clean_notebook2.ipynb

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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)"
      ],
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        "id": "8ZwXrNS0w3Mu"
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      "execution_count": 10,
      "outputs": []
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    {
      "cell_type": "code",
      "source": [
        "sales = pd.read_csv('Sales.csv', sep=\",\", encoding=\"ISO-8859-1\", header=0)"
      ],
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      "execution_count": 11,
      "outputs": []
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      "cell_type": "code",
      "source": [
        "sales.head()"
      ],
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      "execution_count": 12,
      "outputs": [
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          "data": {
            "text/plain": [
              "        outlet_id  transaction_time expected_rainfall         freezer_status  \\\n",
              "0  outlet_code_78  2023-01-05 12:41              25mm    freezers available    \n",
              "1  outlet_code_78  2023-01-12 13:05               0mm    freezers available    \n",
              "2  outlet_code_78   2023-01-17 9:32              79mm    freezers available    \n",
              "3  outlet_code_78  2023-01-27 14:21          194.51mm    freezers available    \n",
              "4  outlet_code_78  2023-01-31 16:24              15mm    freezers available    \n",
              "\n",
              "             sku_name  sales_quantity  \n",
              "0  Sweet Delights Mix             3.0  \n",
              "1  Sweet Delights Mix             3.0  \n",
              "2  Sweet Delights Mix             3.0  \n",
              "3  Sweet Delights Mix             2.0  \n",
              "4  Sweet Delights Mix             3.0  "
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          },
          "metadata": {},
          "execution_count": 12
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "outlet_df = pd.read_csv('Outlet Info.csv', sep=\",\", encoding=\"ISO-8859-1\", header=0)\n",
        "outlet_df.head()"
      ],
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      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       outlet_id      region  outlet_size  population_density  \\\n",
              "0  outlet_code_1  outstation         1334                 276   \n",
              "1  outlet_code_2  outstation         1336                 276   \n",
              "2  outlet_code_3  outstation         1341                 277   \n",
              "3  outlet_code_4  outstation         1025                 239   \n",
              "4  outlet_code_5   upcountry         3965                 646   \n",
              "\n",
              "   number_of_skus_sold  average_household_income  \n",
              "0                   16                     81704  \n",
              "1                   16                     81789  \n",
              "2                   16                     82046  \n",
              "3                   13                     66259  \n",
              "4                   35                     59469  "
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              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-5f9e1bfd-6583-46ad-ba77-e4d1cd329062 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-5f9e1bfd-6583-46ad-ba77-e4d1cd329062');\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",
              "\n",
              "\n",
              "<div id=\"df-2b7af516-1608-4996-b142-bca531244688\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2b7af516-1608-4996-b142-bca531244688')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2b7af516-1608-4996-b142-bca531244688 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mapping = pd.read_csv(\"Distributor Outlet Mapping.csv\")"
      ],
      "metadata": {
        "execution": {
          "iopub.status.busy": "2023-12-16T03:33:12.608794Z",
          "iopub.execute_input": "2023-12-16T03:33:12.609206Z",
          "iopub.status.idle": "2023-12-16T03:33:12.624186Z",
          "shell.execute_reply.started": "2023-12-16T03:33:12.609176Z",
          "shell.execute_reply": "2023-12-16T03:33:12.623094Z"
        },
        "trusted": true,
        "id": "9qkaTvIQw3Mz"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mapping.head()"
      ],
      "metadata": {
        "execution": {
          "iopub.status.busy": "2023-12-16T03:33:18.426589Z",
          "iopub.execute_input": "2023-12-16T03:33:18.426968Z",
          "iopub.status.idle": "2023-12-16T03:33:18.438069Z",
          "shell.execute_reply.started": "2023-12-16T03:33:18.426942Z",
          "shell.execute_reply": "2023-12-16T03:33:18.436729Z"
        },
        "trusted": true,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "IsQq4q56w3Mz",
        "outputId": "c668ca1e-c61f-4314-93f0-b572c1434e09"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   distributor_id      outlet_id\n",
              "0  distributor_24  outlet_code_1\n",
              "1  distributor_24  outlet_code_2\n",
              "2  distributor_24  outlet_code_3\n",
              "3   distributor_3  outlet_code_4\n",
              "4  distributor_21  outlet_code_5"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f23eac49-279c-4354-8cd1-d2bf9bb29f07\" 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>distributor_id</th>\n",
              "      <th>outlet_id</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>distributor_24</td>\n",
              "      <td>outlet_code_1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>distributor_24</td>\n",
              "      <td>outlet_code_2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>distributor_24</td>\n",
              "      <td>outlet_code_3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>distributor_3</td>\n",
              "      <td>outlet_code_4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>distributor_21</td>\n",
              "      <td>outlet_code_5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f23eac49-279c-4354-8cd1-d2bf9bb29f07')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-f23eac49-279c-4354-8cd1-d2bf9bb29f07 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-f23eac49-279c-4354-8cd1-d2bf9bb29f07');\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",
              "\n",
              "\n",
