07-08 15:54:29.990947</td>\n",
       "      <td>1</td>\n",
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       "      <td>8</td>\n",
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       "      <td>d2bfc40b87bceda78823.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Park Avenue Men's Solid Slim Fit Formal Shirt</td>\n",
       "      <td>563</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>White, Blue, Khaki</td>\n",
       "      <td>This classic shirt from Park Avenue is a versa...</td>\n",
       "      <td>2020-07-08 15:57:00.755305</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>52e5a9ab0ec7bb30a1d8.jpg</td>\n",
       "      <td>6bc2786d351652afcfaf.jpg</td>\n",
       "      <td>b0fe79b775b77d9f15fb.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Park Avenue Men's Plain Slim Fit Formal Shirt</td>\n",
       "      <td>654</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>White, Blue, Black</td>\n",
       "      <td>Be noticed at work by enhancing your looks wit...</td>\n",
       "      <td>2020-07-08 15:58:57.811980</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>53a09ec68d5f5ab9627c.jpg</td>\n",
       "      <td>896324c13cde4988b3be.jpg</td>\n",
       "      <td>4537b9a61d8f4013fe9c.jpg</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Wrangler Men's Relaxed Fit Jeans</td>\n",
       "      <td>1198</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Wrangler is the everyday performance denim bra...</td>\n",
       "      <td>2020-07-08 16:02:12.713819</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>5a0acb1668f251563de0.jpg</td>\n",
       "      <td>7c21749eb23b984a2409.jpg</td>\n",
       "      <td>45c87ee10d8d3db36728.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Casio G-Shock Analog-Digital Blue Dial Men's W...</td>\n",
       "      <td>6396</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Mineral Glass Magnetic Resistant Shock Resista...</td>\n",
       "      <td>2020-07-08 16:05:11.097813</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>68618c07e20b3374a091.jpg</td>\n",
       "      <td>703665b9363046d63afa.jpg</td>\n",
       "      <td>e19c74bdbb6bbc914094.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>Casio G-Shock Analog-Digital Black Dial Men's ...</td>\n",
       "      <td>6496</td>\n",
       "      <td>5</td>\n",
       "      <td>100</td>\n",
       "      <td>Yellow</td>\n",
       "      <td>Mineral Glass Magnetic Resistant Shock Resista...</td>\n",
       "      <td>2020-07-08 16:07:09.307929</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>e3f360d8e0cde2ca0358.jpg</td>\n",
       "      <td>63ee5e5a2d06717c38e0.jpg</td>\n",
       "      <td>b8a0f4a34f265be10cb1.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>ACTIMOB Mktd Allen Solly Men's Genuine Rust Le...</td>\n",
       "      <td>1099</td>\n",
       "      <td>10</td>\n",
       "      <td>25</td>\n",
       "      <td>Brown, Black</td>\n",
       "      <td>ACTIMOB MKTD Allen Solly Men's genuine leather...</td>\n",
       "      <td>2020-07-08 16:11:03.696897</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>ae3d28a80715cf1b1569.jpg</td>\n",
       "      <td>07953dd23748ae646b99.jpg</td>\n",
       "      <td>48a2396646a1fc3e15fd.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>BATA Men Black Formal Shoes</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>500</td>\n",
       "      <td>Black</td>\n",
       "      <td>Add a stylish touch to your look when you ador...</td>\n",
       "      <td>2020-07-08 16:15:38.420984</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>3a57a942517193679bee.jpg</td>\n",
       "      <td>773f1eb4454dbf145191.jpg</td>\n",
       "      <td>166e81379638302ca0c7.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>Puma Men's Propel El Mu Idp Running Shoes</td>\n",
       "      <td>1599</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>The navy blue propel EL mu idp is from the run...</td>\n",
       "      <td>2020-07-08 16:18:14.512618</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>eacdf81c60a00eaee2d5.jpg</td>\n",
       "      <td>ca9f83b218482af402dc.jpg</td>\n",
       "      <td>cdf609029dff803f5e2d.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>Allen Solly Men's Polo</td>\n",
       "      <td>585</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Maroon, Purple, Black</td>\n",
       "      <td>Allen Solly Men's Plain Regular Fit Polo</td>\n",
       "      <td>2020-07-08 16:20:48.217788</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>02bf8c21a66b2e14fd2c.jpg</td>\n",
       "      <td>467acc9c954a5f23732a.jpg</td>\n",
       "      <td>4380eff72be27cfa66f7.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>GMI Women's Top</td>\n",
       "      <td>385</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Green, Black, White</td>\n",
       "      <td>Shop from a wide range of Top from GMI. Perfec...</td>\n",
       "      <td>2020-07-08 16:23:25.327349</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>2d7df245ba95a9abc9b8.jpg</td>\n",
       "      <td>59021ab157383fb6fd46.jpg</td>\n",
       "      <td>74bae75a95b38e35f87a.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>THE VANCA Women's Plain Regular Fit Top</td>\n",
       "      <td>585</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Green, blue</td>\n",
       "      <td>The Vanca light blue top with a round neck at ...</td>\n",
       "      <td>2020-07-08 16:25:38.845046</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>9c7c49c0cbb671e2ee66.jpg</td>\n",
       "      <td>f4ea7df2b75fddb5f03e.jpg</td>\n",
       "      <td>ffda9a466ae1cc6d274c.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>Wrangler Women's Skinny Fit Jeans</td>\n",
       "      <td>1200</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Wrangler is the everyday performance denim bra...</td>\n",
       "      <td>2020-07-08 16:29:16.541075</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>9d88922516cd8646ec23.jpg</td>\n",
       "      <td>d6b3ed3ab4d626991e7d.jpg</td>\n",
       "      <td>d2d2540c16097885664e.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>FIBREZA Women's Net Embroidered Anarkali Semi ...</td>\n",
       "      <td>1399</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Pink, Orange, Maroon</td>\n",
       "      <td>This Anarkali Semi Stitched Gown is Made From ...</td>\n",
       "      <td>2020-07-08 16:33:09.596860</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>d58a16cad17a62d9cc10.jpg</td>\n",
