From 70379d9c2e1e837079b8007397ac47b0f28176f2 Mon Sep 17 00:00:00 2001
From: Sibtain Syed <91776856+Shah621@users.noreply.github.com>
Date: Wed, 7 Sep 2022 01:28:31 +0500
Subject: [PATCH] Add files via upload

---
 Sibtain mini_project.ipynb | 3974 ++++++++++++++++++++++++++++++++++++
 1 file changed, 3974 insertions(+)
 create mode 100644 Sibtain mini_project.ipynb

diff --git a/Sibtain mini_project.ipynb b/Sibtain mini_project.ipynb
new file mode 100644
index 0000000..0d50df3
--- /dev/null
+++ b/Sibtain mini_project.ipynb	
@@ -0,0 +1,3974 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "collapsed_sections": [
+        "MVGEhdTf3yYO",
+        "ZiX2JfFZ7T4H"
+      ]
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "metadata": {
+        "id": "gGg2n5khYWcP"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Project Statement"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "DgIf27QkYZdq"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "\n",
+        "The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and find out the sales of each product at a particular store.\n",
+        "\n",
+        "  Using this model, BigMart will try to understand the properties of products and stores which play a key role in increasing sales.\n"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "yHStjdg-ZVrL"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Importing required libraries"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "0jtkDNuNTWuM"
+      },
+      "cell_type": "code",
+      "source": [
+        "import numpy as np\n",
+        "import pandas as pd\n",
+        "import seaborn as sns\n",
+        "import matplotlib.pyplot as plt\n"
+      ],
+      "execution_count": 1,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "H4FKbeOnkOh2",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "7f9da9d6-f3b6-44a2-f169-6ec7030f1002"
+      },
+      "cell_type": "code",
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')\n"
+      ],
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Mounted at /content/drive\n"
+          ]
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "oLIaROFdZdH8"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Importing Dataset"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "ZlVqBiWglcIi"
+      },
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "df_train = pd.read_csv('/content/drive/My Drive/Train.csv')\n",
+        "df_test = pd.read_csv('/content/drive/My Drive/Test.csv')\n"
+      ],
+      "execution_count": 159,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "ZW6RC5T5Zkde",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "cbed743b-a02a-49d8-bbb3-bf6c519c146d"
+      },
+      "cell_type": "code",
+      "source": [
+        "df_train.shape,df_test.shape"
+      ],
+      "execution_count": 7,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "((8523, 12), (5681, 11))"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 7
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "hjnm68J3l79Q",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 357
+        },
+        "outputId": "7320b4f2-73e2-41b7-8200-e1463ba76a2c"
+      },
+      "cell_type": "code",
+      "source": [
+        "df_train.head()"
+      ],
+      "execution_count": 15,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "  Item_Identifier  Item_Weight Item_Fat_Content  Item_Visibility  \\\n",
+              "0           FDA15         9.30          Low Fat         0.016047   \n",
+              "1           DRC01         5.92          Regular         0.019278   \n",
+              "2           FDN15        17.50          Low Fat         0.016760   \n",
+              "3           FDX07        19.20          Regular         0.000000   \n",
+              "4           NCD19         8.93          Low Fat         0.000000   \n",
+              "\n",
+              "               Item_Type  Item_MRP Outlet_Identifier  \\\n",
+              "0                  Dairy  249.8092            OUT049   \n",
+              "1            Soft Drinks   48.2692            OUT018   \n",
+              "2                   Meat  141.6180            OUT049   \n",
+              "3  Fruits and Vegetables  182.0950            OUT010   \n",
+              "4              Household   53.8614            OUT013   \n",
+              "\n",
+              "   Outlet_Establishment_Year Outlet_Size Outlet_Location_Type  \\\n",
+              "0                       1999      Medium               Tier 1   \n",
+              "1                       2009      Medium               Tier 3   \n",
+              "2                       1999      Medium               Tier 1   \n",
+              "3                       1998         NaN               Tier 3   \n",
+              "4                       1987        High               Tier 3   \n",
+              "\n",
+              "         Outlet_Type  Item_Outlet_Sales  \n",
+              "0  Supermarket Type1          3735.1380  \n",
+              "1  Supermarket Type2           443.4228  \n",
+              "2  Supermarket Type1          2097.2700  \n",
+              "3      Grocery Store           732.3800  \n",
+              "4  Supermarket Type1           994.7052  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-1b997705-0404-49c0-bacd-c3c86ed6b27e\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Item_Identifier</th>\n",
+              "      <th>Item_Weight</th>\n",
+              "      <th>Item_Fat_Content</th>\n",
+              "      <th>Item_Visibility</th>\n",
+              "      <th>Item_Type</th>\n",
+              "      <th>Item_MRP</th>\n",
+              "      <th>Outlet_Identifier</th>\n",
+              "      <th>Outlet_Establishment_Year</th>\n",
+              "      <th>Outlet_Size</th>\n",
+              "      <th>Outlet_Location_Type</th>\n",
+              "      <th>Outlet_Type</th>\n",
+              "      <th>Item_Outlet_Sales</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>FDA15</td>\n",
+              "      <td>9.30</td>\n",
+              "      <td>Low Fat</td>\n",
+              "      <td>0.016047</td>\n",
+              "      <td>Dairy</td>\n",
+              "      <td>249.8092</td>\n",
+              "      <td>OUT049</td>\n",
+              "      <td>1999</td>\n",
+              "      <td>Medium</td>\n",
+              "      <td>Tier 1</td>\n",
+              "      <td>Supermarket Type1</td>\n",
+              "      <td>3735.1380</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>DRC01</td>\n",
+              "      <td>5.92</td>\n",
+              "      <td>Regular</td>\n",
+              "      <td>0.019278</td>\n",
+              "      <td>Soft Drinks</td>\n",
+              "      <td>48.2692</td>\n",
+              "      <td>OUT018</td>\n",
+              "      <td>2009</td>\n",
+              "      <td>Medium</td>\n",
+              "      <td>Tier 3</td>\n",
+              "      <td>Supermarket Type2</td>\n",
+              "      <td>443.4228</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>FDN15</td>\n",
+              "      <td>17.50</td>\n",
+              "      <td>Low Fat</td>\n",
+              "      <td>0.016760</td>\n",
+              "      <td>Meat</td>\n",
+              "      <td>141.6180</td>\n",
+              "      <td>OUT049</td>\n",
+              "      <td>1999</td>\n",
+              "      <td>Medium</td>\n",
+              "      <td>Tier 1</td>\n",
+              "      <td>Supermarket Type1</td>\n",
+              "      <td>2097.2700</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>FDX07</td>\n",
+              "      <td>19.20</td>\n",
+              "      <td>Regular</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>Fruits and Vegetables</td>\n",
+              "      <td>182.0950</td>\n",
+              "      <td>OUT010</td>\n",
+              "      <td>1998</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Tier 3</td>\n",
+              "      <td>Grocery Store</td>\n",
+              "      <td>732.3800</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>NCD19</td>\n",
+              "      <td>8.93</td>\n",
+              "      <td>Low Fat</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>Household</td>\n",
+              "      <td>53.8614</td>\n",
+              "      <td>OUT013</td>\n",
+              "      <td>1987</td>\n",
+              "      <td>High</td>\n",
+              "      <td>Tier 3</td>\n",
+              "      <td>Supermarket Type1</td>\n",
+              "      <td>994.7052</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1b997705-0404-49c0-bacd-c3c86ed6b27e')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-1b997705-0404-49c0-bacd-c3c86ed6b27e 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-1b997705-0404-49c0-bacd-c3c86ed6b27e');\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": 15
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df_test.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 357
+        },
+        "id": "5yUjRbw1AciJ",
+        "outputId": "e4cc8f52-4b82-4725-d12e-afc647b9ccf3"
+      },
+      "execution_count": 16,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "  Item_Identifier  Item_Weight Item_Fat_Content  Item_Visibility    Item_Type  \\\n",
+              "0           FDW58       20.750          Low Fat         0.007565  Snack Foods   \n",
+              "1           FDW14        8.300              reg         0.038428        Dairy   \n",
+              "2           NCN55       14.600          Low Fat         0.099575       Others   \n",
+              "3           FDQ58        7.315          Low Fat         0.015388  Snack Foods   \n",
+              "4           FDY38          NaN          Regular         0.118599        Dairy   \n",
+              "\n",
+              "   Item_MRP Outlet_Identifier  Outlet_Establishment_Year Outlet_Size  \\\n",
+              "0  107.8622            OUT049                       1999      Medium   \n",
+              "1   87.3198            OUT017                       2007         NaN   \n",
+              "2  241.7538            OUT010                       1998         NaN   \n",
+              "3  155.0340            OUT017                       2007         NaN   \n",
+              "4  234.2300            OUT027                       1985      Medium   \n",
+              "\n",
+              "  Outlet_Location_Type        Outlet_Type  \n",
+              "0               Tier 1  Supermarket Type1  \n",
+              "1               Tier 2  Supermarket Type1  \n",
+              "2               Tier 3      Grocery Store  \n",
+              "3               Tier 2  Supermarket Type1  \n",
+              "4               Tier 3  Supermarket Type3  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-06165384-d043-4e66-8157-8c8a64aa4e22\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Item_Identifier</th>\n",
+              "      <th>Item_Weight</th>\n",
+              "      <th>Item_Fat_Content</th>\n",
+              "      <th>Item_Visibility</th>\n",
+              "      <th>Item_Type</th>\n",
+              "      <th>Item_MRP</th>\n",
+              "      <th>Outlet_Identifier</th>\n",
+              "      <th>Outlet_Establishment_Year</th>\n",
+              "      <th>Outlet_Size</th>\n",
+              "      <th>Outlet_Location_Type</th>\n",
+              "      <th>Outlet_Type</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>FDW58</td>\n",
+              "      <td>20.750</td>\n",
+              "      <td>Low Fat</td>\n",
+              "      <td>0.007565</td>\n",
+              "      <td>Snack Foods</td>\n",
+              "      <td>107.8622</td>\n",
+              "      <td>OUT049</td>\n",
+              "      <td>1999</td>\n",
+              "      <td>Medium</td>\n",
+              "      <td>Tier 1</td>\n",
+              "      <td>Supermarket Type1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>FDW14</td>\n",
+              "      <td>8.300</td>\n",
+              "      <td>reg</td>\n",
+              "      <td>0.038428</td>\n",
+              "      <td>Dairy</td>\n",
+              "      <td>87.3198</td>\n",
+              "      <td>OUT017</td>\n",
+              "      <td>2007</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Tier 2</td>\n",
+              "      <td>Supermarket Type1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>NCN55</td>\n",
+              "      <td>14.600</td>\n",
+              "      <td>Low Fat</td>\n",
+              "      <td>0.099575</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>241.7538</td>\n",
+              "      <td>OUT010</td>\n",
+              "      <td>1998</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Tier 3</td>\n",
+              "      <td>Grocery Store</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>FDQ58</td>\n",
+              "      <td>7.315</td>\n",
+              "      <td>Low Fat</td>\n",
+              "      <td>0.015388</td>\n",
+              "      <td>Snack Foods</td>\n",
+              "      <td>155.0340</td>\n",
+              "      <td>OUT017</td>\n",
+              "      <td>2007</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Tier 2</td>\n",
+              "      <td>Supermarket Type1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>FDY38</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Regular</td>\n",
+              "      <td>0.118599</td>\n",
+              "      <td>Dairy</td>\n",
+              "      <td>234.2300</td>\n",
+              "      <td>OUT027</td>\n",
+              "      <td>1985</td>\n",
+              "      <td>Medium</td>\n",
+              "      <td>Tier 3</td>\n",
+              "      <td>Supermarket Type3</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-06165384-d043-4e66-8157-8c8a64aa4e22')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
