Shack_lab_assignment_2.ipynb

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  "metadata": {
    "colab": {
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      "mount_file_id": "1Ntg5IMrEsm1K_4pSYhVdBUBKAWryKJdw",
      "authorship_tag": "ABX9TyPmLdlq9k9+ppHwDmBrkIb8",
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      "name": "python3",
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    "language_info": {
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/chandrakar-shubham/Shacklabs_job_assignment-Regression-model-and-Similar-texts-/blob/main/Shack_lab_assignment_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Assigment 2 ---> Shack labs\n",
        "\n",
        "Given two csv file contains amazon data and flipkart data respectively.\n",
        "\n",
        "Objective: To create new dataframe containing similar product of flipkart and amazon with information of selling price in that platform and discounted price in that platform."
      ],
      "metadata": {
        "id": "M6xK560cGG_V"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Data dictionary\n",
        "\n",
        "df1 = dataframe made from amazon data\n",
        "\n",
        "df2 = dataframe made from flipkart data\n",
        "\n"
      ],
      "metadata": {
        "id": "YKWgvObHF0H2"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "id": "JxEc9usaLhiC"
      },
      "outputs": [],
      "source": [
        "#importing basic libraries\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#importing sentence transformer , cosine similarity from torch ilbrary\n",
        "\n",
        "from sentence_transformers import SentenceTransformer, util\n",
        "import torch\n",
        "from torch.nn.functional import cosine_similarity"
      ],
      "metadata": {
        "id": "erelDPVUdtjn"
      },
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from torch.nn.functional import cosine_similarity\n",
        "#similar_prod_indexes = []\n",
        "\n",
        "def similar_products(model_name,data1,data2,path_to_export):\n",
        "\n",
        "\n",
        "  '''take model, two dataframe and path to export as input,\n",
        "  return final database based on similarity,\n",
        "  and export data to a location'''\n",
        "\n",
        "\n",
        "  def embedded_model(model_name,data1,data2):\n",
        "    '''create model of sentence transformer, take input as two dataframe and return cosine similarity'''\n",
        "    # Creating a model of sentence transformer class\n",
        "    model = SentenceTransformer('all-MiniLM-L6-v2')\n",
        "    \n",
        "    # Computing embedding for both amazon and flipkart product \n",
        "    df1_embedding = model.encode(data1.product_name,convert_to_tensor=True)                      #.to_numpy()\n",
        "    df2_embedding = model.encode(data2.product_name,convert_to_tensor=True)\n",
        "\n",
        "    # Computing cosine similarities\n",
        "    cosine_sim_scores = util.cos_sim(df1_embedding,df2_embedding)\n",
        "\n",
        "    return cosine_sim_scores\n",
        "\n",
        "\n",
        "  def store_similar_prod_index(cosine_sim_scores,df1,df2):\n",
        "    '''input tensor of cosine scores, two data frame and store index of similar products'''\n",
        "    \n",
        "    length = len(df1)\n",
        "    \n",
        "    if len(df1) > len(df2):\n",
        "      length =len(df2)\n",
        "    else:\n",
        "      length = len(df1)\n",
        "\n",
        "    # Storing the index of a similar Flipkart product corresponding to each Amazon product \n",
        "    similar_prod_indexes = []\n",
        "    \n",
        "    for i in range(length):\n",
        "      max_score_idxs = torch.topk(cosine_sim_scores[i],k=5,largest=True,sorted=True).indices\n",
        "      for idx in max_score_idxs:\n",
        "        if idx != i:\n",
        "          similar_prod_indexes.append(idx)\n",
        "          break\n",
        "    return similar_prod_indexes\n",
        "  \n",
        "  \n",
        "  def create_sim_list(similar_prod_indexes):\n",
        "    \n",
        "    '''create list of similar product index'''\n",
        "\n",
        "    #similar_prod_indexes = [x.item() for x in similar_prod_indexes]\n",
        "    sim_index = [x.item() for x in similar_prod_indexes]\n",
        "    \n",
        "    return sim_index\n",
        "\n",
        "  \n",
        "  def extract_similar_data(similar_prod_indexes,data1,data2):\n",
        "\n",
        "    '''input two dataframe and list of similar product index and extract details from dataframe'''\n",
        "    \n",
        "    # Extracting the details such as retail price and discounted price for both Flipkart and Amazon similar products\n",
        "    flipkart_prod_data = []\n",
        "    amazon_prod_data = []\n",
        "    \n",
        "    for idx, prod_name in enumerate(df2.product_name):\n",
        "      flipkart_prod_data.append(df2.iloc[similar_prod_indexes[idx]])\n",
        "      amazon_prod_data.append(df1.iloc[idx])\n",
        "      #print(idx,prod_name)\n",
        "\n",
        "    return amazon_prod_data, flipkart_prod_data\n",
        "\n",
        "  def create_dataframe(amazon_prod_data, flipkart_prod_data):\n",
        "\n",
        "    '''create dataframe two dataframe by on basis of similarity to data'''\n",
        "    \n",
        "    flipkart_prod_data = pd.DataFrame(flipkart_prod_data)\n",
        "    flipkart_prod_data.columns = ['Product name in Flipkart','Retail Price in Flipkart','Discounted Price in Flipkart']\n",
        "    \n",
        "    amazon_prod_data = pd.DataFrame(amazon_prod_data)\n",
        "    amazon_prod_data.columns = ['Product name in Amazon','Retail Price in Amazon','Discounted Price in Amazon']\n",
        "\n",
        "    amazon_prod_data['Retail Price in Amazon'] = amazon_prod_data['Retail Price in Amazon'].astype(np.float64)\n",
        "    amazon_prod_data['Discounted Price in Amazon'] = amazon_prod_data['Discounted Price in Amazon'].astype(np.float64)\n",
        "\n",
        "    flipkart_prod_final_data = flipkart_prod_data.copy()\n",
        "    flipkart_prod_final_data = flipkart_prod_final_data.reset_index(drop=True)\n",
        "    flipkart_prod_final_data.head()\n",
        "\n",
        "    return amazon_prod_data,flipkart_prod_final_data\n",
        "\n",
        "\n",
        "\n",
        "  def export_data_csv(path_to_export,amazon_prod_data,flipkart_prod_final_data):\n",
        "\n",
        "    '''create final database and export data in form of csv'''\n",
        "    \n",
        "    final_prod_data = pd.concat([flipkart_prod_final_data,amazon_prod_data],axis=1)\n",
        "    final_prod_data.to_csv(path_to_export + 'final_result.csv')\n",
        "\n",
        "    return final_prod_data\n",
        "\n",
        "  cosine_scores = embedded_model(model_name,data1,data2)\n",
        "\n",
        "  similar_pro_index = store_similar_prod_index(cosine_scores,data1,data2)\n",
        "\n",
        "  similar_prod_indexes = create_sim_list(similar_pro_index)\n",
        "\n",
        "  amazon_data,flip_data = extract_similar_data(similar_prod_indexes,data1,data2)\n",
        "\n",
        "  amazon_df,flip_df = create_dataframe(amazon_data, flip_data)\n",
        "\n",
        "  final_df = export_data_csv(path_to_export,amazon_df,flip_df)\n",
        "\n",
        "  return final_df"
      ],
      "metadata": {
        "id": "CRtplzeVC96U"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#installing sentence transformer library\n",
        "\n",
        "!pip install sentence_transformers"
      ],
      "metadata": {
        "id": "7WLqRqh1de1o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f1afdebf-4914-4761-c993-32ffa22b4d03"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: sentence_transformers in /usr/local/lib/python3.7/dist-packages (2.2.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from sentence_transformers) (1.21.6)\n",