              "<div id=\"df-585bd562-bbeb-4f3b-81f2-bffc47067893\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-585bd562-bbeb-4f3b-81f2-bffc47067893')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-585bd562-bbeb-4f3b-81f2-bffc47067893 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "sales.info()"
      ],
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        "execution": {
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          "shell.execute_reply": "2023-12-16T03:39:35.722328Z"
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        "id": "mGRttQ3_w3Mz",
        "outputId": "7eb23a57-0640-4525-b5aa-f29df518232b"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 137348 entries, 0 to 137347\n",
            "Data columns (total 6 columns):\n",
            " #   Column             Non-Null Count   Dtype  \n",
            "---  ------             --------------   -----  \n",
            " 0   outlet_id          137348 non-null  object \n",
            " 1   transaction_time   137348 non-null  object \n",
            " 2   expected_rainfall  137348 non-null  object \n",
            " 3   freezer_status     137348 non-null  object \n",
            " 4   sku_name           137347 non-null  object \n",
            " 5   sales_quantity     137347 non-null  float64\n",
            "dtypes: float64(1), object(5)\n",
            "memory usage: 6.3+ MB\n"
          ]
        }
      ]
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    {
      "cell_type": "code",
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        "outlet_df.info()"
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      "metadata": {
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          "iopub.status.busy": "2023-12-16T03:41:50.449570Z",
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      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 4200 entries, 0 to 4199\n",
            "Data columns (total 6 columns):\n",
            " #   Column                    Non-Null Count  Dtype \n",
            "---  ------                    --------------  ----- \n",
            " 0   outlet_id                 4200 non-null   object\n",
            " 1   region                    4200 non-null   object\n",
            " 2   outlet_size               4200 non-null   int64 \n",
            " 3   population_density        4200 non-null   int64 \n",
            " 4   number_of_skus_sold       4200 non-null   int64 \n",
            " 5   average_household_income  4200 non-null   int64 \n",
            "dtypes: int64(4), object(2)\n",
            "memory usage: 197.0+ KB\n"
          ]
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "sales[sales[\"outlet_id\"] == \"outlet_code_1\"]"
      ],
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        "execution": {
          "iopub.status.busy": "2023-12-16T03:43:59.219549Z",
          "iopub.execute_input": "2023-12-16T03:43:59.220165Z",
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      "execution_count": 18,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           outlet_id  transaction_time expected_rainfall  \\\n",
              "41348  outlet_code_1  2023-01-06 10:51              60mm   \n",
              "41349  outlet_code_1  2023-01-12 15:14               6mm   \n",
              "41350  outlet_code_1  2023-01-16 16:25              82mm   \n",
              "41351  outlet_code_1   2023-01-24 8:55          172.53mm   \n",
              "41352  outlet_code_1   2023-02-04 9:53              59mm   \n",
              "41353  outlet_code_1  2023-02-10 10:01              15mm   \n",
              "41354  outlet_code_1  2023-02-18 12:09              33mm   \n",
              "41355  outlet_code_1  2023-02-23 16:16               4mm   \n",
              "41356  outlet_code_1   2023-03-02 9:50          178.29mm   \n",
              "41357  outlet_code_1  2023-03-08 12:49               3mm   \n",
              "41358  outlet_code_1  2023-03-16 15:27              57mm   \n",
              "41359  outlet_code_1  2023-03-24 16:43          179.54mm   \n",
              "41360  outlet_code_1  2023-03-29 16:26              28mm   \n",
              "41361  outlet_code_1  2023-04-08 15:35              50mm   \n",
              "41362  outlet_code_1   2023-04-13 9:47              48mm   \n",
              "41363  outlet_code_1  2023-04-17 16:02          164.57mm   \n",
              "41364  outlet_code_1  2023-04-29 12:59              86mm   \n",
              "41365  outlet_code_1  2023-05-02 11:38              32mm   \n",
              "41366  outlet_code_1  2023-05-13 13:24          186.24mm   \n",
              "41367  outlet_code_1  2023-05-19 14:50              46mm   \n",
              "41368  outlet_code_1  2023-05-22 10:24               6mm   \n",
              "41369  outlet_code_1  2023-05-31 12:45              28mm   \n",
              "\n",
              "             freezer_status           sku_name  sales_quantity  \n",
              "41348   freezers available   Fruit Chewy Bites             4.0  \n",
              "41349   freezers available   Fruit Chewy Bites             5.0  \n",
              "41350   freezers available   Fruit Chewy Bites             5.0  \n",
              "41351   freezers available   Fruit Chewy Bites             7.0  \n",
              "41352   freezers available   Fruit Chewy Bites             5.0  \n",
              "41353   freezers available   Fruit Chewy Bites            10.0  \n",
              "41354   freezers available   Fruit Chewy Bites             7.0  \n",
              "41355   freezers available   Fruit Chewy Bites             7.0  \n",
              "41356   freezers available   Fruit Chewy Bites             7.0  \n",
              "41357   freezers available   Fruit Chewy Bites            10.0  \n",
              "41358   freezers available   Fruit Chewy Bites             6.0  \n",
              "41359   freezers available   Fruit Chewy Bites             6.0  \n",
              "41360   freezers available   Fruit Chewy Bites            12.0  \n",
              "41361   freezers available   Fruit Chewy Bites            12.0  \n",
              "41362   freezers available   Fruit Chewy Bites             7.0  \n",
              "41363   freezers available   Fruit Chewy Bites             6.0  \n",
              "41364   freezers available   Fruit Chewy Bites            13.0  \n",
              "41365   freezers available   Fruit Chewy Bites            13.0  \n",
              "41366   freezers available   Fruit Chewy Bites             6.0  \n",
              "41367   freezers available   Fruit Chewy Bites            11.0  \n",