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+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-06165384-d043-4e66-8157-8c8a64aa4e22 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-06165384-d043-4e66-8157-8c8a64aa4e22');\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": 16
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "-0bTR-jsZrAX",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 630
+        },
+        "outputId": "d4d6fc25-df3c-4fc2-9916-ac2e7f740735"
+      },
+      "cell_type": "code",
+      "source": [
+        "df_train.info()\n",
+        "df_train.describe()\n"
+      ],
+      "execution_count": 24,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<class 'pandas.core.frame.DataFrame'>\n",
+            "RangeIndex: 8523 entries, 0 to 8522\n",
+            "Data columns (total 12 columns):\n",
+            " #   Column                     Non-Null Count  Dtype  \n",
+            "---  ------                     --------------  -----  \n",
+            " 0   Item_Identifier            8523 non-null   object \n",
+            " 1   Item_Weight                7060 non-null   float64\n",
+            " 2   Item_Fat_Content           8523 non-null   object \n",
+            " 3   Item_Visibility            8523 non-null   float64\n",
+            " 4   Item_Type                  8523 non-null   object \n",
+            " 5   Item_MRP                   8523 non-null   float64\n",
+            " 6   Outlet_Identifier          8523 non-null   object \n",
+            " 7   Outlet_Establishment_Year  8523 non-null   int64  \n",
+            " 8   Outlet_Size                6113 non-null   object \n",
+            " 9   Outlet_Location_Type       8523 non-null   object \n",
+            " 10  Outlet_Type                8523 non-null   object \n",
+            " 11  Item_Outlet_Sales          8523 non-null   float64\n",
+            "dtypes: float64(4), int64(1), object(7)\n",
+            "memory usage: 799.2+ KB\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "       Item_Weight  Item_Visibility     Item_MRP  Outlet_Establishment_Year  \\\n",
+              "count  7060.000000      8523.000000  8523.000000                8523.000000   \n",
+              "mean     12.857645         0.066132   140.992782                1997.831867   \n",
+              "std       4.643456         0.051598    62.275067                   8.371760   \n",
+              "min       4.555000         0.000000    31.290000                1985.000000   \n",
+              "25%       8.773750         0.026989    93.826500                1987.000000   \n",
+              "50%      12.600000         0.053931   143.012800                1999.000000   \n",
+              "75%      16.850000         0.094585   185.643700                2004.000000   \n",
+              "max      21.350000         0.328391   266.888400                2009.000000   \n",
+              "\n",
+              "       Item_Outlet_Sales  \n",
+              "count        8523.000000  \n",
+              "mean         2181.288914  \n",
+              "std          1706.499616  \n",
+              "min            33.290000  \n",
+              "25%           834.247400  \n",
+              "50%          1794.331000  \n",
+              "75%          3101.296400  \n",
+              "max         13086.964800  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-94ec3ede-94df-41ee-8fad-b1c23c51dffe\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Item_Weight</th>\n",
+              "      <th>Item_Visibility</th>\n",
+              "      <th>Item_MRP</th>\n",
+              "      <th>Outlet_Establishment_Year</th>\n",
+              "      <th>Item_Outlet_Sales</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>7060.000000</td>\n",
+              "      <td>8523.000000</td>\n",
+              "      <td>8523.000000</td>\n",
+              "      <td>8523.000000</td>\n",
+              "      <td>8523.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>12.857645</td>\n",
+              "      <td>0.066132</td>\n",
+              "      <td>140.992782</td>\n",
+              "      <td>1997.831867</td>\n",
+              "      <td>2181.288914</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>4.643456</td>\n",
+              "      <td>0.051598</td>\n",
+              "      <td>62.275067</td>\n",
+              "      <td>8.371760</td>\n",
+              "      <td>1706.499616</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>4.555000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>31.290000</td>\n",
+              "      <td>1985.000000</td>\n",
+              "      <td>33.290000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>8.773750</td>\n",
+              "      <td>0.026989</td>\n",
+              "      <td>93.826500</td>\n",
+              "      <td>1987.000000</td>\n",
+              "      <td>834.247400</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>12.600000</td>\n",
+              "      <td>0.053931</td>\n",
+              "      <td>143.012800</td>\n",
+              "      <td>1999.000000</td>\n",
+              "      <td>1794.331000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>16.850000</td>\n",
+              "      <td>0.094585</td>\n",
+              "      <td>185.643700</td>\n",
+              "      <td>2004.000000</td>\n",
+              "      <td>3101.296400</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>21.350000</td>\n",
+              "      <td>0.328391</td>\n",
+              "      <td>266.888400</td>\n",
+              "      <td>2009.000000</td>\n",
+              "      <td>13086.964800</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-94ec3ede-94df-41ee-8fad-b1c23c51dffe')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
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+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
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+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-94ec3ede-94df-41ee-8fad-b1c23c51dffe 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-94ec3ede-94df-41ee-8fad-b1c23c51dffe');\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": 24
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df_test.info()\n",
+        "df_test.describe()\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 613
+        },
+        "id": "OzHfya1MBzhU",
+        "outputId": "596c074a-88b1-493d-cd59-2124a6df64e0"
+      },
+      "execution_count": 25,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<class 'pandas.core.frame.DataFrame'>\n",
+            "RangeIndex: 5681 entries, 0 to 5680\n",
+            "Data columns (total 11 columns):\n",
+            " #   Column                     Non-Null Count  Dtype  \n",
+            "---  ------                     --------------  -----  \n",
+            " 0   Item_Identifier            5681 non-null   object \n",
+            " 1   Item_Weight                4705 non-null   float64\n",
+            " 2   Item_Fat_Content           5681 non-null   object \n",
+            " 3   Item_Visibility            5681 non-null   float64\n",
+            " 4   Item_Type                  5681 non-null   object \n",
+            " 5   Item_MRP                   5681 non-null   float64\n",
+            " 6   Outlet_Identifier          5681 non-null   object \n",
+            " 7   Outlet_Establishment_Year  5681 non-null   int64  \n",
+            " 8   Outlet_Size                4075 non-null   object \n",
+            " 9   Outlet_Location_Type       5681 non-null   object \n",
+            " 10  Outlet_Type                5681 non-null   object \n",
+            "dtypes: float64(3), int64(1), object(7)\n",
+            "memory usage: 488.3+ KB\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "       Item_Weight  Item_Visibility     Item_MRP  Outlet_Establishment_Year\n",
+              "count  4705.000000      5681.000000  5681.000000                5681.000000\n",
+              "mean     12.695633         0.065684   141.023273                1997.828903\n",
+              "std       4.664849         0.051252    61.809091                   8.372256\n",
+              "min       4.555000         0.000000    31.990000                1985.000000\n",
+              "25%       8.645000         0.027047    94.412000                1987.000000\n",
+              "50%      12.500000         0.054154   141.415400                1999.000000\n",
+              "75%      16.700000         0.093463   186.026600                2004.000000\n",
+              "max      21.350000         0.323637   266.588400                2009.000000"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-c38133e8-5218-4853-8a22-f50f0cb39d36\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Item_Weight</th>\n",
+              "      <th>Item_Visibility</th>\n",
+              "      <th>Item_MRP</th>\n",
+              "      <th>Outlet_Establishment_Year</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>4705.000000</td>\n",
+              "      <td>5681.000000</td>\n",
+              "      <td>5681.000000</td>\n",
+              "      <td>5681.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>12.695633</td>\n",
+              "      <td>0.065684</td>\n",
+              "      <td>141.023273</td>\n",
+              "      <td>1997.828903</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>4.664849</td>\n",
+              "      <td>0.051252</td>\n",
+              "      <td>61.809091</td>\n",
+              "      <td>8.372256</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>4.555000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>31.990000</td>\n",
+              "      <td>1985.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>8.645000</td>\n",
+              "      <td>0.027047</td>\n",
+              "      <td>94.412000</td>\n",
+              "      <td>1987.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>12.500000</td>\n",
+              "      <td>0.054154</td>\n",
+              "      <td>141.415400</td>\n",
+              "      <td>1999.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>16.700000</td>\n",
+              "      <td>0.093463</td>\n",
+              "      <td>186.026600</td>\n",
+              "      <td>2004.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>21.350000</td>\n",
+              "      <td>0.323637</td>\n",
+              "      <td>266.588400</td>\n",
+              "      <td>2009.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c38133e8-5218-4853-8a22-f50f0cb39d36')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-c38133e8-5218-4853-8a22-f50f0cb39d36 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-c38133e8-5218-4853-8a22-f50f0cb39d36');\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": 25
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "hlHJ1Gk1mBQF",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "45bd456b-e8e7-4b46-cf31-157738def39d"
+      },
+      "cell_type": "code",
+      "source": [
+        "df_train.columns,df_test.columns"
+      ],
+      "execution_count": 22,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(Index(['Item_Identifier', 'Item_Weight', 'Item_Fat_Content', 'Item_Visibility',\n",
+              "        'Item_Type', 'Item_MRP', 'Outlet_Identifier',\n",
+              "        'Outlet_Establishment_Year', 'Outlet_Size', 'Outlet_Location_Type',\n",
+              "        'Outlet_Type', 'Item_Outlet_Sales'],\n",
+              "       dtype='object'),\n",
+              " Index(['Item_Identifier', 'Item_Weight', 'Item_Fat_Content', 'Item_Visibility',\n",
+              "        'Item_Type', 'Item_MRP', 'Outlet_Identifier',\n",
+              "        'Outlet_Establishment_Year', 'Outlet_Size', 'Outlet_Location_Type',\n",
+              "        'Outlet_Type'],\n",
+              "       dtype='object'))"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 22
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "0Q9hSlGixCpQ"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Cleaning Data"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "qyyeNysexGOj"
+      },
+      "cell_type": "code",
+      "source": [
+        "#For Training\n",
+        "\n",
+        "df_train.isnull().sum()\n",
+        "# Removing Null values\n",
+        "df_train['Item_Weight']=df_train['Item_Weight'].fillna(df_train['Item_Weight'].mean())\n",
+        "df_train['Outlet_Size']=df_train['Outlet_Size'].fillna('Medium')"
+      ],
+      "execution_count": 160,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# For Testing\n",
+        "\n",
+        "df_test.isnull().sum()\n",
+        "# Removing Null values\n",
+        "df_test['Item_Weight']=df_test['Item_Weight'].fillna(df_test['Item_Weight'].mean())\n",
+        "df_test['Outlet_Size']=df_test['Outlet_Size'].fillna('Medium')\n"
+      ],
+      "metadata": {
+        "id": "sHsZovkBCl-s"
+      },
+      "execution_count": 161,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "MVGEhdTf3yYO"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Exploratory Data Analysis"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "gpp90CIc7-iI"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Univariate Analysis"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "asft9W144A9x",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 352
+        },
+        "outputId": "dda5eef0-b8fa-4c80-ef64-66ce3cfa5388"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.distplot(df_train['Item_Outlet_Sales'])"
+      ],
+      "execution_count": 29,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218e712850>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 29
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "EdfbuF2rackP"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "We can see that the Outlet_sales is normally distributed with right skewness."