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            "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.7/dist-packages (from transformers<5.0.0,>=4.6.0->sentence_transformers) (0.13.2)\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# path of the file\n",
        "\n",
        "path_amzon = '/content/drive/MyDrive/Internship and job assignment/Shack labs/assignment 2 data/amz_com-ecommerce_sample.csv'\n",
        "path_flip= '/content/drive/MyDrive/Internship and job assignment/Shack labs/assignment 2 data/flipkart_com-ecommerce_sample.csv'\n",
        "\n",
        "#importing dataset in pandas\n",
        "\n",
        "df1 =  pd.read_csv(path_amzon,encoding = 'ISO-8859-1')\n",
        "df2 = pd.read_csv(path_flip,encoding = 'ISO-8859-1')"
      ],
      "metadata": {
        "id": "b21Pk_RDL-V6"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Data Wrangling"
      ],
      "metadata": {
        "id": "hBu5LNfqG8eT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Top 5 rows in amazon dataframe\n",
        "\n",
        "df1.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 531
        },
        "id": "JNZTxVpNMixy",
        "outputId": "42f036b2-a750-43ca-ec32-8276c051bc27"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            uniq_id            crawl_timestamp  \\\n",
              "0  c2d766ca982eca8304150849735ffef9  2016-03-25 22:59:23 +0000   \n",
              "1  7f7036a6d550aaa89d34c77bd39a5e48  2016-03-25 22:59:23 +0000   \n",
              "2  f449ec65dcbc041b6ae5e6a32717d01b  2016-03-25 22:59:23 +0000   \n",
              "3  0973b37acd0c664e3de26e97e5571454  2016-03-25 22:59:23 +0000   \n",
              "4  bc940ea42ee6bef5ac7cea3fb5cfbee7  2016-03-25 22:59:23 +0000   \n",
              "\n",
              "                                         product_url  \\\n",
              "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
              "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
              "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
              "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
              "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
              "\n",
              "                            product_name  \\\n",
              "0    Alisha Solid Women's Cycling Shorts   \n",
              "1    FabHomeDecor Fabric Double Sofa Bed   \n",
              "2                             AW Bellies   \n",
              "3    Alisha Solid Women's Cycling Shorts   \n",
              "4  Sicons All Purpose Arnica Dog Shampoo   \n",
              "\n",
              "                               product_category_tree               pid  \\\n",
              "0  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2FF9KEDEFGF   \n",
              "1  [\"Furniture >> Living Room Furniture >> Sofa B...  SBEEH3QGU7MFYJFY   \n",
              "2  [\"Footwear >> Women's Footwear >> Ballerinas >...  SHOEH4GRSUBJGZXE   \n",
              "3  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2F6HUZMQ6SJ   \n",
              "4  [\"Pet Supplies >> Grooming >> Skin & Coat Care...  PSOEH3ZYDMSYARJ5   \n",
              "\n",
              "   retail_price  discounted_price  \\\n",
              "0           982               438   \n",
              "1         32143             29121   \n",
              "2           991               551   \n",
              "3           694               325   \n",
              "4           208               258   \n",
              "\n",
              "                                               image  is_FK_Advantage_product  \\\n",
              "0  [\"http://img5a.flixcart.com/image/short/u/4/a/...                    False   \n",
              "1  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...                    False   \n",
              "2  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...                    False   \n",
              "3  [\"http://img5a.flixcart.com/image/short/6/2/h/...                    False   \n",
              "4  [\"http://img5a.flixcart.com/image/pet-shampoo/...                    False   \n",
              "\n",
              "                                         description       product_rating  \\\n",
              "0  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
              "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  No rating available   \n",
              "2  Key Features of AW Bellies Sandals Wedges Heel...  No rating available   \n",
              "3  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
              "4  Specifications of Sicons All Purpose Arnica Do...  No rating available   \n",
              "\n",
              "        overall_rating         brand  \\\n",
              "0  No rating available        Alisha   \n",
              "1  No rating available  FabHomeDecor   \n",
              "2  No rating available            AW   \n",
              "3  No rating available        Alisha   \n",
              "4  No rating available        Sicons   \n",
              "\n",
              "                              product_specifications  \n",
              "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  \n",
              "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  \n",
              "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  "
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              "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
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              "      <td>False</td>\n",
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              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
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              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
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              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
              "      <td>[\"Furniture &gt;&gt; Living Room Furniture &gt;&gt; Sofa B...</td>\n",
              "      <td>SBEEH3QGU7MFYJFY</td>\n",
              "      <td>32143</td>\n",
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              "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
              "      <td>False</td>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>FabHomeDecor</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
              "      <td>AW Bellies</td>\n",
              "      <td>[\"Footwear &gt;&gt; Women's Footwear &gt;&gt; Ballerinas &gt;...</td>\n",
              "      <td>SHOEH4GRSUBJGZXE</td>\n",
              "      <td>991</td>\n",
              "      <td>551</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
              "      <td>False</td>\n",
              "      <td>Key Features of AW Bellies Sandals Wedges Heel...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>AW</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
              "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
              "      <td>694</td>\n",
              "      <td>325</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Alisha</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
              "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
              "      <td>[\"Pet Supplies &gt;&gt; Grooming &gt;&gt; Skin &amp; Coat Care...</td>\n",
              "      <td>PSOEH3ZYDMSYARJ5</td>\n",
              "      <td>208</td>\n",
              "      <td>258</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Specifications of Sicons All Purpose Arnica Do...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Sicons</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8c61817f-0e78-45e8-b929-98c966761c90')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8c61817f-0e78-45e8-b929-98c966761c90 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8c61817f-0e78-45e8-b929-98c966761c90');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Bottom 5 row in amazon df    \n",
        "\n",
        "df1.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "8fhbjBRvMofJ",
        "outputId": "68364848-b275-4964-ce9a-eafb74cf9186"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                uniq_id            crawl_timestamp  \\\n",