              "41368   freezers available   Fruit Chewy Bites             8.0  \n",
              "41369   freezers available   Fruit Chewy Bites            13.0  "
            ],
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>outlet_id</th>\n",
              "      <th>transaction_time</th>\n",
              "      <th>expected_rainfall</th>\n",
              "      <th>freezer_status</th>\n",
              "      <th>sku_name</th>\n",
              "      <th>sales_quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>41348</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-01-06 10:51</td>\n",
              "      <td>60mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41349</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-01-12 15:14</td>\n",
              "      <td>6mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41350</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-01-16 16:25</td>\n",
              "      <td>82mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41351</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-01-24 8:55</td>\n",
              "      <td>172.53mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41352</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-02-04 9:53</td>\n",
              "      <td>59mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41353</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-02-10 10:01</td>\n",
              "      <td>15mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41354</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-02-18 12:09</td>\n",
              "      <td>33mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41355</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-02-23 16:16</td>\n",
              "      <td>4mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41356</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-03-02 9:50</td>\n",
              "      <td>178.29mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41357</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-03-08 12:49</td>\n",
              "      <td>3mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41358</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-03-16 15:27</td>\n",
              "      <td>57mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41359</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-03-24 16:43</td>\n",
              "      <td>179.54mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41360</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-03-29 16:26</td>\n",
              "      <td>28mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41361</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-04-08 15:35</td>\n",
              "      <td>50mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41362</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-04-13 9:47</td>\n",
              "      <td>48mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41363</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-04-17 16:02</td>\n",
              "      <td>164.57mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41364</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-04-29 12:59</td>\n",
              "      <td>86mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41365</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-05-02 11:38</td>\n",
              "      <td>32mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>13.0</td>\n",
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              "    <tr>\n",
              "      <th>41366</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-05-13 13:24</td>\n",
              "      <td>186.24mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>6.0</td>\n",
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              "    <tr>\n",
              "      <th>41367</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-05-19 14:50</td>\n",
              "      <td>46mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41368</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-05-22 10:24</td>\n",
              "      <td>6mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>8.0</td>\n",
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              "    <tr>\n",
              "      <th>41369</th>\n",
              "      <td>outlet_code_1</td>\n",
              "      <td>2023-05-31 12:45</td>\n",
              "      <td>28mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>13.0</td>\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7d504044-b657-4845-a1f1-81c19513108a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "merged_df = pd.merge(sales, outlet_df, on=\"outlet_id\")"
      ],
      "metadata": {
        "execution": {
          "iopub.status.busy": "2023-12-16T03:45:32.735310Z",
          "iopub.execute_input": "2023-12-16T03:45:32.735891Z",
          "iopub.status.idle": "2023-12-16T03:45:32.939397Z",
          "shell.execute_reply.started": "2023-12-16T03:45:32.735844Z",
          "shell.execute_reply": "2023-12-16T03:45:32.937754Z"
        },
        "trusted": true,
        "id": "epvU0qzNw3M0"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "merged_df.info()"
      ],
      "metadata": {
        "execution": {
          "iopub.status.busy": "2023-12-16T03:44:36.006611Z",
          "iopub.execute_input": "2023-12-16T03:44:36.007097Z",
          "iopub.status.idle": "2023-12-16T03:44:36.168062Z",
          "shell.execute_reply.started": "2023-12-16T03:44:36.007058Z",
          "shell.execute_reply": "2023-12-16T03:44:36.166825Z"
        },
        "trusted": true,
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-7-ieBYnw3M0",
        "outputId": "ee94a8b4-4f04-49cc-d875-af81934c1ce2"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 137348 entries, 0 to 137347\n",
            "Data columns (total 11 columns):\n",
            " #   Column                    Non-Null Count   Dtype  \n",
            "---  ------                    --------------   -----  \n",
            " 0   outlet_id                 137348 non-null  object \n",
            " 1   transaction_time          137348 non-null  object \n",
            " 2   expected_rainfall         137348 non-null  object \n",
            " 3   freezer_status            137348 non-null  object \n",
            " 4   sku_name                  137347 non-null  object \n",
            " 5   sales_quantity            137347 non-null  float64\n",
            " 6   region                    137348 non-null  object \n",
            " 7   outlet_size               137348 non-null  int64  \n",