+      ]
+    },
+    {
+      "metadata": {
+        "id": "-1rvyazj4QPY",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 352
+        },
+        "outputId": "3dd3bc9f-ae9d-4b60-abc0-2abe07fe39c1"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.boxplot(df_train['Item_Weight'])"
+      ],
+      "execution_count": 31,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218df1aed0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 31
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sns.boxplot(df_test['Item_Weight'])"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 352
+        },
+        "id": "4nej4CDJDps-",
+        "outputId": "488405db-d7c2-4a35-ba73-ce46be66d167"
+      },
+      "execution_count": 32,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218e7166d0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 32
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "Qv6W4pTxavQn"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "Most of the items have weight in range of 8-16 in both training and testing dataset. \n",
+        "The mode of weight is near to 13."
+      ]
+    },
+    {
+      "metadata": {
+        "id": "MND32U0-4kTL",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "outputId": "e82e4622-5a12-4d50-e3bf-267ebc522fea"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.countplot(x='Outlet_Size',data=df_train)"
+      ],
+      "execution_count": 37,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218dc6b8d0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 37
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "xLwE9mlG8Ijy",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 355
+        },
+        "outputId": "17d81556-1a9a-495f-a108-72695e781d0c"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.countplot(df_train['Outlet_Location_Type'])"
+      ],
+      "execution_count": 38,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218dc8f750>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 38
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sns.countplot(x='Outlet_Size',data=df_test)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "id": "uMFZkzeSEbk5",
+        "outputId": "5341afcc-388c-4eb9-caaa-657499b165de"
+      },
+      "execution_count": 39,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218db61e90>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 39
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sns.countplot(df_test['Outlet_Location_Type'])"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 352
+        },
+        "id": "zjgg2iigEjQ-",
+        "outputId": "08be0813-b552-4aed-b6ba-80f243b6c701"
+      },
+      "execution_count": 41,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218dab6690>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 41
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "gbb0Q-3EbGBa"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "1.   Most of the Outlet are located in Tier 3 for the training and testing dataset as well.\n",
+        "2.   Tier 2 location is second most after Tier 3 in both cases too.\n",
+        "\n"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "2qZXsZlv8bg_",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 352
+        },
+        "outputId": "294cbfd3-0161-4cfe-8f1b-3ba7120bb4d2"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.countplot(df_train['Outlet_Type'])"
+      ],
+      "execution_count": 16,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7fda386dc410>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 16
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sns.countplot(df_test['Outlet_Type'])"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 352
+        },
+        "id": "n8mPItXPFZxz",
+        "outputId": "28da896d-38da-4464-dec8-ba64a3e3bd97"
+      },
+      "execution_count": 42,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218dab2410>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 42
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "aSD2JbcGbd3-"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "\n",
+        "1.   Most Outlets are Supermarkets of type 1\n",
+        "2.   There is Significant amount of Outlets which are Grocery store. \n",
+        "\n"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "zA9jiqgf8k3z"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Bi-variate Analyis"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "F2H-PQLR8P1X",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "outputId": "c346feba-25d5-4bee-dec4-ece3f29eb400"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.regplot(x='Item_Weight',y='Item_Outlet_Sales',data=df_train)"
+      ],
+      "execution_count": 49,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218db58810>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 49
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "6JOPaobjbzdA"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "The plot show that outlet sales has less co-relation with item weight."
+      ]
+    },
+    {
+      "metadata": {
+        "id": "zo31RrJNERI0",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "outputId": "d1b436f8-e577-42f1-9fd1-b52470814124"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.boxplot(x='Outlet_Identifier',y='Item_Outlet_Sales',data=df_train)"
+      ],
+      "execution_count": 53,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218ae56790>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 53
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "caHE2Yf7cGv7"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "\n",
+        "1.   OUT027 has maximum outlet sales.\n",
+        "2.   OUT049 and OUT019 have least outlet sales among all.\n",
+        "\n"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "-vPMOvt18-SE",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "outputId": "2a15e4fb-a93d-4d32-f46d-eb71ad90918a"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.regplot(x='Item_Visibility',y='Item_Outlet_Sales',data=df_train)"
+      ],
+      "execution_count": 54,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218ad24dd0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 54
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "eLxrZHovcY2e"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "\n",
+        "1.   There is significant co-relation between Item_visibility and outlet sales.\n",
+        "2.   The visbility range 0.00-0.20 has maximum outlet sales.\n",
+        "\n"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "XsyWriwz_M7d",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 623
+        },
+        "outputId": "6fabe664-0fa3-416d-d254-a8757505e128"
+      },
+      "cell_type": "code",
+      "source": [
+        "plt.figure(figsize=(10,10))\n",
+        "sns.boxplot(x='Outlet_Size',y='Item_Outlet_Sales',data=df_train)"
+      ],
+      "execution_count": 55,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218ad1df50>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 55