              "19995  7179d2f6c4ad50a17d014ca1d2815156  2015-12-01 10:15:43 +0000   \n",
              "19996  71ac419198359d37b8fe5e3fffdfee09  2015-12-01 10:15:43 +0000   \n",
              "19997  93e9d343837400ce0d7980874ece471c  2015-12-01 10:15:43 +0000   \n",
              "19998  669e79b8fa5d9ae020841c0c97d5e935  2015-12-01 10:15:43 +0000   \n",
              "19999  cb4fa87a874f715fff567f7b7b3be79c  2015-12-01 10:15:43 +0000   \n",
              "\n",
              "                                             product_url  \\\n",
              "19995  http://www.flipkart.com/walldesign-small-vinyl...   \n",
              "19996  http://www.flipkart.com/wallmantra-large-vinyl...   \n",
              "19997  http://www.flipkart.com/elite-collection-mediu...   \n",
              "19998  http://www.flipkart.com/elite-collection-mediu...   \n",
              "19999  http://www.flipkart.com/elite-collection-mediu...   \n",
              "\n",
              "                                  product_name  \\\n",
              "19995           WALLDESIGN SMALL VINYL STICKER   \n",
              "19996  WALLMANTRA LARGE VINYL STICKERS STICKER   \n",
              "19997  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19998  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19999  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "\n",
              "                                   product_category_tree               pid  \\\n",
              "19995  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE7KFJAKSTDY9G   \n",
              "19996  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE9F5URNQGJCGH   \n",
              "19997  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE7VAYDKQZEBSD   \n",
              "19998  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE8YSVEPPCZ42Y   \n",
              "19999  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE88KN9ZDSGZKY   \n",
              "\n",
              "       retail_price  discounted_price  \\\n",
              "19995          1498               876   \n",
              "19996          1415              1424   \n",
              "19997          1284              1196   \n",
              "19998          1492              1364   \n",
              "19999          1484              1247   \n",
              "\n",
              "                                                   image  \\\n",
              "19995  [\"http://img6a.flixcart.com/image/wall-decorat...   \n",
              "19996  [\"http://img6a.flixcart.com/image/sticker/z/g/...   \n",
              "19997  [\"http://img5a.flixcart.com/image/sticker/b/s/...   \n",
              "19998  [\"http://img5a.flixcart.com/image/sticker/4/2/...   \n",
              "19999  [\"http://img6a.flixcart.com/image/sticker/z/k/...   \n",
              "\n",
              "       is_FK_Advantage_product  \\\n",
              "19995                    False   \n",
              "19996                    False   \n",
              "19997                    False   \n",
              "19998                    False   \n",
              "19999                    False   \n",
              "\n",
              "                                             description       product_rating  \\\n",
              "19995  Buy WallDesign Small Vinyl Sticker for Rs.730 ...  No rating available   \n",
              "19996  Buy Wallmantra Large Vinyl Stickers Sticker fo...  No rating available   \n",
              "19997  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
              "19998  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
              "19999  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
              "\n",
              "            overall_rating             brand  \\\n",
              "19995  No rating available        WallDesign   \n",
              "19996  No rating available        Wallmantra   \n",
              "19997  No rating available  Elite Collection   \n",
              "19998  No rating available  Elite Collection   \n",
              "19999  No rating available  Elite Collection   \n",
              "\n",
              "                                  product_specifications  \n",
              "19995  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19996  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19997  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19998  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19999  {\"product_specification\"=>[{\"key\"=>\"Number of ...  "
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              "      <td>http://www.flipkart.com/walldesign-small-vinyl...</td>\n",
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              "      <td>2015-12-01 10:15:43 +0000</td>\n",
              "      <td>http://www.flipkart.com/wallmantra-large-vinyl...</td>\n",
              "      <td>WALLMANTRA LARGE VINYL STICKERS STICKER</td>\n",
              "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
              "      <td>STIE9F5URNQGJCGH</td>\n",
              "      <td>1415</td>\n",
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              "      <td>http://www.flipkart.com/elite-collection-mediu...</td>\n",
              "      <td>ELITE COLLECTION MEDIUM ACRYLIC STICKER</td>\n",
              "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
              "      <td>STIE7VAYDKQZEBSD</td>\n",
              "      <td>1284</td>\n",
              "      <td>1196</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/sticker/b/s/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
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              "      <td>ELITE COLLECTION MEDIUM ACRYLIC STICKER</td>\n",
              "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
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              "      <td>False</td>\n",
              "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Elite Collection</td>\n",
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              "      <td>ELITE COLLECTION MEDIUM ACRYLIC STICKER</td>\n",
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              "      <td>STIE88KN9ZDSGZKY</td>\n",
              "      <td>1484</td>\n",
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              "      <td>Elite Collection</td>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "    }\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4f4ed5ee-5f02-4221-b995-644ffb9c3542');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#checking info in amazon dataframe\n",
        "\n",
        "df1.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lSufAHcyOgTx",
        "outputId": "d7d9c39b-2513-4d16-9e67-804c533b1946"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20000 entries, 0 to 19999\n",
            "Data columns (total 15 columns):\n",
            " #   Column                   Non-Null Count  Dtype \n",
            "---  ------                   --------------  ----- \n",
            " 0   uniq_id                  20000 non-null  object\n",
            " 1   crawl_timestamp          20000 non-null  object\n",
            " 2   product_url              20000 non-null  object\n",
            " 3   product_name             20000 non-null  object\n",
            " 4   product_category_tree    20000 non-null  object\n",
            " 5   pid                      20000 non-null  object\n",
            " 6   retail_price             20000 non-null  int64 \n",
            " 7   discounted_price         20000 non-null  int64 \n",
            " 8   image                    19997 non-null  object\n",
            " 9   is_FK_Advantage_product  20000 non-null  bool  \n",
            " 10  description              19998 non-null  object\n",
            " 11  product_rating           20000 non-null  object\n",
            " 12  overall_rating           20000 non-null  object\n",
            " 13  brand                    14136 non-null  object\n",
            " 14  product_specifications   19986 non-null  object\n",
            "dtypes: bool(1), int64(2), object(12)\n",