       "      <td>847824c926b23350617b.jpg</td>\n",
       "      <td>d86e3651d9eeab97ec4e.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>Sonata Analog Green Dial Women's Watch -NL8989...</td>\n",
       "      <td>575</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Technical information\\r\\n\\r\\nGeneral\\r\\nBrand ...</td>\n",
       "      <td>2020-07-08 16:36:07.418568</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>4dd1a44e16b08e3c5dd3.jpg</td>\n",
       "      <td>4fa13dab016147b7876b.jpg</td>\n",
       "      <td>c570822bfaf591928f2e.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>Sonata Analog Pink Dial Women's Watch -NK8976S...</td>\n",
       "      <td>625</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Black, Blue, Pink</td>\n",
       "      <td>Keeping in mind her need for the perfect blend...</td>\n",
       "      <td>2020-07-08 16:40:29.662122</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>00c557cb8b8b2c38072c.jpg</td>\n",
       "      <td>f9b2df34649faac3ffba.jpg</td>\n",
       "      <td>7523185045d3fa3896c3.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>Campus Women's Tulip Running Shoes</td>\n",
       "      <td>799</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Black, Pink, Yellow</td>\n",
       "      <td>Campus sport shoes are premium quality light w...</td>\n",
       "      <td>2020-07-08 16:46:02.415356</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>52e5bb4156cd718271be.jpg</td>\n",
       "      <td>b98dc9b902236358b590.jpg</td>\n",
       "      <td>4d61817b5b9b558e67fd.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>United Colors of Benetton Boys Blue Regular Fi...</td>\n",
       "      <td>1599</td>\n",
       "      <td>10</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Blue solid casual shirt with applique detail, ...</td>\n",
       "      <td>2020-07-08 17:20:10.287478</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "      <td>9f8a15f56c86b5d8add2.jpg</td>\n",
       "      <td>ab9ca26d127d815dbb10.jpg</td>\n",
       "      <td>ade7a962b8e38500fe3b.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>Flying Machine Boys White &amp; Blue Regular Fit S...</td>\n",
       "      <td>1199</td>\n",
       "      <td>10</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>White and Blue striped casual shirt, has a spr...</td>\n",
       "      <td>2020-07-08 17:22:16.875577</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>17</td>\n",
       "      <td>fabdbea3970c21ca5328.jpg</td>\n",
       "      <td>0d4c83aa888a7ff3719e.jpg</td>\n",
       "      <td>f0ea7933505a707a571c.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>United Colors of Benetton Boys Blue Mid-Rise C...</td>\n",
       "      <td>1799</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Blue medium acid wash 5-pocket mid-rise jeans,...</td>\n",
       "      <td>2020-07-08 17:24:47.329044</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "      <td>c81501fa53315e900316.jpg</td>\n",
       "      <td>95202859c9a22598f63b.jpg</td>\n",
       "      <td>96279b2a55112f713ea4.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>21</td>\n",
       "      <td>United Colors of Benetton Boys Blue Slim Fit M...</td>\n",
       "      <td>1599</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Black, Blue</td>\n",
       "      <td>Blue medium wash 5-pocket mid-rise jeans, mild...</td>\n",
       "      <td>2020-07-08 17:27:34.183788</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "      <td>dd765d3419f49c675599.jpg</td>\n",
       "      <td>e455cfe9ed293774dddf.jpg</td>\n",
       "      <td>ec52036f0d7be694dc4e.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>CACA CINA Girls Red Georgette Polka Dot Top</td>\n",
       "      <td>566</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Pink</td>\n",
       "      <td>Red printed woven regular top, has a shoulder ...</td>\n",
       "      <td>2020-07-08 17:32:10.045869</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>d8beb8131a6a796610a2.jpg</td>\n",
       "      <td>0c51a3f4604ba9ac1899.jpg</td>\n",
       "      <td>0a87b49d268338ca8dfb.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>23</td>\n",
       "      <td>CACA CINA Girls Navy Blue Printed Tiered Top</td>\n",
       "      <td>566</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Navy Blue printed woven tiered top, has should...</td>\n",
       "      <td>2020-07-08 17:34:17.662085</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>3ab64aeebee3ef77157c.jpg</td>\n",
       "      <td>885142af83eb4ec2c881.jpg</td>\n",
       "      <td>4d182188cd2d7578c99a.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>24</td>\n",
       "      <td>United Colors of Benetton Girls Blue Regular F...</td>\n",
       "      <td>1799</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>Blue</td>\n",
       "      <td>Blue dark wash 5-pocket mid-rise jeans with em...</td>\n",
       "      <td>2020-07-08 17:36:47.136558</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>16</td>\n",
       "      <td>7c6512323c7a6aae9598.jpg</td>\n",
       "      <td>3558591d1908204ceb2e.jpg</td>\n",
       "      <td>81cc9150f3fe255979a7.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>United Colors of Benetton Kids Black &amp; White P...</td>\n",
       "      <td>2499</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>Black</td>\n",
       "      <td>A pair of round-toe black and white printed fl...</td>\n",
       "      <td>2020-07-08 17:39:31.378635</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>a5e2ab30d6a6d6159fc2.jpg</td>\n",
       "      <td>2b0a6ad9ecf295a4036d.jpg</td>\n",
       "      <td>074325b2600255b5604d.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>Campus Boys Black Sneakers</td>\n",
       "      <td>495</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Black, White</td>\n",
       "      <td>A pair of round-toe black sneakers, has regula...</td>\n",
       "      <td>2020-07-08 17:41:50.590949</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>5fb967be9acb8870214d.jpg</td>\n",
       "      <td>66c86a908c84539d122e.jpg</td>\n",
       "      <td>80414963d8891034e3a1.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>27</td>\n",
       "      <td>Puma Kids Girls Pink Smash V2 Glitz Glam Youth...</td>\n",
       "      <td>1499</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>Pink</td>\n",