            " 8   population_density        137348 non-null  int64  \n",
            " 9   number_of_skus_sold       137348 non-null  int64  \n",
            " 10  average_household_income  137348 non-null  int64  \n",
            "dtypes: float64(1), int64(4), object(6)\n",
            "memory usage: 12.6+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "merged_df.to_csv(\"output_file.csv\",index=False, encoding=\"ISO-8859-1\")"
      ],
      "metadata": {
        "execution": {
          "iopub.status.busy": "2023-12-16T03:47:47.216877Z",
          "iopub.execute_input": "2023-12-16T03:47:47.217378Z",
          "iopub.status.idle": "2023-12-16T03:47:49.221266Z",
          "shell.execute_reply.started": "2023-12-16T03:47:47.217343Z",
          "shell.execute_reply": "2023-12-16T03:47:49.220339Z"
        },
        "trusted": true,
        "id": "NCPII47Aw3M1"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"output_file.csv\")"
      ],
      "metadata": {
        "id": "WlotICALw3M1"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(6)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "id": "ffehwUo5zywO",
        "outputId": "6af60c01-18f7-4a4d-c7da-ebf221881f12"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        outlet_id  transaction_time expected_rainfall         freezer_status  \\\n",
              "0  outlet_code_78  2023-01-05 12:41              25mm    freezers available    \n",
              "1  outlet_code_78  2023-01-12 13:05               0mm    freezers available    \n",
              "2  outlet_code_78   2023-01-17 9:32              79mm    freezers available    \n",
              "3  outlet_code_78  2023-01-27 14:21          194.51mm    freezers available    \n",
              "4  outlet_code_78  2023-01-31 16:24              15mm    freezers available    \n",
              "5  outlet_code_78  2023-02-08 12:44              94mm    freezers available    \n",
              "\n",
              "             sku_name  sales_quantity      region  outlet_size  \\\n",
              "0  Sweet Delights Mix             3.0  outstation         2870   \n",
              "1  Sweet Delights Mix             3.0  outstation         2870   \n",
              "2  Sweet Delights Mix             3.0  outstation         2870   \n",
              "3  Sweet Delights Mix             2.0  outstation         2870   \n",
              "4  Sweet Delights Mix             3.0  outstation         2870   \n",
              "5  Sweet Delights Mix             3.0  outstation         2870   \n",
              "\n",
              "   population_density  number_of_skus_sold  average_household_income  \n",
              "0                 344                   14                     71756  \n",
              "1                 344                   14                     71756  \n",
              "2                 344                   14                     71756  \n",
              "3                 344                   14                     71756  \n",
              "4                 344                   14                     71756  \n",
              "5                 344                   14                     71756  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-bcfbf6d8-007d-4bfa-85e0-b131f658dad5\" 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",
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              "\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>outlet_id</th>\n",
              "      <th>transaction_time</th>\n",
              "      <th>expected_rainfall</th>\n",
              "      <th>freezer_status</th>\n",
              "      <th>sku_name</th>\n",
              "      <th>sales_quantity</th>\n",
              "      <th>region</th>\n",
              "      <th>outlet_size</th>\n",
              "      <th>population_density</th>\n",
              "      <th>number_of_skus_sold</th>\n",
              "      <th>average_household_income</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>2023-01-05 12:41</td>\n",
              "      <td>25mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>outstation</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>2023-01-12 13:05</td>\n",
              "      <td>0mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>outstation</td>\n",
              "      <td>2870</td>\n",
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              "      <td>71756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>2023-01-17 9:32</td>\n",
              "      <td>79mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>outstation</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>2023-01-27 14:21</td>\n",
              "      <td>194.51mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>2.0</td>\n",
              "      <td>outstation</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>2023-01-31 16:24</td>\n",
              "      <td>15mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>outstation</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>2023-02-08 12:44</td>\n",
              "      <td>94mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>outstation</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bcfbf6d8-007d-4bfa-85e0-b131f658dad5')\"\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",
              "      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",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-bcfbf6d8-007d-4bfa-85e0-b131f658dad5 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-bcfbf6d8-007d-4bfa-85e0-b131f658dad5');\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",
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              "\n",
              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
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              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
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              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
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              "    80% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
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              "    }\n",
              "  }\n",
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              "\n",
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              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8c67de22-573f-430f-a261-7878b1a8df26 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.tail()"
      ],
      "metadata": {