            "memory usage: 2.2+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Top 5 row in flipkart dataframe\n",
        "\n",
        "df2.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 531
        },
        "id": "T6kzTuw4M1Io",
        "outputId": "e03ebdb4-09b3-4457-db6a-ae32dae15071"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            uniq_id            crawl_timestamp  \\\n",
              "0  c2d766ca982eca8304150849735ffef9  2016-03-25 22:59:23 +0000   \n",
              "1  7f7036a6d550aaa89d34c77bd39a5e48  2016-03-25 22:59:23 +0000   \n",
              "2  f449ec65dcbc041b6ae5e6a32717d01b  2016-03-25 22:59:23 +0000   \n",
              "3  0973b37acd0c664e3de26e97e5571454  2016-03-25 22:59:23 +0000   \n",
              "4  bc940ea42ee6bef5ac7cea3fb5cfbee7  2016-03-25 22:59:23 +0000   \n",
              "\n",
              "                                         product_url  \\\n",
              "0  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
              "1  http://www.flipkart.com/fabhomedecor-fabric-do...   \n",
              "2  http://www.flipkart.com/aw-bellies/p/itmeh4grg...   \n",
              "3  http://www.flipkart.com/alisha-solid-women-s-c...   \n",
              "4  http://www.flipkart.com/sicons-all-purpose-arn...   \n",
              "\n",
              "                            product_name  \\\n",
              "0    Alisha Solid Women's Cycling Shorts   \n",
              "1    FabHomeDecor Fabric Double Sofa Bed   \n",
              "2                             AW Bellies   \n",
              "3    Alisha Solid Women's Cycling Shorts   \n",
              "4  Sicons All Purpose Arnica Dog Shampoo   \n",
              "\n",
              "                               product_category_tree               pid  \\\n",
              "0  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2FF9KEDEFGF   \n",
              "1  [\"Furniture >> Living Room Furniture >> Sofa B...  SBEEH3QGU7MFYJFY   \n",
              "2  [\"Footwear >> Women's Footwear >> Ballerinas >...  SHOEH4GRSUBJGZXE   \n",
              "3  [\"Clothing >> Women's Clothing >> Lingerie, Sl...  SRTEH2F6HUZMQ6SJ   \n",
              "4  [\"Pet Supplies >> Grooming >> Skin & Coat Care...  PSOEH3ZYDMSYARJ5   \n",
              "\n",
              "   retail_price  discounted_price  \\\n",
              "0         999.0             379.0   \n",
              "1       32157.0           22646.0   \n",
              "2         999.0             499.0   \n",
              "3         699.0             267.0   \n",
              "4         220.0             210.0   \n",
              "\n",
              "                                               image  is_FK_Advantage_product  \\\n",
              "0  [\"http://img5a.flixcart.com/image/short/u/4/a/...                    False   \n",
              "1  [\"http://img6a.flixcart.com/image/sofa-bed/j/f...                    False   \n",
              "2  [\"http://img5a.flixcart.com/image/shoe/7/z/z/r...                    False   \n",
              "3  [\"http://img5a.flixcart.com/image/short/6/2/h/...                    False   \n",
              "4  [\"http://img5a.flixcart.com/image/pet-shampoo/...                    False   \n",
              "\n",
              "                                         description       product_rating  \\\n",
              "0  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
              "1  FabHomeDecor Fabric Double Sofa Bed (Finish Co...  No rating available   \n",
              "2  Key Features of AW Bellies Sandals Wedges Heel...  No rating available   \n",
              "3  Key Features of Alisha Solid Women's Cycling S...  No rating available   \n",
              "4  Specifications of Sicons All Purpose Arnica Do...  No rating available   \n",
              "\n",
              "        overall_rating         brand  \\\n",
              "0  No rating available        Alisha   \n",
              "1  No rating available  FabHomeDecor   \n",
              "2  No rating available            AW   \n",
              "3  No rating available        Alisha   \n",
              "4  No rating available        Sicons   \n",
              "\n",
              "                              product_specifications  \n",
              "0  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "1  {\"product_specification\"=>[{\"key\"=>\"Installati...  \n",
              "2  {\"product_specification\"=>[{\"key\"=>\"Ideal For\"...  \n",
              "3  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "4  {\"product_specification\"=>[{\"key\"=>\"Pet Type\",...  "
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>uniq_id</th>\n",
              "      <th>crawl_timestamp</th>\n",
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              "      <th>product_name</th>\n",
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              "      <th>discounted_price</th>\n",
              "      <th>image</th>\n",
              "      <th>is_FK_Advantage_product</th>\n",
              "      <th>description</th>\n",
              "      <th>product_rating</th>\n",
              "      <th>overall_rating</th>\n",
              "      <th>brand</th>\n",
              "      <th>product_specifications</th>\n",
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              "      <th>0</th>\n",
              "      <td>c2d766ca982eca8304150849735ffef9</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
              "      <td>SRTEH2FF9KEDEFGF</td>\n",
              "      <td>999.0</td>\n",
              "      <td>379.0</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/short/u/4/a/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Alisha</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>7f7036a6d550aaa89d34c77bd39a5e48</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/fabhomedecor-fabric-do...</td>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
              "      <td>[\"Furniture &gt;&gt; Living Room Furniture &gt;&gt; Sofa B...</td>\n",
              "      <td>SBEEH3QGU7MFYJFY</td>\n",
              "      <td>32157.0</td>\n",
              "      <td>22646.0</td>\n",
              "      <td>[\"http://img6a.flixcart.com/image/sofa-bed/j/f...</td>\n",
              "      <td>False</td>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed (Finish Co...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>FabHomeDecor</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Installati...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>f449ec65dcbc041b6ae5e6a32717d01b</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/aw-bellies/p/itmeh4grg...</td>\n",
              "      <td>AW Bellies</td>\n",
              "      <td>[\"Footwear &gt;&gt; Women's Footwear &gt;&gt; Ballerinas &gt;...</td>\n",
              "      <td>SHOEH4GRSUBJGZXE</td>\n",
              "      <td>999.0</td>\n",
              "      <td>499.0</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/shoe/7/z/z/r...</td>\n",
              "      <td>False</td>\n",
              "      <td>Key Features of AW Bellies Sandals Wedges Heel...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>AW</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0973b37acd0c664e3de26e97e5571454</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/alisha-solid-women-s-c...</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>[\"Clothing &gt;&gt; Women's Clothing &gt;&gt; Lingerie, Sl...</td>\n",
              "      <td>SRTEH2F6HUZMQ6SJ</td>\n",
              "      <td>699.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/short/6/2/h/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Key Features of Alisha Solid Women's Cycling S...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Alisha</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>bc940ea42ee6bef5ac7cea3fb5cfbee7</td>\n",
              "      <td>2016-03-25 22:59:23 +0000</td>\n",
              "      <td>http://www.flipkart.com/sicons-all-purpose-arn...</td>\n",
              "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