       "      <td>DETAILS\\r\\nSynthetic upper\\r\\nNon-marking rubb...</td>\n",
       "      <td>2020-07-08 17:43:36.541977</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>7</td>\n",
       "      <td>d6fdbb7f8eaf04d4e85e.jpg</td>\n",
       "      <td>e5353c6a0b2b2360c410.jpg</td>\n",
       "      <td>9842fad1a0823ec71991.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>Barbie Girls Pink Shimmer Sneakers</td>\n",
       "      <td>1200</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Pink</td>\n",
       "      <td>A pair of round-toe pink shimmer sneakers, has...</td>\n",
       "      <td>2020-07-08 17:45:17.176036</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>15</td>\n",
       "      <td>6930c2bbb340f2dbad9a.jpg</td>\n",
       "      <td>11a2f15732326beb5237.jpg</td>\n",
       "      <td>7faf3818cede9b7c7327.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>Creative Educational Aids P. Ltd. Fun With Wor...</td>\n",
       "      <td>213</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Multi</td>\n",
       "      <td>Educational Objective(s)\\t\"Fun with Words\" is ...</td>\n",
       "      <td>2020-07-08 17:48:59.572423</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>a6abf7b6a69f388cd5eb.jpg</td>\n",
       "      <td>e0dd64e1a379eba6bbfc.jpg</td>\n",
       "      <td>1c4a2aa56a4c963c4f9e.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>Einstein Box for 3 Year Old Baby Boys and Girl...</td>\n",
       "      <td>599</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Multi</td>\n",
       "      <td>Assembly Required\\tNo\\r\\nBatteries Required\\tN...</td>\n",
       "      <td>2020-07-08 17:50:58.596841</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>3f38d75811f9a280282f.jpg</td>\n",
       "      <td>c54dd753ae781f0efe76.jpg</td>\n",
       "      <td>7c2f36333eb29acc1aa9.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>31</td>\n",
       "      <td>Time Travlr Men Maroon &amp; Black Regular Fit Che...</td>\n",
       "      <td>649</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>Red</td>\n",
       "      <td>Maroon and black checked casual shirt, has a s...</td>\n",
       "      <td>2020-07-09 16:36:52.039533</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>60484a12700fd4e28862.jpg</td>\n",
       "      <td>8aeef96d6a4331b41fe7.jpg</td>\n",
       "      <td>dfb132b6330e3a1d2517.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>Time Travlr Men Black &amp; Grey Checked Casual Shirt</td>\n",
       "      <td>649</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>Black</td>\n",
       "      <td>Black and grey checked casual shirt, has a spr...</td>\n",
       "      <td>2020-07-09 16:47:15.603108</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>3218c3582e825e5ec4f3.jpg</td>\n",
       "      <td>876efeac71732801e589.jpg</td>\n",
       "      <td>ca915e2ebc1f4e8bbfd8.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>0</td>\n",
       "      <td>200</td>\n",
       "      <td>Brown</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>2020-07-09 17:01:23.582165</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>e26fed0bd68205101f95.jpg</td>\n",
       "      <td>97119b43b61c1d122c92.jpg</td>\n",
       "      <td>f29133d4235644b05c78.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id                                               name  price  discount  \\\n",
       "0    1      Allen Solly Men's Plain Slim Fit Casual Shirt    699         0   \n",
       "1    2      Park Avenue Men's Solid Slim Fit Formal Shirt    563         0   \n",
       "2    3      Park Avenue Men's Plain Slim Fit Formal Shirt    654         0   \n",
       "3    4                   Wrangler Men's Relaxed Fit Jeans   1198         5   \n",
       "4    5  Casio G-Shock Analog-Digital Blue Dial Men's W...   6396         0   \n",
       "5    6  Casio G-Shock Analog-Digital Black Dial Men's ...   6496         5   \n",
       "6    7  ACTIMOB Mktd Allen Solly Men's Genuine Rust Le...   1099        10   \n",
       "7    8                        BATA Men Black Formal Shoes    999         0   \n",
       "8    9          Puma Men's Propel El Mu Idp Running Shoes   1599         0   \n",
       "9   10                             Allen Solly Men's Polo    585         0   \n",
       "10  11                                    GMI Women's Top    385         0   \n",
       "11  12            THE VANCA Women's Plain Regular Fit Top    585         0   \n",
       "12  13               Wrangler Women's Skinny Fit Jeans      1200        10   \n",
       "13  14  FIBREZA Women's Net Embroidered Anarkali Semi ...   1399         0   \n",
       "14  15  Sonata Analog Green Dial Women's Watch -NL8989...    575         0   \n",
       "15  16  Sonata Analog Pink Dial Women's Watch -NK8976S...    625         0   \n",
       "16  17                 Campus Women's Tulip Running Shoes    799         0   \n",
       "17  18  United Colors of Benetton Boys Blue Regular Fi...   1599        10   \n",
       "18  19  Flying Machine Boys White & Blue Regular Fit S...   1199        10   \n",
       "19  20  United Colors of Benetton Boys Blue Mid-Rise C...   1799        20   \n",
       "20  21  United Colors of Benetton Boys Blue Slim Fit M...   1599         0   \n",
       "21  22        CACA CINA Girls Red Georgette Polka Dot Top    566         0   \n",
       "22  23       CACA CINA Girls Navy Blue Printed Tiered Top    566         0   \n",
       "23  24  United Colors of Benetton Girls Blue Regular F...   1799        15   \n",
       "24  25  United Colors of Benetton Kids Black & White P...   2499        15   \n",
       "25  26                         Campus Boys Black Sneakers    495         0   \n",
       "26  27  Puma Kids Girls Pink Smash V2 Glitz Glam Youth...   1499        15   \n",
       "27  28                 Barbie Girls Pink Shimmer Sneakers   1200         0   \n",
       "28  29  Creative Educational Aids P. Ltd. Fun With Wor...    213         0   \n",
       "29  30  Einstein Box for 3 Year Old Baby Boys and Girl...    599         0   \n",
       "30  31  Time Travlr Men Maroon & Black Regular Fit Che...    649         0   \n",
       "31  32  Time Travlr Men Black & Grey Checked Casual Shirt    649         0   \n",
       "32  33               Men Brown Printed Round Neck T-shirt    350         0   \n",
       "\n",
       "    stock                 colors  \\\n",
       "0      25    Blue, Purple, Black   \n",