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 720x720 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "zVD_eF2Xc1_J"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "The plot shows the relation of Outlet size with outlet sales."
+      ]
+    },
+    {
+      "metadata": {
+        "id": "F5DBFSVZ9KFI",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 206
+        },
+        "outputId": "3d9d2196-b1cd-490a-ce25-8c530cfb005a"
+      },
+      "cell_type": "code",
+      "source": [
+        "df_train.corr()"
+      ],
+      "execution_count": 60,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                           Item_Weight  Item_Visibility  Item_MRP  \\\n",
+              "Item_Weight                   1.000000        -0.012049  0.024756   \n",
+              "Item_Visibility              -0.012049         1.000000 -0.001315   \n",
+              "Item_MRP                      0.024756        -0.001315  1.000000   \n",
+              "Outlet_Establishment_Year    -0.008301        -0.074834  0.005020   \n",
+              "Item_Outlet_Sales             0.011550        -0.128625  0.567574   \n",
+              "\n",
+              "                           Outlet_Establishment_Year  Item_Outlet_Sales  \n",
+              "Item_Weight                                -0.008301           0.011550  \n",
+              "Item_Visibility                            -0.074834          -0.128625  \n",
+              "Item_MRP                                    0.005020           0.567574  \n",
+              "Outlet_Establishment_Year                   1.000000          -0.049135  \n",
+              "Item_Outlet_Sales                          -0.049135           1.000000  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-57a6af31-8bce-455a-8e7c-e15362bf212e\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Item_Weight</th>\n",
+              "      <th>Item_Visibility</th>\n",
+              "      <th>Item_MRP</th>\n",
+              "      <th>Outlet_Establishment_Year</th>\n",
+              "      <th>Item_Outlet_Sales</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Item_Weight</th>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>-0.012049</td>\n",
+              "      <td>0.024756</td>\n",
+              "      <td>-0.008301</td>\n",
+              "      <td>0.011550</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Item_Visibility</th>\n",
+              "      <td>-0.012049</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>-0.001315</td>\n",
+              "      <td>-0.074834</td>\n",
+              "      <td>-0.128625</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Item_MRP</th>\n",
+              "      <td>0.024756</td>\n",
+              "      <td>-0.001315</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.005020</td>\n",
+              "      <td>0.567574</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Outlet_Establishment_Year</th>\n",
+              "      <td>-0.008301</td>\n",
+              "      <td>-0.074834</td>\n",
+              "      <td>0.005020</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>-0.049135</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Item_Outlet_Sales</th>\n",
+              "      <td>0.011550</td>\n",
+              "      <td>-0.128625</td>\n",
+              "      <td>0.567574</td>\n",
+              "      <td>-0.049135</td>\n",
+              "      <td>1.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-57a6af31-8bce-455a-8e7c-e15362bf212e')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-57a6af31-8bce-455a-8e7c-e15362bf212e 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-57a6af31-8bce-455a-8e7c-e15362bf212e');\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": 60
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "08rVDK1z9NQ9",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 409
+        },
+        "outputId": "998af0ee-f9fb-4509-e595-eafdc5d95152"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.heatmap(df_train.corr())"
+      ],
+      "execution_count": 61,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218aa30a50>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 61
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 2 Axes>"
+            ],
+            "image/png": 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n4FvNL5R0mKTZkmbf/8hf2gglIqIzer2JOL2Ie4eAI21fvFyhtCuwpKFosGF/kPZ+hxcAJwOzbT8o/ds/tt2AhcBZwCeAD5blj9qePtqJbc8EZgLs8OyX9viotIjoJ+lFHCNZBKzdsH8x8G5JqwBI2kzSmp24kO1HgI8AnxrlmKXAByhq0U/txHUjIrrJY9iqkBpsdeYAA5JuAs4ETqVo7r1eRRXzfoom3Y6wfU4bx9wn6WzgCOCTnbp2REQ3VNX0264k2Alme63y5+PA7k1Pf6zcGl1abkOv37Xh8XLPDXOtE0YobzzH1Kbnjmx4vNZI546IqFonewdL2ouiojMZON32SSMc9wbgR8COtmePds40EUdERC0NjmEbjaTJwFcpOnpuAewvaYthjlsbeD9FR9SWkmD7gKRjy/G0jduxVccVEdFNRm1vLcwAbrd9p+3HKEZe7DPMcZ8EPgssbie+NBH3AdufYpQOTBER/WjpGJqIJR0GHNZQNLMcBQHFBDt3Nzx3D/CiptdvB2xo++eSjm7nmkmwERFRS23UTJcd2zCkcKwkTQK+CBw8ltclwUZERC21urc6BvcCGzbsb1CWDVkb2Aq4tJxH4FnALEl7j9bRKQk2IiJqaSw12BauBaaV09PeSzHz3ROLsdh+AHja0L6kS4EPpRdxRET0pU71Ii4n2nkvxYQ/NwPn2p4v6URJe69ofKnBRkRELQ10rgaL7QuBC5vKjhvh2F3bOWcSbERE1NJgb0/klAQbERH1NNjBGmw3JMFGREQt9fryXUmwERFRSx0cptMVSbAREVFLg/++tnVPSYKNiIhaGqg6gBaSYCMiopbSizgiIqIL0os4VhoPDyypOoSOu3/xwqpD6Irttzqw6hA67rp5Z1UdQldsvNkKTyTU0+7pwDnSizgiIqIL0kQcERHRBRmmExER0QUDqcFGRER0XmqwERERXZAEGxER0QVOE3FERETnpQYbERHRBZkqMSIiogsyDjYiIqIL0kQcERHRBUmwERERXZC5iCMiIrog92AjIiK6IL2IIyIiumCwxxuJk2AjIqKW0skpIiKiC3q7/poEGxERNdXrNdhJ7RwkaQNJ50u6TdIdkk6VtGqL13ysaf+hFsdPkfSeFsdMlfSopBsbtreOcvzBkp4z2jnL4y6VtMMIr/9K+fjwFtc6QdKHWl2rk5o/46bnJOm3kl7ZULafpIsmJrqIiO5aKre9VaFlgpUk4CfAT21PAzYD1gI+1eKlI/7xH8EUYNQEW7rD9vSG7bujHHsw0DLBtsP2aS2uVYURP2PbBg4HvihpNUlrAZ8GjljRi0lKi0dE9AyPYatCOzXY3YHFtr8NYHsAOAp4h6T3DNXwACRdIGlXSScBq5c1zLOaTyjpaEnXSpoj6RNl8UnApuVrTh7Lm5A0WdKZkuZJmivpKEn7AjsAZ5XnXF3SceV150maWX55GPKW8rh5kmYMc40naqiS3idpQRn/OQ2HbVHWhu+U9L7y2KmSbinj+72ksyS9QtIVZYvAjPK4NSWdIekaSTdI2qcsP1jSTyRdVB7/ubJ81M8YwPY84GfAR4DjgO8CfxnhOlMlXS7p+nLbuSzftSyfBSwYy+8lIqKbBsewtSJpL0m3Srpd0jHDPP/Bhr/7v5K0UatztlMj2RK4rrHA9oOS/jTS620fI+m9tqcPE+SewDRgBiBglqT/AI4BthruNU02lXRjw/6RwCPA+ra3Kq8xxfZCSe8FPmR7dln+Fdsnlo+/B7yGIgEBrGF7ehnLGcBWo8RwDLCx7SWSpjSUvwDYDVgbuFXS18vy5wH7Ae8ArgUOAHYB9qaohb4OOBb4H9vvKM95jaRflq+fDrwQWFKe98ujfcZNPgFcDzxG8YXj+BGu8zdgD9uLJU0Dzi6PB9iO4ndzV4trRURMmE4N05E0GfgqsAdwD3CtpFm2GysVNwA72H5E0ruBzwFvGu28VTT57VluN5T7a1Ek3D+1+fo7mpOKpKcAm0j6MvBz4JIRXrubpA8DawBPBeazLMGeDWD7N5LWaUqczeZQ1Ix/Cvy0ofzntpcASyT9DXhmWX6X7bllrPOBX9m2pLnA1PKYPYG9tew+7mrAc8vHv7L9QPn6BcBGwN2jxPcE2w9L+iHwUPmFYKTr/Bn4iqTpFOO3N2s4zTUjJVdJhwGHATxrrY2Ysvoz2gkrImLcOtj0OwO43fadAGXL5D40tNrZ/nXD8b8DDmp10nYS7AJg38YCSetQ/FFeyPLNzKu1cT4Bn7H9jaZzTm3jtcOy/S9J2wL/SXHf8Y0UtcXG868GfI3iG8jdkk5oirf5dzXa7+7VwH8ArwWOlbR1Wb6k4ZgBln2+jeWDDfuDDccIeIPtW5viftEo521XYyvJSNc5AfgrsC3F73Rxw9MPj3Ri2zOBmQCbP2NGr/eaj4g+MpZexI2VgdLM8u8XwPosX2m5B3jRKKc7BPhFq2u2cw/2V8AaKnvQllXpLwBnAncC0yVNkrQhxbeAIY9LWmWY811Mcf92rfJ860t6BrCIoml1zCQ9DZhk+8fAxymaNGk651Ay/Xt57X2XP0tR1Ze0C/DAUI1xmGtNAjYsv818BFiXohY+XhcDRw7dF5b0wjZeM9JnvCLXWRe4z/Yg8BZg8hjPGxExoQZw25vtmbZ3aNhmtr7Cv5N0EMXts5Z9hVrWhMqmzNcDX5P0XxRJ+UKKe4ePAXdR1HJvprjXN2QmMEfS9bYPbDjfJZI2B64q/8Y/BBxk+46y48884Be2jx4hpOZ7sGcAlwHfLpMfwEfLn2cCp0l6FNgJ+CYwD/gLxb3QRosl3QCsQlPtt8lk4PuS1qWoDX6pvN87ykva8kng/1J8ZpMoPtfXtHjNsJ/xCl7na8CPyy9SFzFKrTUiohd0cBzsvcCGDfsblGXLkfQKiv4yLytvB45KxWiOiPHrxybi+xcvrDqErnjOGutVHULHXTdv2M70tbfxZntXHUJX3PPPeeOulbxv6pva/pvzpT/8cMTrqRiC+Hvg5RSJ9VrgANvzG455IfAjYC/bt7VzzYxrjIiIWupUDdb20nLUycUUrZRn2J4v6URgtu1ZFE3CawHnlS2Wf7I96refnkywZaeh7zUVL7E92k3nlZak9SjulTd7ue1/THQ8EREToZOr6di+kOL2Z2PZcQ2PXzHWc/Zkgi2HtLQa3xmlMonm84qIlUqv35PqyQQbERHRytIeT7FJsBERUUtOgo2IiOi8Xl+uLgk2IiJqKTXYiIiILkgNNiIiogsGenyipCTYiIiopU6Og+2GJNiIiKil3IONiIjogtyDjYiI6II0EUdERHRBmogjIiK6IL2IIyIiuiBNxLHSWHVS//1zWrj44apD6Ipbdnp21SF0XL8uTH7X72dVHULPSieniIiILsg92IiIiC5IE3FEREQXOJ2cIiIiOm8gNdiIiIjOSxNxREREF6SJOCIiogtSg42IiOiCDNOJiIjogkyVGBER0QVpIo6IiOiCJNiIiIguSC/iiIiILkgNNiIiogvSizgiIqILBtzbC9ZNqjqAiIiIFWG77a0VSXtJulXS7ZKOGeb5J0v6Yfn81ZKmtjpnEmxERNTSIG57G42kycBXgVcCWwD7S9qi6bBDgH/Zfh5wCvDZVvH1VYKV9FD5c6qkAybgeodJuqXcrpG0Sxuv2VXSzg37J0j6UIvXvG6YX3bzMS8uv1XdKOlmSSe0EccFreKNiOhVHsN/LcwAbrd9p+3HgHOAfZqO2Qf4Tvn4R8DLJWm0k/ZVgm0wFehqgpX0GuBdwC62XwAcDvxA0rNavHRXYOcWxzR7HcW3qtF8BzjM9nRgK+DcMV4jIqJWBu22t7JCNLthO6zhVOsDdzfs31OWMdwxtpcCDwDrjRZfvybYk4CXlrW5oyRNlnSypGslzZH0LniiFneZpPMl3SnpJEkHlrXRuZI2HeUaHwGOtv13ANvXUyS5I8pz/0HS08rHO0i6tGyzPxw4qoztpY0nlLSppIskXSfpckkvKGu7ewMnl68ZKaZnAPeVsQzYXlCec4akqyTdIOlKSc9vfqGkNSWdUb7vGyTtU5ZvWZbdWH5u09r47CMiJsRYarC2Z9reoWGb2e34+rUX8THAh2y/BoqmXOAB2ztKejJwhaRLymO3BTYH/gncCZxue4ak9wNHAh8Y4RpbAtc1lc0G3jZSULb/IOk04CHbny9je3nDITOBw23fJulFwNds7y5pFnCB7R+N8p5PAW6VdClwEfAd24uBW4CX2l4q6RXAp4E3NL32WOB/bL9D0hTgGkm/pPgycKrtsyStCkwe5foREROqg72I7wU2bNjfoCwb7ph7JD0JWBf4x2gn7dcE22xPYBtJ+5b76wLTgMeAa23fByDpDmAo8c4FdpuoACWtRdF0fF5Ds/6T23297RMlnUXxXg8A9qdojl4X+E5Z+zSwyjAv3xPYu+Fe8GrAc4GrgGMlbQD8xPZtw8R9GHAYwPprb8J6azyz3ZAjIsZlsHMzOV0LTJO0MUUifTP/fptxFkUF6ipgX4pKyagBrCwJVsCRti9erlDaFVjSUDTYsD/I6J/PAmB74H8ayrYH5pePl7KsCX61NmKcBCws76GuENt3AF+X9E3gfknrAZ8Efm379WUT9aXDvFTAG2zf2lR+s6SrgVcDF0p6l+3G90vZzDITYNtn7dzbo74joq90aqKJsoXvvcDFFC11Z9ieL+lEYLbtWcC3gO9Jup2ixfPNrc7br/dgFwFrN+xfDLxb0ioAkjaTtOY4r/E54LNlEkPSdOBg4Gvl83+gSLiwfJNsc2wA2H4QuEvSfuX5JGnb0V7TSNKrG3q0TQMGgIUUNdihpo6DR3j5xcCRQ6+X9MLy5ybAnba/BJwPbDNaDBERE2ksnZxasX2h7c1sb2r7U2XZcWVyxfZi2/vZfp7tGbbvbHXOfk2wc4ABSTdJOgo4naLGeb2kecA3GGftvfzQzwCulHQL8E3goKHmZuATwKmSZlMkuyE/A14/XCcn4EDgEEk3UdSEh7qJnwMcXXZAGqmT01so7sHeCHwPOND2AMUXgc9IumGU9/xJiqbjOZLml/sAbwTmlefcCvjuaJ9JRMRE6uAwna5Qr69GEPXRj03E8//5x6pD6Iq/7Pa8qkPouOnXjtrfpLbu+v2sqkPoilWetsmoY0jbsdF627T9N+eP/5gz7uuN1cpyDzYiIvpMr1cQk2BbkHQssF9T8XlDbfQVxPNV4CVNxafa/nYV8UREVCXL1dVcmUgrSabDsX1E1TFERPSC1GAjIiK6oIPjYLsiCTYiImopC65HRER0Qa8vuJ4EGxERtZR7sBEREV2Qe7ARERFdkBpsREREF2QcbERERBekBhsREdEF6UUcERHRBenkFBER0QVpIo6IiOiCzOQUERHRBanBRkREdEGv34NVr38DiBiOpMNsz6w6jk7rx/fVj+8J+vN99eN7qtKkqgOIWEGHVR1Al/Tj++rH9wT9+b768T1VJgk2IiKiC5JgIyIiuiAJNuqqX+8T9eP76sf3BP35vvrxPVUmnZwiIiK6IDXYiIiILkiCjYiI6IIk2IiIiC5Igo3akLRxO2V1I+m1kvL/YkSfyf/UUSc/HqbsRxMeRee9CbhN0uckvaDqYMZL0mqSPiDpK5LeJakvpmSVNFnSLVXH0Q2SNpX05PLxrpLeJ2lK1XHVXV/8w4/+ViadLYF1Jf2vhqfWAVarJqrOsX2QpHWA/YEzJRn4NnC27UXVRrdCvgM8DlwOvBLYAnh/pRF1gO0BSbdKeq7tP1UdT4f9GNhB0vMohuqcD/wAeFWlUdVcEmzUwfOB1wBTgNc2lC8CDq0kog6z/aCkHwGrAx8AXg8cLelLtr9cbXRjtoXtrQEkfQu4puJ4OukpwHxJ1wAPDxXa3ru6kDpi0PZSSa8Hvmz7y5JuqDqoukuCjZ5n+3zgfEk72b6q6ng6TdI+wMHA84DvAjNs/03SGsACoG4J9vGhB+Uf7Spj6bT/qjqALnlc0v7A21j2JXaVCuPpC5loImpD0tMpaqxTafhyaPsdVcXUCZK+A3zL9m+Gee7ltn9VQVgrTNIAy2p3oqiVP1I+tu11qoothidpC+Bw4CrbZ5edB99o+7MVh1ZrSX77eGAAABRZSURBVLBRG5KupLivdx0wMFRue7jOT7Uh6bO2P9KqLKon6cUULQqbA6sCk4GH++FLg6TVgefavrXqWPpFehFHnaxh+yO2z7X946Gt6qA6YI9hyl454VF0maQpko6tOo5x+gpFZ7TbKGrm7wS+WmlEHSDptcCNwEXl/nRJs6qNqv6SYKNOLpDUN70aJb1b0lzgBZLmNGx3AXOqjm9FSdpQ0kxJF0h6p6Q1JX2BIik9o+r4xsv27cBk2wO2vw3sVXVMHXACMANYCGD7RmCTKgPqB+nkFD1P0iLAFPfwPiZpCUVHmrrf0/sB8AvgM8AxDeWLbP+zmpA64rvAZRRDP/YCZlPUjra2/ZcqA+uARyStCtwo6XPAffRHReVx2w80dUgbrCqYfpF7sBEVkbROOTznqcM9X9ckK+km29s27N9DcW+v9n+wJW0E/JXi/utRwLrA18pabW2Vw6l+RfFF7w3A+4BVbB9eaWA1lwQbtSFpu2GKHwD+aHvpRMczXpIusP2askl4qIY+xLZr2UQn6SZgV5a9n1837tf1i8OQfuwMVA4JOxbYk+L3dDHwSduLKw2s5pJgozYk/Q7YDphbFm0NzKOoRbzb9iVVxRbLSPoDRfPicANga/vFAZ7oDPR5YFXbG0uaDpzYBxNNRBfkHmzUyZ+BQ2zPhyfG7p0IfBj4CVCrBDtCjfwJtq+fqFg6yfbUqmPoohMoOgNdCkVnoDovOCHpZxStJ8PKF4fxSYKNOtlsKLkC2F4g6QW276zpbEFfGOU5A7tPVCCd1K9fHErDdQaqczPg56sOoJ8lwUadzJf0deCccv9NwIJyFZDHR35Zb7K9W9UxdMlsiqb7v5f7y91bpqZfHErzJR0ATJY0jaIz0JUVx7TCbF9WdQz9LPdgozbKziXvAXYpi64AvgYsppiE4qGqYlsRkna3/T9NKwQ9wfZPJjqmTpD0AWBfig5o5wD/XbffTTNJF1L82/sbfdgZqPyy8BmKlY+eWKGqzvfLe0ESbERFJH3C9vGSvj3M0+6DOZY3Ad4M7AP8Efh0OYFB7UjaD/gUxVJ8n7NduxaT0Uj6LXA8cArFZP9vBybZPq7SwGouCTZ6nqRzbb+xnPXo3/7B2t6mgrCiDZK2pEiybwE+bPvcikNaYZLWolhNZy/gezRMxGD7i1XF1QmSrrO9vaS5DUsNXmd7+6pjq7Pcg406GFqs+zWVRtElktajqD3sQvEF4rcUQz/+UWlgK6ip5no3RTPxp20/Wmlg4/cYxSpBTwbWpr9mOloiaRJwm6T3AvcCa1UcU+2lBhu1Us6kM832L8t7sk+yvajquMZD0v8DfgN8vyw6ENjV9iuqi2rFSRqkmEv5fOBBmlod6ljbk7QX8EVgFsWXn0cqDqmjJO0I3AxMAT5JMbb8c7Z/V2lgNZcEG7Uh6VDgMOCptjctO2acZvvlFYc2LpLm2d6qqeyJprq6kXQCo4+t/MTERdMZki4HDm8cJjbCcU+x/a8JCqsrJD0FWOgkh3FLgo3akHQjxSD/q22/sCyrbSIaIumLwDXA0P3JfYEZtj9UXVTdJ+mjtj9TdRydJOl626OOA+4lko4DzrV9Sznc7SJgW2ApcIDtX1YaYM31wyoQsfJYYvuxoR1JT6LGg/wlLZL0IHAoxco6S8rtHIqaer/br+oAuqBuM568CRiaU/lt5c+nAy8DPl1JRH0knZyiTi6T9DFgdUl7UIxL/FnFMa0w22tXHUPF6paM2lG3L3yPNTQF/ydwju0B4ObyC2yMQz7AqJNjgEMoJvt/F3AhcHqlEY1DOc3jLSNNLVjzKQXbUbdk1I+WSNqKYgm+3YDG2xJrVBNS/0iCjZ4n6R/A1RQzN10JnNUnvTg/SNEUPNycxHWfUrAd/ViDrdt7ej/wI4pm4VNs3wUg6VXADVUG1g/SySl6nqR1gBcDO5fb9sBdFAn3ijpPXrAyk/Qx27W6zyfpe7bfMlKZpKfWfb3b4Uh6m+3vVB1H3STBRu1IWpNiKrcPABvbnlxxSONSTsN3ke1Fkj5OsebtJ23XugZRLuN2JDCVhtayOi+B1txLWNJkYK7tLSoMq+vq1ju6V6SJOHqepOewrPa6Y1l8HfBx4Kqq4uqg/7J9nqRdgFcAJwOnAS+qNqxx+ynwLYqOaLWe9UjSR4GhDnYPDhVTzO40s7LAJk7dmr57Qmqw0fPKmYGup5iI/LzGoTr9QNINtl8o6TMUtaEfDJVVHdt4SLradt2/JCxH0mdsf7TqOCZaarArJgk2ep6knYCdKGqwGwN/oKi5XgXMtr2kuujGT9IFFHO/7kHRPPwocI3tbSsNbJzKdVOnAZdQjO8F6t87WtL6wEYs3+z9m+oi6r5++MJXhSTYqB1JUymW1Ho/sIHt1UZ9QY+TtAbFCi1zbd8m6dnA1rYvqTi0cSlr5G8B7mBZE7Ft17Z3tKSTKBYyWAAMlMWu831lKO6XD/UgHq5M0ldsv7ea6OorCTZqQdILWHYf9iUUk5L/jqIX8eerjG1FSVrH9oOSnjrc83XvjSrpdmCLfmrSl3QrsE3dW02aDdcEnOXqxi+dnKLnSfo78GeKJuHfACfZvr3aqDriBxRL8F1HMe61sSOJgU2qCKqD5lF8Efpb1YF00J3AKjQ0eddZ+cV1S2BdSf+r4al1gFq3DPWCJNiog01tP9DqoBpOHv9OANsbVx1Il0wBbpF0Lcvfg61zc+ojwI2SfsXy7+l91YU0Ls+n+JI3heK2y5BFFHNkxzikiTj6Rt16Okr6C0Ut7wfAj9v5ElEnkl42XLntyyY6lk6R9Lbhyus+CYOknWz3w5C3npIEG32jbj0dy0kKXkHRaeZVFPeUzwbOt/1olbF1iqSNgGm2f1l25ppse1HVcY2HpNWB59q+teXBNSFpM+DrwDNtbyVpG2Bv2/+n4tBqLcvVRT+p1bdF2wO2L7b9dmBD4AxgH+AuSWdVG934STqUYp7bb5RF61NMPlFbkl4L3EixbiqSpkuaVW1UHfFN4KPA4wC251B88YtxSIKNflLb2WbKnrYLgJuBB4HNq42oI46g6PH9IIDt24BnVBrR+J0AzAAWAti+kfp3RgNYw/Y1TWVLK4mkjyTBRj85r+oAxkrShpKOlnQ9cAHF/5N71+le8iiWNA7RKdcXrVUrwzAeH+Zeea2ngSz9XdKmlL8fSfsC91UbUv2lF3HURqvJ42u4MsuVFM2m5wKH2r6u4pA67TJJQ/P37gG8h2Je4jqbX85QNVnSNOB9FEso1t0RFHMqv0DSvRSrVR1UbUj1l05OURuSbqKYPH4uDbWGuvZKlfQfwOVu8T9hDYcfASBpEnAIsCdF8/3Ftr9ZbVTjU3bUOpaG90Sx8tHiSgPrkHKlqkl174jWK5Jgozb6cfL4dtRt+NEQSe+3fWqrsqiOpA+O9rztL05ULP0oTcRRJ6dKOp4+mzy+DXXtvPU2oDmZHjxMWW1I2oFi2bqpLH+bYpuqYhqntUd5LrWvcUqCjTrZmmLy+N1pmDy+3O9ntfpDJ2l/4ABg46YhLGsDtZ5fGTgLOJqm2xR1ZfsTAJJeYvuKxuckvaSaqPpHEmzUyX7AJv00eXyb6laDvZKiB+rTgC80lC8C5lQSUefcb