        "id": "6a_im0_80XOS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "outputId": "a185a63a-502a-43f2-b14b-6244647d456d"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               outlet_id  transaction_time expected_rainfall  \\\n",
              "137343  outlet_code_3057  2023-04-28 13:16              32mm   \n",
              "137344  outlet_code_3057   2023-05-01 9:51              59mm   \n",
              "137345  outlet_code_3057  2023-05-09 16:39           81.02mm   \n",
              "137346  outlet_code_3057   2023-05-18 9:03               4mm   \n",
              "137347  outlet_code_3057  2023-05-24 14:41              43mm   \n",
              "\n",
              "              freezer_status           sku_name  sales_quantity   region  \\\n",
              "137343   freezers available   Fruit Chewy Bites            16.0  western   \n",
              "137344   freezers available   Fruit Chewy Bites            19.0  western   \n",
              "137345   freezers available   Fruit Chewy Bites            16.0  western   \n",
              "137346   freezers available   Fruit Chewy Bites            15.0  western   \n",
              "137347   freezers available   Fruit Chewy Bites            24.0  western   \n",
              "\n",
              "        outlet_size  population_density  number_of_skus_sold  \\\n",
              "137343         1133                2066                   35   \n",
              "137344         1133                2066                   35   \n",
              "137345         1133                2066                   35   \n",
              "137346         1133                2066                   35   \n",
              "137347         1133                2066                   35   \n",
              "\n",
              "        average_household_income  \n",
              "137343                    118301  \n",
              "137344                    118301  \n",
              "137345                    118301  \n",
              "137346                    118301  \n",
              "137347                    118301  "
            ],
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              "      <th>outlet_id</th>\n",
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              "      <th>expected_rainfall</th>\n",
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              "      <td>outlet_code_3057</td>\n",
              "      <td>2023-04-28 13:16</td>\n",
              "      <td>32mm</td>\n",
              "      <td>freezers available</td>\n",
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              "      <td>59mm</td>\n",
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              "      <td>western</td>\n",
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              "    <tr>\n",
              "      <th>137346</th>\n",
              "      <td>outlet_code_3057</td>\n",
              "      <td>2023-05-18 9:03</td>\n",
              "      <td>4mm</td>\n",
              "      <td>freezers available</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>15.0</td>\n",
              "      <td>western</td>\n",
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              "    <tr>\n",
              "      <th>137347</th>\n",
              "      <td>outlet_code_3057</td>\n",
              "      <td>2023-05-24 14:41</td>\n",
              "      <td>43mm</td>\n",
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              "      <td>24.0</td>\n",
              "      <td>western</td>\n",
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              "                                                    [key], {});\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    height: 32px;\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a2ebc8ea-7e68-4eac-8bd6-3be7eeaf972e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UHWztVxWz0UO",
        "outputId": "2af0eee8-7c83-43f2-ba44-eedb9d56c724"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(137348, 11)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.nunique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ozXz5uerz6m2",
        "outputId": "68a3ebf5-2bbd-4256-e2d2-8291c5c56362"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "outlet_id                    4200\n",
              "transaction_time            62092\n",
              "expected_rainfall            9704\n",
              "freezer_status                  4\n",
              "sku_name                        4\n",
              "sales_quantity                 66\n",
              "region                          3\n",
              "outlet_size                  1640\n",
              "population_density           1559\n",
              "number_of_skus_sold            51\n",
              "average_household_income     4125\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"expected_rainfall_num\"] = pd.to_numeric(df[\"expected_rainfall\"].str.replace(\"mm\", \"\"), errors=\"coerce\")"
      ],
      "metadata": {
        "id": "BiABXd2M1fKG"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "9dZOWRsy2_Fq",
        "outputId": "ba7223ae-63ec-4573-810a-f2b1d70fec05"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-28-2f6f6606aa2c>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  df.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          sales_quantity  outlet_size  population_density  \\\n",
              "sales_quantity                  1.000000     0.376421            0.426136   \n",
              "outlet_size                     0.376421     1.000000            0.259453   \n",
              "population_density              0.426136     0.259453            1.000000   \n",
              "number_of_skus_sold             0.359745     0.220011            0.906953   \n",
              "average_household_income        0.308166     0.189437            0.806620   \n",
              "expected_rainfall_num          -0.088617    -0.006649           -0.141811   \n",
              "\n",
              "                          number_of_skus_sold  average_household_income  \\\n",
              "sales_quantity                       0.359745                  0.308166   \n",
              "outlet_size                          0.220011                  0.189437   \n",
              "population_density                   0.906953                  0.806620   \n",
              "number_of_skus_sold                  1.000000                  0.837900   \n",
              "average_household_income             0.837900                  1.000000   \n",