       "1      15     White, Blue, Khaki   \n",
       "2      15     White, Blue, Black   \n",
       "3      25            Blue, Black   \n",
       "4      25            Blue, Black   \n",
       "5     100                 Yellow   \n",
       "6      25           Brown, Black   \n",
       "7     500                  Black   \n",
       "8      25            Blue, Black   \n",
       "9      15  Maroon, Purple, Black   \n",
       "10     15    Green, Black, White   \n",
       "11     25            Green, blue   \n",
       "12     15            Blue, Black   \n",
       "13     25   Pink, Orange, Maroon   \n",
       "14     25            Blue, Black   \n",
       "15     15      Black, Blue, Pink   \n",
       "16     15    Black, Pink, Yellow   \n",
       "17     25            Blue, Black   \n",
       "18     25            Blue, Black   \n",
       "19     25            Blue, Black   \n",
       "20     15            Black, Blue   \n",
       "21     15                   Pink   \n",
       "22     25            Blue, Black   \n",
       "23     15                   Blue   \n",
       "24     25                  Black   \n",
       "25     25           Black, White   \n",
       "26     25                   Pink   \n",
       "27     25                   Pink   \n",
       "28     25                  Multi   \n",
       "29     25                  Multi   \n",
       "30    100                    Red   \n",
       "31    150                  Black   \n",
       "32    200                  Brown   \n",
       "\n",
       "                                                 desc  \\\n",
       "0   Allen solly Mens Cotton Full sleeve Overdyed s...   \n",
       "1   This classic shirt from Park Avenue is a versa...   \n",
       "2   Be noticed at work by enhancing your looks wit...   \n",
       "3   Wrangler is the everyday performance denim bra...   \n",
       "4   Mineral Glass Magnetic Resistant Shock Resista...   \n",
       "5   Mineral Glass Magnetic Resistant Shock Resista...   \n",
       "6   ACTIMOB MKTD Allen Solly Men's genuine leather...   \n",
       "7   Add a stylish touch to your look when you ador...   \n",
       "8   The navy blue propel EL mu idp is from the run...   \n",
       "9            Allen Solly Men's Plain Regular Fit Polo   \n",
       "10  Shop from a wide range of Top from GMI. Perfec...   \n",
       "11  The Vanca light blue top with a round neck at ...   \n",
       "12  Wrangler is the everyday performance denim bra...   \n",
       "13  This Anarkali Semi Stitched Gown is Made From ...   \n",
       "14  Technical information\\r\\n\\r\\nGeneral\\r\\nBrand ...   \n",
       "15  Keeping in mind her need for the perfect blend...   \n",
       "16  Campus sport shoes are premium quality light w...   \n",
       "17  Blue solid casual shirt with applique detail, ...   \n",
       "18  White and Blue striped casual shirt, has a spr...   \n",
       "19  Blue medium acid wash 5-pocket mid-rise jeans,...   \n",
       "20  Blue medium wash 5-pocket mid-rise jeans, mild...   \n",
       "21  Red printed woven regular top, has a shoulder ...   \n",
       "22  Navy Blue printed woven tiered top, has should...   \n",
       "23  Blue dark wash 5-pocket mid-rise jeans with em...   \n",
       "24  A pair of round-toe black and white printed fl...   \n",
       "25  A pair of round-toe black sneakers, has regula...   \n",
       "26  DETAILS\\r\\nSynthetic upper\\r\\nNon-marking rubb...   \n",
       "27  A pair of round-toe pink shimmer sneakers, has...   \n",
       "28  Educational Objective(s)\\t\"Fun with Words\" is ...   \n",
       "29  Assembly Required\\tNo\\r\\nBatteries Required\\tN...   \n",
       "30  Maroon and black checked casual shirt, has a s...   \n",
       "31  Black and grey checked casual shirt, has a spr...   \n",
       "32  Brown printed T-shirt, has a round neck, short...   \n",
       "\n",
       "                      pub_date  category_id  subcategory_id  brand_id  \\\n",
       "0   2020-07-08 15:54:29.990947            1               2         8   \n",
       "1   2020-07-08 15:57:00.755305            1               2        11   \n",
       "2   2020-07-08 15:58:57.811980            1               2        11   \n",
       "3   2020-07-08 16:02:12.713819            1               3        12   \n",
       "4   2020-07-08 16:05:11.097813            1               4        13   \n",
       "5   2020-07-08 16:07:09.307929            1               4        13   \n",
       "6   2020-07-08 16:11:03.696897            1               5         8   \n",
       "7   2020-07-08 16:15:38.420984            1               6        14   \n",
       "8   2020-07-08 16:18:14.512618            1               6         7   \n",
       "9   2020-07-08 16:20:48.217788            1              24         8   \n",
       "10  2020-07-08 16:23:25.327349            2               7         9   \n",
       "11  2020-07-08 16:25:38.845046            2               7        10   \n",
       "12  2020-07-08 16:29:16.541075            2               9        12   \n",
       "13  2020-07-08 16:33:09.596860            2              10         6   \n",
       "14  2020-07-08 16:36:07.418568            2              11         1   \n",
       "15  2020-07-08 16:40:29.662122            2              11         1   \n",
       "16  2020-07-08 16:46:02.415356            2              12        15   \n",
       "17  2020-07-08 17:20:10.287478            3              13        16   \n",
       "18  2020-07-08 17:22:16.875577            3              13        17   \n",
       "19  2020-07-08 17:24:47.329044            3              13        16   \n",
       "20  2020-07-08 17:27:34.183788            3              13        16   \n",
       "21  2020-07-08 17:32:10.045869            3              14         5   \n",
       "22  2020-07-08 17:34:17.662085            3              14         5   \n",
       "23  2020-07-08 17:36:47.136558            3              14        16   \n",
       "24  2020-07-08 17:39:31.378635            3              15        16   \n",
       "25  2020-07-08 17:41:50.590949            3              15        15   \n",
       "26  2020-07-08 17:43:36.541977            3              16         7   \n",
       "27  2020-07-08 17:45:17.176036            3              16        15   \n",
       "28  2020-07-08 17:48:59.572423            3              30         4   \n",
       "29  2020-07-08 17:50:58.596841            3              30         4   \n",