7sfxr02+zLFUomtymIMkmCjTvpx8vh21Gr4ke0/An+kWMO33xwv6XSgeS7in1QX0oor11reGXh60/3YdYDJ1UTVP5Jgo076cfL4fhx+tIjhm7VFsXbqOhMcUie9HXgBxYo6jbcpaplggVWBtSj+3TXej30Q2LeSiPpIehFHbfTj5PHQf8OP+pmkW20/v+o4Ok3SRmXLQ3RQarBRG7YvG27y+Krj6oDFtr9UdRDRlislbWF7QdWBdNiZkv6ttmW73zsQdlVqsFEb5eTxhwFPtb1pOZPOabZfXnFo41LODDSNlW/4Ue1IuhnYlGKmoyUsa/au6zAdACRt37C7GvAGYKntD1cUUl9IDTbq5AiKidavhmLyeEl1nzweVt7hR3W0V9UBdMMw03ReIal58v8YoyTYqJMlth+TilErfTJ5PKy8w49qx/Yfy3V8n0kf/f2U9NSG3UnA9sC6FYXTN/rmH0isFPpx8nhYeYcf1Y6kI4Hjgb+yfGtDrZuIgcYa7FKKJvBDKoqlb+QebNRGP04eDyDpUoo/0H01/KgfSbodeJHtf1QdS/S+1GCjTo4sJ4p/Iqn2yeTxx1cdQLTtbqB5PdhaK/sxHAFsWRbNB75qOy0q45QabNTGcKvKSLrB9guriqlThht+lCXDekfDLEdbAs8Hfs7yrQ21XHWmnG/4B8CZLGsm3p5ioYYDm+cnjrFJDTZ6Xp9PHr/c8COKISDrA6cBtR5+1GeGZjn6U7mtWm519wXgdbZvaCibJem/gW8AK93ykJ2UBBt10M+Tx0P/Dj/qG0OrzjQq+wSsZfvBCkLqlHWakisAtm+UNNpSdtGGJNjoeX0+eTz07/CjviPpB8DhwABFp7R1JJ1q++RqI1thkvQU2/9qKnwqxXCdGId8gNHzJC2S9OAw2yJJda49DGkefnQe/TH8qB9tUdZYXwf8AtiYYpKQujoFuETSyyStXW67Ury3U6oNrf7SySmiYv06/KgfSZoPTKfoGPSVcn7sm2xvW3FoK0zSa4APU3TgMrAAONl2vuSNUxJsRMWGG2rUJ8OP+o6k9wEfAW4CXg08F/i+7ZdWGliXSfqo7c9UHUfdJMFGVKyfhx+tDCQ9yfbSquPopuH+jUZr6eQUUZF+H37UTyQdZPv7DeNhm9VyHOwYqOoA6igJNqI6/T78qJ+sWf5cWYeupKlzBaSJOCIiRpVbFismNdiIikhaxPA1g6FFvNeZ4JBiBJK+NNrztt83UbFU5LyqA6ijJNiIitheWZsb66h5QfK+Imlj4EhgKg15YWhFJ9ufriayeksTcUTEGElah6KVoS8WZJB0E/AtYC7L1rnF9mWVBdUHkmAjItokaQfg2xSdnQQsBN5hu9Y1XElX287E/h2WBBsR0SZJc4AjbF9e7u8CfM32NtVGNj6SDgCmAZew/DJ811cWVB/IPdiIiPYNDCVXANu/ldQPk0xsTTGn8u4sayJ2uR8rKDXYiIgWJA3NYvRWYHXgbIoE9CZgse2RJqCoBUm3Uyxk8FjVsfST1GAjIlr7QtP+8Q2P+6GWMg+YAvyt6kD6SWqwERErOUmXAttQrHHbeA9276pi6gepwUZEjIGkV1Ms7bbaUJntE6uLqCOOb31IjFUSbEREmySdBqwB7AacDuwLXFNpUB1Qrmu7ETDN9i8lrQFMrjquuptUdQARETWys+23Av+y/QlgJ2CzimMaN0mHAj8CvlEWrQ/8tLqI+kMSbERE+x4tfz4i6TnA48CzK4ynU44AXgI8CGD7NuAZlUbUB9JEHBHRvgskTQFOBq6n6EF8erUhdcQS249JxbKvkp5Ef/SOrlR6EUdEtEnSk20vGXpM0dFp8VBZXUn6HMW0j2+lmPT/PcAC28dWGljNJcFGRLRJ0vW2t2tVVjeSJgGHAHtSzLF8se1vVhtV/aWJOCKiBUnPouj4s7qkF1IkIYB1KHoV192Rtk8Fnkiqkt5flsUKSg02IqIFSW8DDgZ2oJiMYSjBLgLOtP2TikLriBFq5jfYfmFVMfWDJNiIiDZJeoPtH1cdR6dI2h84ANgFuLzhqbWBQdsvrySwPpEm4oiI9m1QLra+iKI5dTvgGNuXVBvWCrsSuA94GsvPt7wImFNJRH0kNdiIiDZJusn2tpL+Ezgc+Djwvbp3coruSA02IqJ9Q/deXwV81/Z8DQ0erSFJixh+vKsA215ngkPqK0mwERHtu07SJcDGwEclrc2yBcprx/baVcfQz9JEHBHRpnK86HTgTtsLJa0HrG879yvj32Qu4oiIFiQdBGB7EFjd9sJy/x/Af1QZW/Su1GAjIlpoHCfaPGa0H2Zyiu5IDTYiojWN8Hi4/QggCTYioh0e4fFw+xFAmogjIlqS9AhwO0VtddPyMeX+JrbXrCq26F0ZphMR0drmVQcQ9ZMabEREh0i6yvZOVccRvSH3YCMiOme1qgOI3pEEGxHROWkSjCckwUZERHRBEmxEROdkTGw8IQk2IqJNkj7bouwtExhO9Lgk2IiI9u0xTNkrhx7YnjeBsUSPyzjYiIgWJL0beA+wiaTGlXPWBq6oJqrodRkHGxHRgqR1gacAnwGOaXhqke1/VhNV9Lok2IiIMZC0CzDN9rclPQ1Y2/ZdVccVvScJNiKiTZKOB3YAnm97M0nPAc6z/ZKKQ4selE5OERHtez2wN/AwgO0/U9yHjfg3SbAREe17zEWznwEkZRWdGFESbERE+86V9A1giqRDgV8C36w4puhRuQcbETEGkvYA9qSYteli2/+v4pCiRyXBRkREdEEmmoiIaEHSIor7rmL5FXME2PY6lQQWPS012IiIiC5IJ6eIiDZJ+l47ZRGQBBsRMRZbNu5IehKwfUWxRI9Lgo2IaEHSR8v7sNtIerDcFgF/Bc6vOLzoUbkHGxHRJkmfsf3RquOIekiCjYhok6T/GK7c9m8mOpbofUmwERFtkvSzht3VgBnAdbZ3ryik6GEZBxsR0Sbbr23cl7Qh8H8rCid6XDo5RUSsuHuAzasOInpTarAREW2S9GWWzeQ0CXghcH11EUUvS4KNiGjfAmBy+XghcLbtKyqMJ3pYEmxERAvlhBKfBt4B/Kksfi5whqRrbD9eWXDRs3IPNiKitZOBpwIb297O9nbAJsAU4POVRhY9K8N0IiJakHQbsJmb/mBKmgzcYntaNZFFL0sNNiKiNTcn17JwgOWXr4t4QhJsRERrCyS9tblQ0kHALRXEEzWQJuKIiBYkrQ/8BHgUuK4s3gFYHXi97Xurii16VxJsRESbJO3OsiXrFtj+VZXxRG9Lgo2IiOiC3IONiIjogiTYiIiILkiCjYiI6IIk2IiIiC74/5Z8ZKjUnzz0AAAAAElFTkSuQmCC\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "FQLPcAvs9RAx",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "outputId": "6183b13a-bc58-4ba4-ebe1-a445cd0b8e7a"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.regplot(x='Item_MRP',y='Item_Outlet_Sales',data=df_train)"
+      ],
+      "execution_count": 62,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f218a97a4d0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 62
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "x1LYy_ySdA6m"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "\n",
+        "1.   The plot shows that more the price of item, the better is its outlet sale.\n",
+        "2.   The relation is almost linear.\n",
+        "\n"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "JElgnCuz895Z",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 441
+        },
+        "outputId": "03d5a08e-a3f6-4643-a77c-c446df4b8e41"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.factorplot(x='Outlet_Type',y='Item_Outlet_Sales',hue='Outlet_Size',data=df_train)"
+      ],
+      "execution_count": 63,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:3717: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
+            "  warnings.warn(msg)\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<seaborn.axisgrid.FacetGrid at 0x7f218abfe7d0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 63
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 436x360 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "CZud8M-X9kYu",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 920
+        },
+        "outputId": "04c5fb19-538d-4253-cabf-960afac0ca58"
+      },
+      "cell_type": "code",
+      "source": [
+        "sns.pairplot(df_train)"
+      ],
+      "execution_count": 64,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<seaborn.axisgrid.PairGrid at 0x7f218a9020d0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 64
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 900x900 with 30 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "QieG6sOodZOS"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "The above plot shows all pair of relationship between all attributes"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "ZiX2JfFZ7T4H"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Feature Engineeering"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "Hk9Qtu4T7Zrx"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Converting categorical data into numerical"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "h1rqJmsq9tHP",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "837372b7-4b66-4eb5-95c0-8a00eac1f825"
+      },
+      "cell_type": "code",
+      "source": [
+        "# for training\n",
+        "df_y_train=df_train.copy()\n",
+        "df_y_train=df_train['Item_Outlet_Sales']\n",
+        "df_x_train=df_train.drop(['Item_Outlet_Sales'],axis=1)\n",
+        "\n",
+        "\n",
+        "df_x_train['Item_Fat_Content'].unique()\n",
+        "\n",
+        "def fun(x):\n",
+        "  if x=='Low Fat' or x=='LF' or x=='low fat':\n",
+        "    return(0)\n",
+        "  else:\n",
+        "    return(1)\n",
+        "\n",
+        "\n",
+        "def fun1(x):\n",
+        "  if x=='Medium':\n",
+        "    return(0)\n",
+        "  elif x=='High':\n",
+        "    return(1)\n",
+        "  else:\n",
+        "    return(2)\n",
+        "\n",
+        "def fun2(x):\n",
+        "  if x=='Tier 1':\n",
+        "    return(0)\n",
+        "  elif x=='Tier 2':\n",
+        "    return(1)\n",
+        "  else:\n",
+        "    return(2)   \n",
+        "\n",
+        "\n",
+        "def fun3(x):\n",
+        "  if x=='Supermarket Type1':\n",