              "expected_rainfall_num               -0.130893                 -0.122101   \n",
              "\n",
              "                          expected_rainfall_num  \n",
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          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def clean_freezer(df: pd.DataFrame) -> pd.DataFrame:\n",
        "    unique_values = np.unique(df[\"freezer_status\"])\n",
        "    values = np.array(unique_values, dtype=str)\n",
        "\n",
        "    replacement_dict = {value: 'freezers available' for value in values if value.strip() == 'freezers available'}\n",
        "    replacement_dict_2 = {'freezers available': 1, ' nofreezers available': 0}\n",
        "\n",
        "    df[\"freezer_status\"] = df[\"freezer_status\"].replace(replacement_dict, regex=True)\n",
        "\n",
        "    df[\"freezer_status\"] = df[\"freezer_status\"].replace(replacement_dict_2)\n",
        "\n",
        "    return df\n",
        "\n",
        "df = clean_freezer(df)\n",
        "df.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "id": "BIDbjEWD3BKe",
        "outputId": "1c9cd8b0-f579-49b5-95d2-be2cf3ee37ac"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-29-8972a620afb8>:15: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  df.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          freezer_status  sales_quantity  outlet_size  \\\n",
              "freezer_status                  1.000000        0.452458     0.625314   \n",
              "sales_quantity                  0.452458        1.000000     0.376421   \n",
              "outlet_size                     0.625314        0.376421     1.000000   \n",
              "population_density              0.127867        0.426136     0.259453   \n",
              "number_of_skus_sold             0.111072        0.359745     0.220011   \n",
              "average_household_income        0.001667        0.308166     0.189437   \n",
              "expected_rainfall_num          -0.011928       -0.088617    -0.006649   \n",
              "\n",
              "                          population_density  number_of_skus_sold  \\\n",
              "freezer_status                      0.127867             0.111072   \n",
              "sales_quantity                      0.426136             0.359745   \n",
              "outlet_size                         0.259453             0.220011   \n",
              "population_density                  1.000000             0.906953   \n",
              "number_of_skus_sold                 0.906953             1.000000   \n",
              "average_household_income            0.806620             0.837900   \n",
              "expected_rainfall_num              -0.141811            -0.130893   \n",
              "\n",
              "                          average_household_income  expected_rainfall_num  \n",
              "freezer_status                            0.001667              -0.011928  \n",
              "sales_quantity                            0.308166              -0.088617  \n",
              "outlet_size                               0.189437              -0.006649  \n",
              "population_density                        0.806620              -0.141811  \n",
              "number_of_skus_sold                       0.837900              -0.130893  \n",
              "average_household_income                  1.000000              -0.122101  \n",
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              "    .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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-1a223195-547d-4253-94e4-637ed1dad47a 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-1a223195-547d-4253-94e4-637ed1dad47a');\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",
              "\n",
              "\n",
              "<div id=\"df-e9ee2956-526b-457d-a78f-651796e29398\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e9ee2956-526b-457d-a78f-651796e29398')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e9ee2956-526b-457d-a78f-651796e29398 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def clean_outlet_region(df: pd.DataFrame) -> pd.DataFrame:\n",
        "    encoded = pd.get_dummies(df['region'], prefix='region')\n",
        "    df = pd.concat([df, encoded], axis=1)\n",
        "    df = df.drop(columns=['region'])\n",
        "    df = df.replace({True: 1, False: 0})\n",
        "\n",
        "    return df\n",
        "\n",
        "df = clean_outlet_region(df)"
      ],
      "metadata": {
        "id": "SGxFPE9v3mGY"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def convert_to_date(df: pd.DataFrame):\n",
        "\n",
        "    df[\"transaction_time\"] = pd.to_datetime(df[\"transaction_time\"], format='%Y-%m-%d %H:%M', errors='coerce')\n",
        "\n",
        "    # If you want to extract the week number\n",
        "    df[\"transaction_time\"] = df[\"transaction_time\"].dt.isocalendar().week.astype(\"int\")\n",
        "\n",
        "    return df\n",
        "\n",
        "df = convert_to_date(df)"
      ],
      "metadata": {
        "id": "2Vn-8Fir4ngQ"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cd1IR_7C6VL8",
        "outputId": "29d85275-5a29-4060-e461-b53ce1510c71"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 137348 entries, 0 to 137347\n",
            "Data columns (total 14 columns):\n",
            " #   Column                    Non-Null Count   Dtype  \n",
            "---  ------                    --------------   -----  \n",
            " 0   outlet_id                 137348 non-null  object \n",
            " 1   transaction_time          137348 non-null  int64  \n",
            " 2   expected_rainfall         137348 non-null  object \n",
            " 3   freezer_status            137348 non-null  int64  \n",
            " 4   sku_name                  137347 non-null  object \n",
            " 5   sales_quantity            137347 non-null  float64\n",
            " 6   outlet_size               137348 non-null  int64  \n",
            " 7   population_density        137348 non-null  int64  \n",
            " 8   number_of_skus_sold       137348 non-null  int64  \n",
            " 9   average_household_income  137348 non-null  int64  \n",
            " 10  expected_rainfall_num     137348 non-null  float64\n",
            " 11  region_outstation         137348 non-null  uint8  \n",
            " 12  region_upcountry          137348 non-null  uint8  \n",
            " 13  region_western            137348 non-null  uint8  \n",
            "dtypes: float64(2), int64(6), object(3), uint8(3)\n",