       "30  2020-07-09 16:36:52.039533            1               2        11   \n",
       "31  2020-07-09 16:47:15.603108            1               2        11   \n",
       "32  2020-07-09 17:01:23.582165            1              24        17   \n",
       "\n",
       "                     image_1                   image_2  \\\n",
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       "30  60484a12700fd4e28862.jpg  8aeef96d6a4331b41fe7.jpg   \n",
       "31  3218c3582e825e5ec4f3.jpg  876efeac71732801e589.jpg   \n",
       "32  e26fed0bd68205101f95.jpg  97119b43b61c1d122c92.jpg   \n",
       "\n",
       "                     image_3  \n",
       "0   d2bfc40b87bceda78823.jpg  \n",
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       "6   48a2396646a1fc3e15fd.jpg  \n",
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       "14  c570822bfaf591928f2e.jpg  \n",
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       "17  ade7a962b8e38500fe3b.jpg  \n",
       "18  f0ea7933505a707a571c.jpg  \n",
       "19  96279b2a55112f713ea4.jpg  \n",
       "20  ec52036f0d7be694dc4e.jpg  \n",
       "21  0a87b49d268338ca8dfb.jpg  \n",
       "22  4d182188cd2d7578c99a.jpg  \n",
       "23  81cc9150f3fe255979a7.jpg  \n",
       "24  074325b2600255b5604d.jpg  \n",
       "25  80414963d8891034e3a1.jpg  \n",
       "26  9842fad1a0823ec71991.jpg  \n",
       "27  7faf3818cede9b7c7327.jpg  \n",
       "28  1c4a2aa56a4c963c4f9e.jpg  \n",
       "29  7c2f36333eb29acc1aa9.jpg  \n",
       "30  dfb132b6330e3a1d2517.jpg  \n",
       "31  ca915e2ebc1f4e8bbfd8.jpg  \n",
       "32  f29133d4235644b05c78.jpg  "
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addproduct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(s1.loc[(s1['product_id']==product_id),[x for x in s1.columns if x!='product_id']].dot(s1.loc[i,[x for x in s1.columns if x!='product_id']]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1.loc[s1['product_id']==product_id,[x for x in s1.columns if x!='product_id' and x!='spec_id']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#s1=s1.drop('spec_id',axis='columns')\n",
    "s1.loc[(s1['product_id']==1),[x for x in s1.columns if x!='product_id' and x!='spec_id']].dot(s1.loc[2,[x for x in s1.columns if x!='product_id' and x!='spec_id']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#scores=pd.Series(index=s1['product_id'])\n",
    "scores.loc[33]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product_id</th>\n",
       "      <th>spec_id</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>[21, 22, 23, 24, 25, 26]</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[27, 28, 29, 30, 31, 32]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[33, 34, 35, 36, 37]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>[38, 39, 40, 41, 42, 43]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>[43, 44, 46, 47, 48]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>[1, 3, 5, 12, 17, 50]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>31</td>\n",
       "      <td>[1, 2, 3, 8, 12, 13]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>32</td>\n",
       "      <td>[1, 2, 3, 8, 11, 14]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>33</td>\n",
       "      <td>[1, 3, 12, 15, 16, 17]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    product_id                   spec_id  1  2  3  8  12  13  11  14  ...  39  \\\n",
       "0            1                    [1, 2]  0  0  0  0   0   0   0   0  ...   0   \n",
       "1            2   [2, 3, 4, 5, 6, 10, 19]  0  0  0  0   0   0   0   0  ...   0   \n",
       "2            3      [2, 3, 5, 6, 10, 20]  0  0  0  0   0   0   0   0  ...   0   \n",
       "3            4  [21, 22, 23, 24, 25, 26]  0  0  0  0   0   0   0   0  ...   0   \n",
       "4            5  [27, 28, 29, 30, 31, 32]  0  0  0  0   0   0   0   0  ...   0   \n",
       "5            6  [27, 28, 29, 30, 31, 32]  0  0  0  0   0   0   0   0  ...   0   \n",
       "6            7      [33, 34, 35, 36, 37]  0  0  0  0   0   0   0   0  ...   0   \n",
       "7            8  [38, 39, 40, 41, 42, 43]  0  0  0  0   0   0   0   0  ...   0   \n",
       "8            9      [43, 44, 46, 47, 48]  0  0  0  0   0   0   0   0  ...   0   \n",
       "9           10     [1, 3, 5, 12, 17, 50]  0  0  0  0   0   0   0   0  ...   0   \n",
       "10          31      [1, 2, 3, 8, 12, 13]  0  0  0  0   0   0   0   0  ...   0   \n",
       "11          32      [1, 2, 3, 8, 11, 14]  0  0  0  0   0   0   0   0  ...   0   \n",
       "12          33    [1, 3, 12, 15, 16, 17]  0  0  0  0   0   0   0   0  ...   0   \n",
       "\n",
       "    40  41  42  43  44  46  47  48  50  \n",
       "0    0   0   0   0   0   0   0   0   0  \n",
       "1    0   0   0   0   0   0   0   0   0  \n",
       "2    0   0   0   0   0   0   0   0   0  \n",
       "3    0   0   0   0   0   0   0   0   0  \n",
       "4    0   0   0   0   0   0   0   0   0  \n",
       "5    0   0   0   0   0   0   0   0   0  \n",
       "6    0   0   0   0   0   0   0   0   0  \n",
       "7    0   0   0   0   0   0   0   0   0  \n",
       "8    0   0   0   0   0   0   0   0   0  \n",
       "9    0   0   0   0   0   0   0   0   0  \n",
       "10   0   0   0   0   0   0   0   0   0  \n",
       "11   0   0   0   0   0   0   0   0   0  \n",
       "12   0   0   0   0   0   0   0   0   0  \n",
       "\n",
       "[13 rows x 47 columns]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in s['spec_id'].unique():\n",
    "    s1[i]=0\n",
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "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",
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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_id</th>\n",
       "      <th>spec_id</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>8</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>11</th>\n",
       "      <th>14</th>\n",
       "      <th>...</th>\n",
       "      <th>39</th>\n",
       "      <th>40</th>\n",
       "      <th>41</th>\n",
       "      <th>42</th>\n",
       "      <th>43</th>\n",
       "      <th>44</th>\n",
       "      <th>46</th>\n",
       "      <th>47</th>\n",
       "      <th>48</th>\n",