+        "    return(0)\n",
+        "  elif x=='Supermarket Type2':\n",
+        "    return(1)\n",
+        "  elif x=='Supermarket Type3':\n",
+        "    return(2)\n",
+        "  else:\n",
+        "    return(3) \n",
+        "\n",
+        "\n",
+        "df_x_train['Item_Fat_Content']=df_x_train['Item_Fat_Content'].apply(fun)\n",
+        "df_x_train['Item_Fat_Content'].head()\n",
+        "df_x_train['Item_Type'].unique()\n",
+        "df_x_train['Outlet_Size'].unique()\n",
+        "df_x_train['Outlet_Size']=df_x_train['Outlet_Size'].apply(fun1)\n",
+        "df_x_train['Outlet_Size'].head()\n",
+        "df_x_train['Outlet_Location_Type'].unique()\n",
+        "df_x_train['Outlet_Location_Type']=df_x_train['Outlet_Location_Type'].apply(fun2)\n",
+        "df_x_train['Outlet_Location_Type'].head()\n",
+        "df_x_train['Outlet_Type'].unique()\n",
+        "df_x_train['Outlet_Type']=df_x_train['Outlet_Type'].apply(fun3)\n",
+        "df_x_train['Outlet_Type'].head()\n",
+        "df_x_train['Outlet_Identifier'].unique()\n",
+        "df_x_train1=pd.get_dummies(df_x_train['Outlet_Identifier'])\n",
+        "df_x_train=pd.concat([df_x_train,df_x_train1],axis=1)\n",
+        "df_x_train.columns"
+      ],
+      "execution_count": 163,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Index(['Item_Identifier', 'Item_Weight', 'Item_Fat_Content', 'Item_Visibility',\n",
+              "       'Item_Type', 'Item_MRP', 'Outlet_Identifier',\n",
+              "       'Outlet_Establishment_Year', 'Outlet_Size', 'Outlet_Location_Type',\n",
+              "       'Outlet_Type', 'OUT010', 'OUT013', 'OUT017', 'OUT018', 'OUT019',\n",
+              "       'OUT027', 'OUT035', 'OUT045', 'OUT046', 'OUT049'],\n",
+              "      dtype='object')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 163
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# for testing\n",
+        "\n",
+        "df_test['Item_Fat_Content'].unique()\n",
+        "\n",
+        "def fun(x):\n",
+        "  if x=='Low Fat' or x=='LF' or x=='low fat':\n",
+        "    return(0)\n",
+        "  else:\n",
+        "    return(1)\n",
+        "\n",
+        "\n",
+        "def fun1(x):\n",
+        "  if x=='Medium':\n",
+        "    return(0)\n",
+        "  elif x=='High':\n",
+        "    return(1)\n",
+        "  else:\n",
+        "    return(2)\n",
+        "\n",
+        "def fun2(x):\n",
+        "  if x=='Tier 1':\n",
+        "    return(0)\n",
+        "  elif x=='Tier 2':\n",
+        "    return(1)\n",
+        "  else:\n",
+        "    return(2)   \n",
+        "\n",
+        "\n",
+        "def fun3(x):\n",
+        "  if x=='Supermarket Type1':\n",
+        "    return(0)\n",
+        "  elif x=='Supermarket Type2':\n",
+        "    return(1)\n",
+        "  elif x=='Supermarket Type3':\n",
+        "    return(2)\n",
+        "  else:\n",
+        "    return(3) \n",
+        "\n",
+        "\n",
+        "df_test['Item_Fat_Content']=df_test['Item_Fat_Content'].apply(fun)\n",
+        "df_test['Item_Fat_Content'].head()\n",
+        "df_test['Item_Type'].unique()\n",
+        "df_test['Outlet_Size'].unique()\n",
+        "df_test['Outlet_Size']=df_test['Outlet_Size'].apply(fun1)\n",
+        "df_test['Outlet_Size'].head()\n",
+        "df_test['Outlet_Location_Type'].unique()\n",
+        "df_test['Outlet_Location_Type']=df_test['Outlet_Location_Type'].apply(fun2)\n",
+        "df_test['Outlet_Location_Type'].head()\n",
+        "df_test['Outlet_Type'].unique()\n",
+        "df_test['Outlet_Type']=df_test['Outlet_Type'].apply(fun3)\n",
+        "df_test['Outlet_Type'].head()\n",
+        "df_test['Outlet_Identifier'].unique()\n",
+        "df_test1=pd.get_dummies(df_test['Outlet_Identifier'])\n",
+        "df_test=pd.concat([df_test,df_test1],axis=1)\n",
+        "df_test.columns"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "hFpq_D_xMFJk",
+        "outputId": "3b1570cc-850a-4a13-d05a-6a05f6f9618d"
+      },
+      "execution_count": 164,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Index(['Item_Identifier', 'Item_Weight', 'Item_Fat_Content', 'Item_Visibility',\n",
+              "       'Item_Type', 'Item_MRP', 'Outlet_Identifier',\n",
+              "       'Outlet_Establishment_Year', 'Outlet_Size', 'Outlet_Location_Type',\n",
+              "       'Outlet_Type', 'OUT010', 'OUT013', 'OUT017', 'OUT018', 'OUT019',\n",
+              "       'OUT027', 'OUT035', 'OUT045', 'OUT046', 'OUT049'],\n",
+              "      dtype='object')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 164
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "DrnjWx1C6w5G",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 317
+        },
+        "outputId": "582bc089-8254-4798-c883-03a9f16bb8a4"
+      },
+      "cell_type": "code",
+      "source": [
+        "df_x_train.head()"
+      ],
+      "execution_count": 165,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "  Item_Identifier  Item_Weight  Item_Fat_Content  Item_Visibility  \\\n",
+              "0           FDA15         9.30                 0         0.016047   \n",
+              "1           DRC01         5.92                 1         0.019278   \n",
+              "2           FDN15        17.50                 0         0.016760   \n",
+              "3           FDX07        19.20                 1         0.000000   \n",
+              "4           NCD19         8.93                 0         0.000000   \n",
+              "\n",
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+        "outputId": "f585a2ff-2079-4186-ca7b-2b19a98fb7ed"
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+      "execution_count": 166,
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+              "  Item_Identifier  Item_Weight  Item_Fat_Content  Item_Visibility  \\\n",
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+              "     Item_Type  Item_MRP Outlet_Identifier  Outlet_Establishment_Year  \\\n",
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+              "<p>5 rows × 21 columns</p>\n",
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+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af09d499-32b6-4ab8-97f1-317319b683ef')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-af09d499-32b6-4ab8-97f1-317319b683ef 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-af09d499-32b6-4ab8-97f1-317319b683ef');\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": 166
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "BCXyOPATAPIU"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Feature selection"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "iRGYkIKQAgxx"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "From the co-relation map we plotted before, we can see that there almost no co-relation between 'Item_Identifier', 'Item_type' and 'Outlet_Establishment_year' with our target i.e 'Item_Outlet_sales'\n",
+        "\n",
+        "So we will drop these columns and will not use in training out model."