            "memory usage: 11.9+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "y8QYlEhJ8ozT",
        "outputId": "e84f3eb3-20ec-4bc1-cc10-b9ab230ec27e"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        outlet_id  transaction_time expected_rainfall  freezer_status  \\\n",
              "0  outlet_code_78                 1              25mm               1   \n",
              "1  outlet_code_78                 2               0mm               1   \n",
              "2  outlet_code_78                 3              79mm               1   \n",
              "3  outlet_code_78                 4          194.51mm               1   \n",
              "4  outlet_code_78                 5              15mm               1   \n",
              "\n",
              "             sku_name  sales_quantity  outlet_size  population_density  \\\n",
              "0  Sweet Delights Mix             3.0         2870                 344   \n",
              "1  Sweet Delights Mix             3.0         2870                 344   \n",
              "2  Sweet Delights Mix             3.0         2870                 344   \n",
              "3  Sweet Delights Mix             2.0         2870                 344   \n",
              "4  Sweet Delights Mix             3.0         2870                 344   \n",
              "\n",
              "   number_of_skus_sold  average_household_income  expected_rainfall_num  \\\n",
              "0                   14                     71756                  25.00   \n",
              "1                   14                     71756                   0.00   \n",
              "2                   14                     71756                  79.00   \n",
              "3                   14                     71756                 194.51   \n",
              "4                   14                     71756                  15.00   \n",
              "\n",
              "   region_outstation  region_upcountry  region_western  \n",
              "0                  1                 0               0  \n",
              "1                  1                 0               0  \n",
              "2                  1                 0               0  \n",
              "3                  1                 0               0  \n",
              "4                  1                 0               0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-de232cab-b38a-468a-bf37-bf1ec2f38c49\" class=\"colab-df-container\">\n",
              "    <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",
              "      <th>outlet_id</th>\n",
              "      <th>transaction_time</th>\n",
              "      <th>expected_rainfall</th>\n",
              "      <th>freezer_status</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>3</td>\n",
              "      <td>79mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "      <td>79.00</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>4</td>\n",
              "      <td>194.51mm</td>\n",
              "      <td>1</td>\n",
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              "      <td>194.51</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>5</td>\n",
              "      <td>15mm</td>\n",
              "      <td>1</td>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          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",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1addbd4a-4bc2-48a8-846d-3c980dde53c7 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.nunique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BkQmIwS38uHJ",
        "outputId": "23769d76-30da-4d93-967e-c5e875f04a41"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "outlet_id                   4200\n",
              "transaction_time              22\n",
              "expected_rainfall           9704\n",
              "freezer_status                 2\n",
              "sku_name                       4\n",
              "sales_quantity                66\n",
              "outlet_size                 1640\n",
              "population_density          1559\n",
              "number_of_skus_sold           51\n",
              "average_household_income    4125\n",
              "expected_rainfall_num       9693\n",
              "region_outstation              2\n",
              "region_upcountry               2\n",
              "region_western                 2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def sort_dataframe(df, column_name)-> pd.DataFrame:\n",
        "    sorted_df = df.sort_values(by=[column_name])\n",
        "    return sorted_df\n",
        "\n",
        "df = sort_dataframe(df,\"transaction_time\")"
      ],
      "metadata": {
        "id": "3VywX4dV8VYj"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "H9xPRjbk9JHA",
        "outputId": "6f1e12bd-79a8-4414-fbde-c08104fe58e6"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              outlet_id  transaction_time expected_rainfall  freezer_status  \\\n",
              "0        outlet_code_78                 1              25mm               1   \n",
              "12478  outlet_code_4060                 1              56mm               1   \n",
              "79292  outlet_code_4070                 1              50mm               1   \n",
              "46059  outlet_code_2949                 1              48mm               0   \n",
              "29231   outlet_code_698                 1              24mm               1   \n",
              "\n",
              "                        sku_name  sales_quantity  outlet_size  \\\n",
              "0             Sweet Delights Mix             3.0         2870   \n",
              "12478          Fruit Chewy Bites            14.0         3986   \n",
              "79292          Fruit Chewy Bites             3.0         1547   \n",
              "46059  Gummy Carnival Assortment             2.0          357   \n",
              "29231          Fruit Chewy Bites            18.0         2798   \n",
              "\n",
              "       population_density  number_of_skus_sold  average_household_income  \\\n",
              "0                     344                   14                     71756   \n",
              "12478                 399                   20                     99655   \n",
              "79292                 302                   18                     92360   \n",
              "46059                 139                   18                     89280   \n",