       "      <th>50</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>[1, 2]</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>[2, 3, 5, 6, 10, 20]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>[21, 22, 23, 24, 25, 26]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[27, 28, 29, 30, 31, 32]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[27, 28, 29, 30, 31, 32]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[33, 34, 35, 36, 37]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>[38, 39, 40, 41, 42, 43]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>[43, 44, 46, 47, 48]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>[1, 3, 5, 12, 17, 50]</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>31</td>\n",
       "      <td>[1, 2, 3, 8, 12, 13]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>32</td>\n",
       "      <td>[1, 2, 3, 8, 11, 14]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>33</td>\n",
       "      <td>[1, 3, 12, 15, 16, 17]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    product_id                   spec_id  1  2  3  8  12  13  11  14  ...  39  \\\n",
       "0            1                    [1, 2]  1  1  0  0   0   0   0   0  ...   0   \n",
       "1            2   [2, 3, 4, 5, 6, 10, 19]  0  1  1  0   0   0   0   0  ...   0   \n",
       "2            3      [2, 3, 5, 6, 10, 20]  0  1  1  0   0   0   0   0  ...   0   \n",
       "3            4  [21, 22, 23, 24, 25, 26]  0  0  0  0   0   0   0   0  ...   0   \n",
       "4            5  [27, 28, 29, 30, 31, 32]  0  0  0  0   0   0   0   0  ...   0   \n",
       "5            6  [27, 28, 29, 30, 31, 32]  0  0  0  0   0   0   0   0  ...   0   \n",
       "6            7      [33, 34, 35, 36, 37]  0  0  0  0   0   0   0   0  ...   0   \n",
       "7            8  [38, 39, 40, 41, 42, 43]  0  0  0  0   0   0   0   0  ...   1   \n",
       "8            9      [43, 44, 46, 47, 48]  0  0  0  0   0   0   0   0  ...   0   \n",
       "9           10     [1, 3, 5, 12, 17, 50]  1  0  1  0   1   0   0   0  ...   0   \n",
       "10          31      [1, 2, 3, 8, 12, 13]  1  1  1  1   1   1   0   0  ...   0   \n",
       "11          32      [1, 2, 3, 8, 11, 14]  1  1  1  1   0   0   1   1  ...   0   \n",
       "12          33    [1, 3, 12, 15, 16, 17]  1  0  1  0   1   0   0   0  ...   0   \n",
       "\n",
       "    40  41  42  43  44  46  47  48  50  \n",
       "0    0   0   0   0   0   0   0   0   0  \n",
       "1    0   0   0   0   0   0   0   0   0  \n",
       "2    0   0   0   0   0   0   0   0   0  \n",
       "3    0   0   0   0   0   0   0   0   0  \n",
       "4    0   0   0   0   0   0   0   0   0  \n",
       "5    0   0   0   0   0   0   0   0   0  \n",
       "6    0   0   0   0   0   0   0   0   0  \n",
       "7    1   1   1   1   0   0   0   0   0  \n",
       "8    0   0   0   1   1   1   1   1   0  \n",
       "9    0   0   0   0   0   0   0   0   1  \n",
       "10   0   0   0   0   0   0   0   0   0  \n",
       "11   0   0   0   0   0   0   0   0   0  \n",
       "12   0   0   0   0   0   0   0   0   0  \n",
       "\n",
       "[13 rows x 47 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in s1.index:\n",
    "    for j in s1.loc[i,'spec_id']:\n",
    "        s1.loc[i,j]=1\n",
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2, 3, 4, 5, 6, 10, 19]"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1.loc[1,'spec_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <td>70</td>\n",
       "      <td>10</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    product_id  spec_id\n",
       "0            1        1\n",
       "1            1        2\n",
       "2           31        1\n",
       "3           31        2\n",
       "4           31        3\n",
       "..         ...      ...\n",
       "68          10        3\n",
       "69          10        5\n",
       "70          10       12\n",
       "71          10       17\n",
       "72          10       50\n",
       "\n",
       "[73 rows x 2 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s=pd.read_sql_query(\"SELECT product_id,spec_id from specsvalues where category_id=\"+str(1),con)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1=s.groupby('product_id')['spec_id'].apply(list)\n",
    "type(s1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>9</td>\n",
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       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    product_id                   spec_id\n",
       "0            1                    [1, 2]\n",
       "1            2   [2, 3, 4, 5, 6, 10, 19]\n",
       "2            3      [2, 3, 5, 6, 10, 20]\n",
       "3            4  [21, 22, 23, 24, 25, 26]\n",
       "4            5  [27, 28, 29, 30, 31, 32]\n",
       "5            6  [27, 28, 29, 30, 31, 32]\n",
       "6            7      [33, 34, 35, 36, 37]\n",
       "7            8  [38, 39, 40, 41, 42, 43]\n",
       "8            9      [43, 44, 46, 47, 48]\n",
       "9           10     [1, 3, 5, 12, 17, 50]\n",
       "10          31      [1, 2, 3, 8, 12, 13]\n",
       "11          32      [1, 2, 3, 8, 11, 14]\n",
       "12          33    [1, 3, 12, 15, 16, 17]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1=s1.to_frame().reset_index()\n",
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0</td>\n",
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       "      <td>Allen Solly Men's Plain Slim Fit Casual Shirt</td>\n",
       "      <td>699</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Purple, Black</td>\n",
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       "    <tr>\n",
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       "      <td>2</td>\n",
       "      <td>Park Avenue Men's Solid Slim Fit Formal Shirt</td>\n",
       "      <td>563</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>White, Blue, Khaki</td>\n",
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       "      <td>Park Avenue Men's Plain Slim Fit Formal Shirt</td>\n",
       "      <td>654</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>White, Blue, Black</td>\n",
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       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Wrangler Men's Relaxed Fit Jeans</td>\n",
       "      <td>1198</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Wrangler is the everyday performance denim bra...</td>\n",
       "      <td>2020-07-08 16:02:12.713819</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>5a0acb1668f251563de0.jpg</td>\n",
       "      <td>7c21749eb23b984a2409.jpg</td>\n",
       "      <td>45c87ee10d8d3db36728.jpg</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Casio G-Shock Analog-Digital Blue Dial Men's W...</td>\n",