              "      <td>[\"Pet Supplies &gt;&gt; Grooming &gt;&gt; Skin &amp; Coat Care...</td>\n",
              "      <td>PSOEH3ZYDMSYARJ5</td>\n",
              "      <td>220.0</td>\n",
              "      <td>210.0</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/pet-shampoo/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Specifications of Sicons All Purpose Arnica Do...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Sicons</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pet Type\",...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-22d38a1e-9e23-4360-bbc0-4ab9c436c8a5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-22d38a1e-9e23-4360-bbc0-4ab9c436c8a5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#bottom 5 rows in filpkart dataframe\n",
        "\n",
        "df2.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "vlqyr8qpM2Xo",
        "outputId": "a691d9d9-0a51-4a46-aadf-1576cd8a2a75"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                uniq_id            crawl_timestamp  \\\n",
              "19995  7179d2f6c4ad50a17d014ca1d2815156  2015-12-01 10:15:43 +0000   \n",
              "19996  71ac419198359d37b8fe5e3fffdfee09  2015-12-01 10:15:43 +0000   \n",
              "19997  93e9d343837400ce0d7980874ece471c  2015-12-01 10:15:43 +0000   \n",
              "19998  669e79b8fa5d9ae020841c0c97d5e935  2015-12-01 10:15:43 +0000   \n",
              "19999  cb4fa87a874f715fff567f7b7b3be79c  2015-12-01 10:15:43 +0000   \n",
              "\n",
              "                                             product_url  \\\n",
              "19995  http://www.flipkart.com/walldesign-small-vinyl...   \n",
              "19996  http://www.flipkart.com/wallmantra-large-vinyl...   \n",
              "19997  http://www.flipkart.com/elite-collection-mediu...   \n",
              "19998  http://www.flipkart.com/elite-collection-mediu...   \n",
              "19999  http://www.flipkart.com/elite-collection-mediu...   \n",
              "\n",
              "                                  product_name  \\\n",
              "19995           WallDesign Small Vinyl Sticker   \n",
              "19996  Wallmantra Large Vinyl Stickers Sticker   \n",
              "19997  Elite Collection Medium Acrylic Sticker   \n",
              "19998  Elite Collection Medium Acrylic Sticker   \n",
              "19999  Elite Collection Medium Acrylic Sticker   \n",
              "\n",
              "                                   product_category_tree               pid  \\\n",
              "19995  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE7KFJAKSTDY9G   \n",
              "19996  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE9F5URNQGJCGH   \n",
              "19997  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE7VAYDKQZEBSD   \n",
              "19998  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE8YSVEPPCZ42Y   \n",
              "19999  [\"Baby Care >> Baby & Kids Gifts >> Stickers >...  STIE88KN9ZDSGZKY   \n",
              "\n",
              "       retail_price  discounted_price  \\\n",
              "19995        1500.0             730.0   \n",
              "19996        1429.0            1143.0   \n",
              "19997        1299.0             999.0   \n",
              "19998        1499.0            1199.0   \n",
              "19999        1499.0             999.0   \n",
              "\n",
              "                                                   image  \\\n",
              "19995  [\"http://img6a.flixcart.com/image/wall-decorat...   \n",
              "19996  [\"http://img6a.flixcart.com/image/sticker/z/g/...   \n",
              "19997  [\"http://img5a.flixcart.com/image/sticker/b/s/...   \n",
              "19998  [\"http://img5a.flixcart.com/image/sticker/4/2/...   \n",
              "19999  [\"http://img6a.flixcart.com/image/sticker/z/k/...   \n",
              "\n",
              "       is_FK_Advantage_product  \\\n",
              "19995                    False   \n",
              "19996                    False   \n",
              "19997                    False   \n",
              "19998                    False   \n",
              "19999                    False   \n",
              "\n",
              "                                             description       product_rating  \\\n",
              "19995  Buy WallDesign Small Vinyl Sticker for Rs.730 ...  No rating available   \n",
              "19996  Buy Wallmantra Large Vinyl Stickers Sticker fo...  No rating available   \n",
              "19997  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
              "19998  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
              "19999  Buy Elite Collection Medium Acrylic Sticker fo...  No rating available   \n",
              "\n",
              "            overall_rating             brand  \\\n",
              "19995  No rating available        WallDesign   \n",
              "19996  No rating available        Wallmantra   \n",
              "19997  No rating available  Elite Collection   \n",
              "19998  No rating available  Elite Collection   \n",
              "19999  No rating available  Elite Collection   \n",
              "\n",
              "                                  product_specifications  \n",
              "19995  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19996  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19997  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19998  {\"product_specification\"=>[{\"key\"=>\"Number of ...  \n",
              "19999  {\"product_specification\"=>[{\"key\"=>\"Number of ...  "
            ],
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              "      <th>19995</th>\n",
              "      <td>7179d2f6c4ad50a17d014ca1d2815156</td>\n",
              "      <td>2015-12-01 10:15:43 +0000</td>\n",
              "      <td>http://www.flipkart.com/walldesign-small-vinyl...</td>\n",
              "      <td>WallDesign Small Vinyl Sticker</td>\n",
              "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
              "      <td>STIE7KFJAKSTDY9G</td>\n",
              "      <td>1500.0</td>\n",
              "      <td>730.0</td>\n",
              "      <td>[\"http://img6a.flixcart.com/image/wall-decorat...</td>\n",
              "      <td>False</td>\n",
              "      <td>Buy WallDesign Small Vinyl Sticker for Rs.730 ...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>WallDesign</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
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              "      <th>19996</th>\n",
              "      <td>71ac419198359d37b8fe5e3fffdfee09</td>\n",
              "      <td>2015-12-01 10:15:43 +0000</td>\n",
              "      <td>http://www.flipkart.com/wallmantra-large-vinyl...</td>\n",
              "      <td>Wallmantra Large Vinyl Stickers Sticker</td>\n",
              "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
              "      <td>STIE9F5URNQGJCGH</td>\n",
              "      <td>1429.0</td>\n",
              "      <td>1143.0</td>\n",
              "      <td>[\"http://img6a.flixcart.com/image/sticker/z/g/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Buy Wallmantra Large Vinyl Stickers Sticker fo...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Wallmantra</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
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              "    <tr>\n",
              "      <th>19997</th>\n",
              "      <td>93e9d343837400ce0d7980874ece471c</td>\n",
              "      <td>2015-12-01 10:15:43 +0000</td>\n",
              "      <td>http://www.flipkart.com/elite-collection-mediu...</td>\n",
              "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
              "      <td>[\"Baby Care &gt;&gt; Baby &amp; Kids Gifts &gt;&gt; Stickers &gt;...</td>\n",
              "      <td>STIE7VAYDKQZEBSD</td>\n",
              "      <td>1299.0</td>\n",
              "      <td>999.0</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/sticker/b/s/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Elite Collection</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