+      ]
+    },
+    {
+      "metadata": {
+        "id": "G1J39r8qCFe6"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Assigning data to X and Y variable"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "y7-xf7Ym7nGc"
+      },
+      "cell_type": "code",
+      "source": [
+        "x_train=df_x_train.drop(['Item_Identifier','Item_Type','Outlet_Establishment_Year','Outlet_Identifier'],axis=1)\n",
+        "x_test=df_test.drop(['Item_Identifier','Item_Type','Outlet_Establishment_Year','Outlet_Identifier'],axis=1)\n",
+        "y_train=df_y_train"
+      ],
+      "execution_count": 176,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "kr8Mw_XFDAlg",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 270
+        },
+        "outputId": "c65e29c3-c419-45e1-e1de-1ec69bb13060"
+      },
+      "cell_type": "code",
+      "source": [
+        "x_train.head()"
+      ],
+      "execution_count": 177,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "   Item_Weight  Item_Fat_Content  Item_Visibility  Item_MRP  Outlet_Size  \\\n",
+              "0         9.30                 0         0.016047  249.8092            0   \n",
+              "1         5.92                 1         0.019278   48.2692            0   \n",
+              "2        17.50                 0         0.016760  141.6180            0   \n",
+              "3        19.20                 1         0.000000  182.0950            0   \n",
+              "4         8.93                 0         0.000000   53.8614            1   \n",
+              "\n",
+              "   Outlet_Location_Type  Outlet_Type  OUT010  OUT013  OUT017  OUT018  OUT019  \\\n",
+              "0                     0            0       0       0       0       0       0   \n",
+              "1                     2            1       0       0       0       1       0   \n",
+              "2                     0            0       0       0       0       0       0   \n",
+              "3                     2            3       1       0       0       0       0   \n",
+              "4                     2            0       0       1       0       0       0   \n",
+              "\n",
+              "   OUT027  OUT035  OUT045  OUT046  OUT049  \n",
+              "0       0       0       0       0       1  \n",
+              "1       0       0       0       0       0  \n",
+              "2       0       0       0       0       1  \n",
+              "3       0       0       0       0       0  \n",
+              "4       0       0       0       0       0  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-a5617588-51f2-4347-b8f0-ddbdd77976f9\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
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+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Item_Weight</th>\n",
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+              "      <th>Outlet_Size</th>\n",
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+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>9.30</td>\n",
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+              "      <td>5.92</td>\n",
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+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>17.50</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.016760</td>\n",
+              "      <td>141.6180</td>\n",
+              "      <td>0</td>\n",
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+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>19.20</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>182.0950</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
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+              "      <td>0</td>\n",
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+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8.93</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>53.8614</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
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+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a5617588-51f2-4347-b8f0-ddbdd77976f9')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
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+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-a5617588-51f2-4347-b8f0-ddbdd77976f9 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-a5617588-51f2-4347-b8f0-ddbdd77976f9');\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": 177
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "cUiK6NSJDFNw",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "7c36e747-246b-41a6-cb6d-ab547b68a513"
+      },
+      "cell_type": "code",
+      "source": [
+        "y_train.head()"
+      ],
+      "execution_count": 178,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0    3735.1380\n",
+              "1     443.4228\n",
+              "2    2097.2700\n",
+              "3     732.3800\n",
+              "4     994.7052\n",
+              "Name: Item_Outlet_Sales, dtype: float64"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 178
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "x_test.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 270
+        },
+        "id": "0__ej_rQKRKH",
+        "outputId": "1a8a5302-d7ee-40aa-96c8-e20c4da150e1"
+      },
+      "execution_count": 179,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "   Item_Weight  Item_Fat_Content  Item_Visibility  Item_MRP  Outlet_Size  \\\n",
+              "0    20.750000                 0         0.007565  107.8622            0   \n",
+              "1     8.300000                 1         0.038428   87.3198            0   \n",
+              "2    14.600000                 0         0.099575  241.7538            0   \n",
+              "3     7.315000                 0         0.015388  155.0340            0   \n",
+              "4    12.695633                 1         0.118599  234.2300            0   \n",
+              "\n",
+              "   Outlet_Location_Type  Outlet_Type  OUT010  OUT013  OUT017  OUT018  OUT019  \\\n",
+              "0                     0            0       0       0       0       0       0   \n",
+              "1                     1            0       0       0       1       0       0   \n",
+              "2                     2            3       1       0       0       0       0   \n",
+              "3                     1            0       0       0       1       0       0   \n",
+              "4                     2            2       0       0       0       0       0   \n",
+              "\n",
+              "   OUT027  OUT035  OUT045  OUT046  OUT049  \n",
+              "0       0       0       0       0       1  \n",
+              "1       0       0       0       0       0  \n",
+              "2       0       0       0       0       0  \n",
+              "3       0       0       0       0       0  \n",
+              "4       1       0       0       0       0  "
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+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
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+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
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+              "      <th>Item_Visibility</th>\n",
+              "      <th>Item_MRP</th>\n",
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+              "      <th>OUT010</th>\n",
+              "      <th>OUT013</th>\n",
+              "      <th>OUT017</th>\n",
+              "      <th>OUT018</th>\n",
+              "      <th>OUT019</th>\n",
+              "      <th>OUT027</th>\n",
+              "      <th>OUT035</th>\n",
+              "      <th>OUT045</th>\n",
+              "      <th>OUT046</th>\n",
+              "      <th>OUT049</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>20.750000</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.007565</td>\n",
+              "      <td>107.8622</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>8.300000</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.038428</td>\n",
+              "      <td>87.3198</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>14.600000</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.099575</td>\n",
+              "      <td>241.7538</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>7.315000</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.015388</td>\n",
+              "      <td>155.0340</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>12.695633</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.118599</td>\n",
+              "      <td>234.2300</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-da5576d9-f43b-49d4-8d88-a5e69a28082d')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\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",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-da5576d9-f43b-49d4-8d88-a5e69a28082d 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-da5576d9-f43b-49d4-8d88-a5e69a28082d');\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": 179
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "08LmFRbIKvn5"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Linear Regression Model"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "7BiGs39gDwZB"
+      },
+      "cell_type": "code",
+      "source": [
+        "from sklearn.linear_model import LinearRegression"
+      ],
+      "execution_count": 181,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "YniOMgvzHWYX"
+      },
+      "cell_type": "code",
+      "source": [
+        "lrm=LinearRegression()"
+      ],
+      "execution_count": 182,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "Z9z9PDULHhY1",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "da5ecce5-b403-4d65-e856-475c5979be3b"
+      },
+      "cell_type": "code",
+      "source": [
+        "lrm.fit(x_train,y_train)"
+      ],
+      "execution_count": 184,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "LinearRegression()"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 184
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "QstO5DPgHj-j"
+      },
+      "cell_type": "code",
+      "source": [
+        "predicted=lrm.predict(x_test)"
+      ],
+      "execution_count": 186,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "ts4kgFueK0JN"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Random Forest Regressor"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "fXu0b6u5JAQu"
+      },
+      "cell_type": "code",
+      "source": [
+        "from sklearn.ensemble import RandomForestRegressor"
+      ],
+      "execution_count": 190,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "mG6Fy65TLCeR"
+      },
+      "cell_type": "code",
+      "source": [
+        "rfg=RandomForestRegressor()"
+      ],
+      "execution_count": 191,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "rU8JnWSYLMS2",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "6291b6e8-e88e-4b00-e3f1-ae3e441acb1c"
+      },
+      "cell_type": "code",
+      "source": [
+        "rfg.fit(x_train,y_train)"
+      ],
+      "execution_count": 192,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "RandomForestRegressor()"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 192
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "8Z2KLz7YLZpQ"
+      },
+      "cell_type": "code",
+      "source": [
+        "predicted=rfg.predict(x_test)"
+      ],
+      "execution_count": 193,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# XG Boost Regression"
+      ],
+      "metadata": {
+        "id": "EDUK8C8bAB2T"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from numpy import loadtxt\n",
+        "from xgboost import XGBRegressor"
+      ],
+      "metadata": {
+        "id": "j2HvcB0gATJ2"
+      },
+      "execution_count": 194,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "model = XGBRegressor()\n",
+        "model.fit(x_train, y_train)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "g1rDX_ukTydw",
+        "outputId": "25a7a3ad-6933-4408-da95-6d72ac3e7bd1"
+      },
+      "execution_count": 195,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[20:01:03] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "XGBRegressor()"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 195
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "predicted=model.predict(x_test)"
+      ],
+      "metadata": {
+        "id": "lgAzVVMTT2IM"
+      },
+      "execution_count": 196,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "Zth3G9rOMwYA"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Ada Boost Regression"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "JxlDVFjILnWO"
+      },
+      "cell_type": "code",
+      "source": [
+        "from sklearn.ensemble import AdaBoostRegressor"
+      ],
+      "execution_count": 197,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "rSoxRGSuM6WA"
+      },
+      "cell_type": "code",
+      "source": [
+        "abr=AdaBoostRegressor(n_estimators=70)"
+      ],
+      "execution_count": 198,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "WZrrJKEyM9dW",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "86523bee-357c-4561-d1ba-4b159254082b"
+      },
+      "cell_type": "code",
+      "source": [
+        "abr.fit(x_train,y_train)"
+      ],
+      "execution_count": 199,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "AdaBoostRegressor(n_estimators=70)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 199
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "y76Ryi8uNNe6"
+      },
+      "cell_type": "code",
+      "source": [
+        "predicted=abr.predict(x_test)"
+      ],
+      "execution_count": 200,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "fRHoHtBZOHKa"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Bagging Regressor"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "BoyXRClzNeA5"
+      },
+      "cell_type": "code",
+      "source": [
+        "from sklearn.ensemble import BaggingRegressor"
+      ],
+      "execution_count": 201,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "rwKFQ4uFOa2t"
+      },
+      "cell_type": "code",
+      "source": [
+        "br=BaggingRegressor(n_estimators=30)"
+      ],
+      "execution_count": 202,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "gRp5NkzSOebP",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "aa6cc016-13b5-450e-cb85-ed1ae1678caf"
+      },
+      "cell_type": "code",
+      "source": [
+        "br.fit(x_train,y_train)"
+      ],
+      "execution_count": 203,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "BaggingRegressor(n_estimators=30)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 203
+        }
+      ]
+    },
+    {
+      "metadata": {
+        "id": "Hka8t006OpKN"
+      },
+      "cell_type": "code",
+      "source": [
+        "predicted=br.predict(x_test)"
+      ],
+      "execution_count": 204,
+      "outputs": []
+    },
+    {
+      "metadata": {
+        "id": "M3ecpQ7tQVyJ"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "##Summary"
+      ]
+    },
+    {
+      "metadata": {
+        "id": "LQVVxqKaQa6y"
+      },
+      "cell_type": "markdown",
+      "source": [
+        "Firstly we studied about the dataset i.e Big Mart Sales Analysis and understood the meaning of each columns. Then we performed Exploratory Data Analysis on our dataset. We plotted various Univariate and Bi-variate plots to study the relationship between various features. Then we cleaned our data and also performed feature enginnering.                                                                                              \n",
+        "We trained our model and predicted values for Outlet_sales."
+      ]
+    }
+  ]
+}
\ No newline at end of file