       "      <td>6396</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>Mineral Glass Magnetic Resistant Shock Resista...</td>\n",
       "      <td>2020-07-08 16:05:11.097813</td>\n",
       "      <td>1</td>\n",
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       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>Casio G-Shock Analog-Digital Black Dial Men's ...</td>\n",
       "      <td>6496</td>\n",
       "      <td>5</td>\n",
       "      <td>100</td>\n",
       "      <td>Yellow</td>\n",
       "      <td>Mineral Glass Magnetic Resistant Shock Resista...</td>\n",
       "      <td>2020-07-08 16:07:09.307929</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
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       "      <td>b8a0f4a34f265be10cb1.jpg</td>\n",
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       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>ACTIMOB Mktd Allen Solly Men's Genuine Rust Le...</td>\n",
       "      <td>1099</td>\n",
       "      <td>10</td>\n",
       "      <td>25</td>\n",
       "      <td>Brown, Black</td>\n",
       "      <td>ACTIMOB MKTD Allen Solly Men's genuine leather...</td>\n",
       "      <td>2020-07-08 16:11:03.696897</td>\n",
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       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>BATA Men Black Formal Shoes</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>500</td>\n",
       "      <td>Black</td>\n",
       "      <td>Add a stylish touch to your look when you ador...</td>\n",
       "      <td>2020-07-08 16:15:38.420984</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>3a57a942517193679bee.jpg</td>\n",
       "      <td>773f1eb4454dbf145191.jpg</td>\n",
       "      <td>166e81379638302ca0c7.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>Puma Men's Propel El Mu Idp Running Shoes</td>\n",
       "      <td>1599</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>Blue, Black</td>\n",
       "      <td>The navy blue propel EL mu idp is from the run...</td>\n",
       "      <td>2020-07-08 16:18:14.512618</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>eacdf81c60a00eaee2d5.jpg</td>\n",
       "      <td>ca9f83b218482af402dc.jpg</td>\n",
       "      <td>cdf609029dff803f5e2d.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>Allen Solly Men's Polo</td>\n",
       "      <td>585</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>Maroon, Purple, Black</td>\n",
       "      <td>Allen Solly Men's Plain Regular Fit Polo</td>\n",
       "      <td>2020-07-08 16:20:48.217788</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>02bf8c21a66b2e14fd2c.jpg</td>\n",
       "      <td>467acc9c954a5f23732a.jpg</td>\n",
       "      <td>4380eff72be27cfa66f7.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>31</td>\n",
       "      <td>Time Travlr Men Maroon &amp; Black Regular Fit Che...</td>\n",
       "      <td>649</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>Red</td>\n",
       "      <td>Maroon and black checked casual shirt, has a s...</td>\n",
       "      <td>2020-07-09 16:36:52.039533</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>60484a12700fd4e28862.jpg</td>\n",
       "      <td>8aeef96d6a4331b41fe7.jpg</td>\n",
       "      <td>dfb132b6330e3a1d2517.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>32</td>\n",
       "      <td>Time Travlr Men Black &amp; Grey Checked Casual Shirt</td>\n",
       "      <td>649</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>Black</td>\n",
       "      <td>Black and grey checked casual shirt, has a spr...</td>\n",
       "      <td>2020-07-09 16:47:15.603108</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>3218c3582e825e5ec4f3.jpg</td>\n",
       "      <td>876efeac71732801e589.jpg</td>\n",
       "      <td>ca915e2ebc1f4e8bbfd8.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>33</td>\n",
       "      <td>Men Brown Printed Round Neck T-shirt</td>\n",
       "      <td>350</td>\n",
       "      <td>0</td>\n",
       "      <td>200</td>\n",
       "      <td>Brown</td>\n",
       "      <td>Brown printed T-shirt, has a round neck, short...</td>\n",
       "      <td>2020-07-09 17:01:23.582165</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>17</td>\n",
       "      <td>e26fed0bd68205101f95.jpg</td>\n",
       "      <td>97119b43b61c1d122c92.jpg</td>\n",
       "      <td>f29133d4235644b05c78.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id                                               name  price  discount  \\\n",
       "0    1      Allen Solly Men's Plain Slim Fit Casual Shirt    699         0   \n",
       "1    2      Park Avenue Men's Solid Slim Fit Formal Shirt    563         0   \n",
       "2    3      Park Avenue Men's Plain Slim Fit Formal Shirt    654         0   \n",
       "3    4                   Wrangler Men's Relaxed Fit Jeans   1198         5   \n",
       "4    5  Casio G-Shock Analog-Digital Blue Dial Men's W...   6396         0   \n",
       "5    6  Casio G-Shock Analog-Digital Black Dial Men's ...   6496         5   \n",
       "6    7  ACTIMOB Mktd Allen Solly Men's Genuine Rust Le...   1099        10   \n",
       "7    8                        BATA Men Black Formal Shoes    999         0   \n",
       "8    9          Puma Men's Propel El Mu Idp Running Shoes   1599         0   \n",
       "9   10                             Allen Solly Men's Polo    585         0   \n",
       "10  31  Time Travlr Men Maroon & Black Regular Fit Che...    649         0   \n",
       "11  32  Time Travlr Men Black & Grey Checked Casual Shirt    649         0   \n",
       "12  33               Men Brown Printed Round Neck T-shirt    350         0   \n",
       "\n",
       "    stock                 colors  \\\n",
       "0      25    Blue, Purple, Black   \n",
       "1      15     White, Blue, Khaki   \n",
       "2      15     White, Blue, Black   \n",
       "3      25            Blue, Black   \n",
       "4      25            Blue, Black   \n",
       "5     100                 Yellow   \n",
       "6      25           Brown, Black   \n",
       "7     500                  Black   \n",
       "8      25            Blue, Black   \n",
       "9      15  Maroon, Purple, Black   \n",
       "10    100                    Red   \n",
       "11    150                  Black   \n",
       "12    200                  Brown   \n",
       "\n",
       "                                                 desc  \\\n",
       "0   Allen solly Mens Cotton Full sleeve Overdyed s...   \n",