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              "      <td>STIE8YSVEPPCZ42Y</td>\n",
              "      <td>1499.0</td>\n",
              "      <td>1199.0</td>\n",
              "      <td>[\"http://img5a.flixcart.com/image/sticker/4/2/...</td>\n",
              "      <td>False</td>\n",
              "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>Elite Collection</td>\n",
              "      <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
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              "      <th>19999</th>\n",
              "      <td>cb4fa87a874f715fff567f7b7b3be79c</td>\n",
              "      <td>2015-12-01 10:15:43 +0000</td>\n",
              "      <td>http://www.flipkart.com/elite-collection-mediu...</td>\n",
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              "      <td>False</td>\n",
              "      <td>Buy Elite Collection Medium Acrylic Sticker fo...</td>\n",
              "      <td>No rating available</td>\n",
              "      <td>No rating available</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#checking information of flipkart dataframe\n",
        "\n",
        "df2.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LIGxMH5yOoDp",
        "outputId": "0ad9e40a-1352-4705-8c70-0cc1c74d6fea"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20000 entries, 0 to 19999\n",
            "Data columns (total 15 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   uniq_id                  20000 non-null  object \n",
            " 1   crawl_timestamp          20000 non-null  object \n",
            " 2   product_url              20000 non-null  object \n",
            " 3   product_name             20000 non-null  object \n",
            " 4   product_category_tree    20000 non-null  object \n",
            " 5   pid                      20000 non-null  object \n",
            " 6   retail_price             19922 non-null  float64\n",
            " 7   discounted_price         19922 non-null  float64\n",
            " 8   image                    19997 non-null  object \n",
            " 9   is_FK_Advantage_product  20000 non-null  bool   \n",
            " 10  description              19998 non-null  object \n",
            " 11  product_rating           20000 non-null  object \n",
            " 12  overall_rating           20000 non-null  object \n",
            " 13  brand                    14136 non-null  object \n",
            " 14  product_specifications   19986 non-null  object \n",
            "dtypes: bool(1), float64(2), object(12)\n",
            "memory usage: 2.2+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Keeping only relevant columns"
      ],
      "metadata": {
        "id": "_5N2KCGhfv-0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# retain only relevant information\n",
        "\n",
        "to_retain =['product_name','retail_price','discounted_price']\n",
        "df1 = df1[to_retain]\n",
        "df2 = df2[to_retain]"
      ],
      "metadata": {
        "id": "SO432_qbM3T4"
      },
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Check for duplicates"
      ],
      "metadata": {
        "id": "1aFWhw-LfTDU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(df1[df1.duplicated()])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DyILfKPuO5yY",
        "outputId": "ec579e68-f1c4-47a0-b01a-58046b81e2b2"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "17"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df2[df2.duplicated()])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ljEvSjNbPMih",
        "outputId": "62b0006e-220f-4ca4-e93f-8e1d38c01cd5"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4425"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#df1 = df1[~df1.duplicated()]\n",
        "#df2 = df2[~df2.duplicated()]"
      ],
      "metadata": {
        "id": "BZLoQgADPe7i"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Check for null values"
      ],
      "metadata": {
        "id": "n1RUW8HKfbTz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df1.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8bCtM9LGR1xp",
        "outputId": "87e490e8-3f98-4e81-f8b7-df868c4118ef"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_name        0\n",
              "retail_price        0\n",
              "discounted_price    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "er12PwcOR5Vv",
        "outputId": "e2506101-3c6c-43e3-f502-0af3d6145ca3"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_name         0\n",
              "retail_price        78\n",
              "discounted_price    78\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.fillna(0,inplace=True)"
      ],
      "metadata": {
        "id": "eKW7MaceR8b4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bbb92613-f719-4f33-940d-d5032efd6242"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/frame.py:5182: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  downcast=downcast,\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kGXVEmzQdPpg",
        "outputId": "2ec669aa-8ecd-4435-e10d-5d7f96dd6c8f"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20000, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2ZU4zWFRdS24",
        "outputId": "94f12a14-bb39-4802-800e-f963f35b012e"
      },
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20000, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#df1['pn1']=df1['product_name'].str.lower()\n",
        "#df2['pn2']=df2['product_name'].str.lower()"
      ],
      "metadata": {
        "id": "8VRId6NIqns8"
      },
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df1.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "XtaQFGmRqVic",
        "outputId": "fd08f60d-7646-4a21-fe88-322fb8f31c4f"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            product_name  retail_price  discounted_price\n",
              "0    Alisha Solid Women's Cycling Shorts           982               438\n",
              "1    FabHomeDecor Fabric Double Sofa Bed         32143             29121\n",
              "2                             AW Bellies           991               551\n",
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              "                            product_name  retail_price  discounted_price\n",
              "0    Alisha Solid Women's Cycling Shorts         999.0             379.0\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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    {
      "cell_type": "code",
      "source": [
        "df1.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hcW8Gg5FdcW_",
        "outputId": "479f4149-b149-4039-bf7c-7222ebce9760"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20000, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sxziMcbLddeo",
        "outputId": "78f3d4c4-1b25-4f55-9116-78861f674d01"
      },
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20000, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Sentence transformation"
      ],
      "metadata": {
        "id": "QkkCiU-YdqUf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#name of the model used for sentence transformation\n",
        "model_name = SentenceTransformer('all-MiniLM-L6-v2')\n",
        "\n",
        "#amazon data after data wrangling as data1\n",
        "data1 = df1\n",
        "\n",
        "#flipkart data after data wrangling as data2\n",
        "data2 = df2\n",
        "\n",
        "#path where final csv file is to be exported\n",
        "path_to_export ='/content/drive/MyDrive/Internship and job assignment/Shack labs/'\n",
        "\n"
      ],
      "metadata": {
        "id": "23jtPHMjImSL"
      },
      "execution_count": 78,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#create and export final dataframe by using sentence transformer model\n",
        "\n",
        "#calling similar products function\n",
        "final_df = similar_products(model_name,data1,data2,path_to_export)\n",
        "\n",
        "#printing final df\n",
        "final_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 589