       "1   This classic shirt from Park Avenue is a versa...   \n",
       "2   Be noticed at work by enhancing your looks wit...   \n",
       "3   Wrangler is the everyday performance denim bra...   \n",
       "4   Mineral Glass Magnetic Resistant Shock Resista...   \n",
       "5   Mineral Glass Magnetic Resistant Shock Resista...   \n",
       "6   ACTIMOB MKTD Allen Solly Men's genuine leather...   \n",
       "7   Add a stylish touch to your look when you ador...   \n",
       "8   The navy blue propel EL mu idp is from the run...   \n",
       "9            Allen Solly Men's Plain Regular Fit Polo   \n",
       "10  Maroon and black checked casual shirt, has a s...   \n",
       "11  Black and grey checked casual shirt, has a spr...   \n",
       "12  Brown printed T-shirt, has a round neck, short...   \n",
       "\n",
       "                      pub_date  category_id  subcategory_id  brand_id  \\\n",
       "0   2020-07-08 15:54:29.990947            1               2         8   \n",
       "1   2020-07-08 15:57:00.755305            1               2        11   \n",
       "2   2020-07-08 15:58:57.811980            1               2        11   \n",
       "3   2020-07-08 16:02:12.713819            1               3        12   \n",
       "4   2020-07-08 16:05:11.097813            1               4        13   \n",
       "5   2020-07-08 16:07:09.307929            1               4        13   \n",
       "6   2020-07-08 16:11:03.696897            1               5         8   \n",
       "7   2020-07-08 16:15:38.420984            1               6        14   \n",
       "8   2020-07-08 16:18:14.512618            1               6         7   \n",
       "9   2020-07-08 16:20:48.217788            1              24         8   \n",
       "10  2020-07-09 16:36:52.039533            1               2        11   \n",
       "11  2020-07-09 16:47:15.603108            1               2        11   \n",
       "12  2020-07-09 17:01:23.582165            1              24        17   \n",
       "\n",
       "                     image_1                   image_2  \\\n",
       "0   58a16e6bee54bb2cddbf.jpg  a983bf257c13c61f6600.jpg   \n",
       "1   52e5a9ab0ec7bb30a1d8.jpg  6bc2786d351652afcfaf.jpg   \n",
       "2   53a09ec68d5f5ab9627c.jpg  896324c13cde4988b3be.jpg   \n",
       "3   5a0acb1668f251563de0.jpg  7c21749eb23b984a2409.jpg   \n",
       "4   68618c07e20b3374a091.jpg  703665b9363046d63afa.jpg   \n",
       "5   e3f360d8e0cde2ca0358.jpg  63ee5e5a2d06717c38e0.jpg   \n",
       "6   ae3d28a80715cf1b1569.jpg  07953dd23748ae646b99.jpg   \n",
       "7   3a57a942517193679bee.jpg  773f1eb4454dbf145191.jpg   \n",
       "8   eacdf81c60a00eaee2d5.jpg  ca9f83b218482af402dc.jpg   \n",
       "9   02bf8c21a66b2e14fd2c.jpg  467acc9c954a5f23732a.jpg   \n",
       "10  60484a12700fd4e28862.jpg  8aeef96d6a4331b41fe7.jpg   \n",
       "11  3218c3582e825e5ec4f3.jpg  876efeac71732801e589.jpg   \n",
       "12  e26fed0bd68205101f95.jpg  97119b43b61c1d122c92.jpg   \n",
       "\n",
       "                     image_3  \n",
       "0   d2bfc40b87bceda78823.jpg  \n",
       "1   b0fe79b775b77d9f15fb.jpg  \n",
       "2   4537b9a61d8f4013fe9c.jpg  \n",
       "3   45c87ee10d8d3db36728.jpg  \n",
       "4   e19c74bdbb6bbc914094.jpg  \n",
       "5   b8a0f4a34f265be10cb1.jpg  \n",
       "6   48a2396646a1fc3e15fd.jpg  \n",
       "7   166e81379638302ca0c7.jpg  \n",
       "8   cdf609029dff803f5e2d.jpg  \n",
       "9   4380eff72be27cfa66f7.jpg  \n",
       "10  dfb132b6330e3a1d2517.jpg  \n",
       "11  ca915e2ebc1f4e8bbfd8.jpg  \n",
       "12  f29133d4235644b05c78.jpg  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p=pd.read_sql_query(\"SELECT * from addproduct WHERE category_id=\"+str(1), con)\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexingError",
     "evalue": "Too many indexers",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexingError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-71-333d5921512c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'specs'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'object'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'id'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m     \u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'id'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m==\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'specs'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'spec_id'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m     \u001b[1;31m#print(i)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   1416\u001b[0m                 \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1417\u001b[0m                     \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1418\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1419\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1420\u001b[0m             \u001b[1;31m# we by definition only have the 0th axis\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[1;34m(self, tup)\u001b[0m\n\u001b[0;32m    808\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    809\u001b[0m         \u001b[1;31m# no multi-index, so validate all of the indexers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 810\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_valid_tuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    811\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    812\u001b[0m         \u001b[1;31m# ugly hack for GH #836\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    231\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mk\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    232\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mi\u001b[0m \u001b[1;33m>=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 233\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Too many indexers\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    234\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    235\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexingError\u001b[0m: Too many indexers"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "p['specs']=np.zeros(len(p))\n",
    "p['specs'].astype('object')\n",
    "for i in p['id']:\n",
    "    p.loc[p['id']==i,'specs']=s.loc[i,'spec_id']\n",
    "    #print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.loc[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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