        },
        "id": "7jN7vuGcIjeb",
        "outputId": "79adf9a7-e974-4f5d-ebd7-793221ec1d6c"
      },
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                         Product name in Flipkart  Retail Price in Flipkart  \\\n",
              "0             Alisha Solid Women's Cycling Shorts                     699.0   \n",
              "1             FabHomeDecor Fabric Double Sofa Bed                   32157.0   \n",
              "2                                i-Sports Bellies                     899.0   \n",
              "3             Alisha Solid Women's Cycling Shorts                     999.0   \n",
              "4      Sicons Conditioning Conditoner Dog Shampoo                     110.0   \n",
              "...                                           ...                       ...   \n",
              "19995              WallDesign Small Vinyl Sticker                    1220.0   \n",
              "19996     Wallmantra Large Vinyl Stickers Sticker                     727.0   \n",
              "19997     Elite Collection Medium Acrylic Sticker                    1499.0   \n",
              "19998     Elite Collection Medium Acrylic Sticker                    1299.0   \n",
              "19999     Elite Collection Medium Acrylic Sticker                    1499.0   \n",
              "\n",
              "       Discounted Price in Flipkart                   Product name in Amazon  \\\n",
              "0                             267.0      Alisha Solid Women's Cycling Shorts   \n",
              "1                           22646.0      FabHomeDecor Fabric Double Sofa Bed   \n",
              "2                             399.0                               AW Bellies   \n",
              "3                             379.0      Alisha Solid Women's Cycling Shorts   \n",
              "4                             100.0    Sicons All Purpose Arnica Dog Shampoo   \n",
              "...                             ...                                      ...   \n",
              "19995                         600.0           WALLDESIGN SMALL VINYL STICKER   \n",
              "19996                         582.0  WALLMANTRA LARGE VINYL STICKERS STICKER   \n",
              "19997                        1199.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19998                         999.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19999                        1199.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "\n",
              "       Retail Price in Amazon  Discounted Price in Amazon  \n",
              "0                       982.0                       438.0  \n",
              "1                     32143.0                     29121.0  \n",
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              "3                       694.0                       325.0  \n",
              "4                       208.0                       258.0  \n",
              "...                       ...                         ...  \n",
              "19995                  1498.0                       876.0  \n",
              "19996                  1415.0                      1424.0  \n",
              "19997                  1284.0                      1196.0  \n",
              "19998                  1492.0                      1364.0  \n",
              "19999                  1484.0                      1247.0  \n",
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              "[20000 rows x 6 columns]"
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              "      <th>4</th>\n",
              "      <td>Sicons Conditioning Conditoner Dog Shampoo</td>\n",
              "      <td>110.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
              "      <td>208.0</td>\n",
              "      <td>258.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19995</th>\n",
              "      <td>WallDesign Small Vinyl Sticker</td>\n",
              "      <td>1220.0</td>\n",
              "      <td>600.0</td>\n",
              "      <td>WALLDESIGN SMALL VINYL STICKER</td>\n",
              "      <td>1498.0</td>\n",
              "      <td>876.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19996</th>\n",
              "      <td>Wallmantra Large Vinyl Stickers Sticker</td>\n",
              "      <td>727.0</td>\n",
              "      <td>582.0</td>\n",
              "      <td>WALLMANTRA LARGE VINYL STICKERS STICKER</td>\n",
              "      <td>1415.0</td>\n",
              "      <td>1424.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19997</th>\n",
              "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
              "      <td>1499.0</td>\n",
              "      <td>1199.0</td>\n",
              "      <td>ELITE COLLECTION MEDIUM ACRYLIC STICKER</td>\n",
              "      <td>1284.0</td>\n",
              "      <td>1196.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19998</th>\n",
              "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
              "      <td>1299.0</td>\n",
              "      <td>999.0</td>\n",
              "      <td>ELITE COLLECTION MEDIUM ACRYLIC STICKER</td>\n",
              "      <td>1492.0</td>\n",
              "      <td>1364.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19999</th>\n",
              "      <td>Elite Collection Medium Acrylic Sticker</td>\n",
              "      <td>1499.0</td>\n",
              "      <td>1199.0</td>\n",
              "      <td>ELITE COLLECTION MEDIUM ACRYLIC STICKER</td>\n",
              "      <td>1484.0</td>\n",
              "      <td>1247.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20000 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c0a9a2b7-4295-4257-8b7f-556d1c3a0319')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c0a9a2b7-4295-4257-8b7f-556d1c3a0319');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#top 10 rows of final df\n",
        "final_df.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 476
        },
        "id": "da2cz0JJLP78",
        "outputId": "006a034f-bce4-47b5-9ad2-d155c5b88a49"
      },
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            Product name in Flipkart  \\\n",
              "0                Alisha Solid Women's Cycling Shorts   \n",
              "1                FabHomeDecor Fabric Double Sofa Bed   \n",
              "2                                   i-Sports Bellies   \n",
              "3                Alisha Solid Women's Cycling Shorts   \n",
              "4         Sicons Conditioning Conditoner Dog Shampoo   \n",
              "5  Aaishwarya Glim Glam Crystal Crystal Alloy Nec...   \n",
              "6                Alisha Solid Women's Cycling Shorts   \n",
              "7                FabHomeDecor Fabric Double Sofa Bed   \n",
              "8                         Provogue Corporate Casuals   \n",
              "9                Alisha Solid Women's Cycling Shorts   \n",
              "\n",
              "   Retail Price in Flipkart  Discounted Price in Flipkart  \\\n",
              "0                     699.0                         267.0   \n",
              "1                   32157.0                       22646.0   \n",
              "2                     899.0                         399.0   \n",
              "3                     999.0                         379.0   \n",
              "4                     110.0                         100.0   \n",
              "5                    1450.0                         599.0   \n",
              "6                     699.0                         267.0   \n",
              "7                   32157.0                       22646.0   \n",
              "8                    2485.0                        2485.0   \n",
              "9                     699.0                         267.0   \n",
              "\n",
              "                              Product name in Amazon  Retail Price in Amazon  \\\n",
              "0                Alisha Solid Women's Cycling Shorts                   982.0   \n",
              "1                FabHomeDecor Fabric Double Sofa Bed                 32143.0   \n",
              "2                                         AW Bellies                   991.0   \n",
              "3                Alisha Solid Women's Cycling Shorts                   694.0   \n",
              "4              Sicons All Purpose Arnica Dog Shampoo                   208.0   \n",
              "5  Eternal Gandhi Super Series Crystal Paper Weig...                   427.0   \n",
              "6                Alisha Solid Women's Cycling Shorts                  1198.0   \n",
              "7                FabHomeDecor Fabric Double Sofa Bed                 32137.0   \n",
              "8  dilli bazaaar Bellies, Corporate Casuals, Casuals                   682.0   \n",
              "9                Alisha Solid Women's Cycling Shorts                  1197.0   \n",
              "\n",
              "   Discounted Price in Amazon  \n",
              "0                       438.0  \n",
              "1                     29121.0  \n",
              "2                       551.0  \n",
              "3                       325.0  \n",
              "4                       258.0  \n",
              "5                       473.0  \n",
              "6                       602.0  \n",
              "7                     28664.0  \n",
              "8                       385.0  \n",
              "9                       542.0  "
            ],
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              "      <th></th>\n",
              "      <th>Product name in Flipkart</th>\n",
              "      <th>Retail Price in Flipkart</th>\n",
              "      <th>Discounted Price in Flipkart</th>\n",
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              "      <th>Retail Price in Amazon</th>\n",
              "      <th>Discounted Price in Amazon</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>699.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>982.0</td>\n",
              "      <td>438.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
              "      <td>32157.0</td>\n",
              "      <td>22646.0</td>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
              "      <td>32143.0</td>\n",
              "      <td>29121.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>i-Sports Bellies</td>\n",
              "      <td>899.0</td>\n",
              "      <td>399.0</td>\n",
              "      <td>AW Bellies</td>\n",
              "      <td>991.0</td>\n",
              "      <td>551.0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>999.0</td>\n",
              "      <td>379.0</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>694.0</td>\n",
              "      <td>325.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Sicons Conditioning Conditoner Dog Shampoo</td>\n",
              "      <td>110.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>Sicons All Purpose Arnica Dog Shampoo</td>\n",
              "      <td>208.0</td>\n",
              "      <td>258.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Aaishwarya Glim Glam Crystal Crystal Alloy Nec...</td>\n",
              "      <td>1450.0</td>\n",
              "      <td>599.0</td>\n",
              "      <td>Eternal Gandhi Super Series Crystal Paper Weig...</td>\n",
              "      <td>427.0</td>\n",
              "      <td>473.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>699.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>1198.0</td>\n",
              "      <td>602.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
              "      <td>32157.0</td>\n",
              "      <td>22646.0</td>\n",
              "      <td>FabHomeDecor Fabric Double Sofa Bed</td>\n",
              "      <td>32137.0</td>\n",
              "      <td>28664.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Provogue Corporate Casuals</td>\n",
              "      <td>2485.0</td>\n",
              "      <td>2485.0</td>\n",
              "      <td>dilli bazaaar Bellies, Corporate Casuals, Casuals</td>\n",
              "      <td>682.0</td>\n",
              "      <td>385.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>699.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>Alisha Solid Women's Cycling Shorts</td>\n",
              "      <td>1197.0</td>\n",
              "      <td>542.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6dcd733d-17fd-4bff-8890-8d3be72724cb')\"\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6dcd733d-17fd-4bff-8890-8d3be72724cb');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#bottom 10 rows of final df\n",
        "final_df.tail(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 546
        },
        "id": "smiUz3KILWLb",
        "outputId": "1ae2ec0c-5ff4-420e-cd11-fd4b51e54ae1"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      Product name in Flipkart  Retail Price in Flipkart  \\\n",
              "19990  Elite Collection Medium Acrylic Sticker                    1499.0   \n",
              "19991           WallDesign Small Vinyl Sticker                    1500.0   \n",
              "19992            999store Medium Paper Sticker                     999.0   \n",
              "19993  Elite Collection Medium Acrylic Sticker                    1499.0   \n",
              "19994  Wallmantra Large Vinyl Stickers Sticker                     727.0   \n",
              "19995           WallDesign Small Vinyl Sticker                    1220.0   \n",
              "19996  Wallmantra Large Vinyl Stickers Sticker                     727.0   \n",
              "19997  Elite Collection Medium Acrylic Sticker                    1499.0   \n",
              "19998  Elite Collection Medium Acrylic Sticker                    1299.0   \n",
              "19999  Elite Collection Medium Acrylic Sticker                    1499.0   \n",
              "\n",
              "       Discounted Price in Flipkart                   Product name in Amazon  \\\n",
              "19990                        1199.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19991                         730.0           WALLDESIGN SMALL VINYL STICKER   \n",
              "19992                         599.0            999STORE MEDIUM PAPER STICKER   \n",
              "19993                        1199.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19994                         582.0  WALLMANTRA LARGE VINYL STICKERS STICKER   \n",
              "19995                         600.0           WALLDESIGN SMALL VINYL STICKER   \n",
              "19996                         582.0  WALLMANTRA LARGE VINYL STICKERS STICKER   \n",
              "19997                        1199.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19998                         999.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "19999                        1199.0  ELITE COLLECTION MEDIUM ACRYLIC STICKER   \n",
              "\n",
              "       Retail Price in Amazon  Discounted Price in Amazon  \n",
              "19990                  1289.0                      1293.0  \n",
              "19991                  1212.0                       684.0  \n",
              "19992                   989.0                       713.0  \n",
              "19993                  1282.0                      1164.0  \n",
              "19994                   709.0                       721.0  \n",
              "19995                  1498.0                       876.0  \n",
              "19996                  1415.0                      1424.0  \n",
              "19997                  1284.0                      1196.0  \n",
              "19998                  1492.0                      1364.0  \n",
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            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Conclusion: \n",
        "\n",
        "Sentence transformer is best model for arranging similar product together."
      ],
      "metadata": {
        "id": "u0imn_ZDLhyk"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "mw1f59A0Lyt0"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}