              "29231                3397                   36                    114924   \n",
              "\n",
              "       expected_rainfall_num  region_outstation  region_upcountry  \\\n",
              "0                       25.0                  1                 0   \n",
              "12478                   56.0                  1                 0   \n",
              "79292                   50.0                  1                 0   \n",
              "46059                   48.0                  1                 0   \n",
              "29231                   24.0                  0                 0   \n",
              "\n",
              "       region_western  \n",
              "0                   0  \n",
              "12478               0  \n",
              "79292               0  \n",
              "46059               0  \n",
              "29231               1  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e3536aa6-c6e6-4923-a508-01b63f577da5\" 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>outlet_id</th>\n",
              "      <th>transaction_time</th>\n",
              "      <th>expected_rainfall</th>\n",
              "      <th>freezer_status</th>\n",
              "      <th>sku_name</th>\n",
              "      <th>sales_quantity</th>\n",
              "      <th>outlet_size</th>\n",
              "      <th>population_density</th>\n",
              "      <th>number_of_skus_sold</th>\n",
              "      <th>average_household_income</th>\n",
              "      <th>expected_rainfall_num</th>\n",
              "      <th>region_outstation</th>\n",
              "      <th>region_upcountry</th>\n",
              "      <th>region_western</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>1</td>\n",
              "      <td>25mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12478</th>\n",
              "      <td>outlet_code_4060</td>\n",
              "      <td>1</td>\n",
              "      <td>56mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3986</td>\n",
              "      <td>399</td>\n",
              "      <td>20</td>\n",
              "      <td>99655</td>\n",
              "      <td>56.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79292</th>\n",
              "      <td>outlet_code_4070</td>\n",
              "      <td>1</td>\n",
              "      <td>50mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1547</td>\n",
              "      <td>302</td>\n",
              "      <td>18</td>\n",
              "      <td>92360</td>\n",
              "      <td>50.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46059</th>\n",
              "      <td>outlet_code_2949</td>\n",
              "      <td>1</td>\n",
              "      <td>48mm</td>\n",
              "      <td>0</td>\n",
              "      <td>Gummy Carnival Assortment</td>\n",
              "      <td>2.0</td>\n",
              "      <td>357</td>\n",
              "      <td>139</td>\n",
              "      <td>18</td>\n",
              "      <td>89280</td>\n",
              "      <td>48.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29231</th>\n",
              "      <td>outlet_code_698</td>\n",
              "      <td>1</td>\n",
              "      <td>24mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2798</td>\n",
              "      <td>3397</td>\n",
              "      <td>36</td>\n",
              "      <td>114924</td>\n",
              "      <td>24.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e3536aa6-c6e6-4923-a508-01b63f577da5')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-e3536aa6-c6e6-4923-a508-01b63f577da5 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-e3536aa6-c6e6-4923-a508-01b63f577da5');\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",
              "\n",
              "\n",
              "<div id=\"df-01b3830d-f5de-45e6-9138-278a74f5e3d0\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-01b3830d-f5de-45e6-9138-278a74f5e3d0')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-01b3830d-f5de-45e6-9138-278a74f5e3d0 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def drop_columns(df: pd.DataFrame, columns_to_drop):\n",
        "    # Create a new DataFrame without the specified columns\n",
        "    new_df = df.drop(columns=columns_to_drop, errors='ignore')\n",
        "    return new_df\n",
        "\n",
        "columns_to_drop = [\"outlet_id\", \"expected_rainfall\", \"sku_name\"]\n",
        "\n",
        "cleaned_df = drop_columns(df, columns_to_drop)"
      ],
      "metadata": {
        "id": "ZczyzA606mUG"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cleaned_df.to_csv(\"cleaned_data.csv\",index=False, encoding=\"ISO-8859-1\")\n"
      ],
      "metadata": {
        "id": "dg1zwaYQ7zyT"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv(\"without_drop_column.csv\",index=False, encoding=\"ISO-8859-1\")\n",
        "df = pd.read_csv(\"without_drop_column.csv\")\n",
        "df"
      ],
      "metadata": {
        "id": "48j7F4RX8Ev_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 790
        },
        "outputId": "939094f3-1da7-45fe-de74-9c01fa5eab0d"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               outlet_id  transaction_time expected_rainfall  freezer_status  \\\n",
              "0         outlet_code_78                 1              25mm               1   \n",
              "1       outlet_code_4060                 1              56mm               1   \n",
              "2       outlet_code_4070                 1              50mm               1   \n",
              "3       outlet_code_2949                 1              48mm               0   \n",
              "4        outlet_code_698                 1              24mm               1   \n",
              "...                  ...               ...               ...             ...   \n",
              "137343   outlet_code_445                22              56mm               1   \n",
              "137344   outlet_code_983                22              51mm               1   \n",
              "137345   outlet_code_920                22              77mm               1   \n",
              "137346  outlet_code_1962                22              86mm               0   \n",
              "137347  outlet_code_3994                22               7mm               1   \n",
              "\n",
              "                         sku_name  sales_quantity  outlet_size  \\\n",
              "0              Sweet Delights Mix             3.0         2870   \n",
              "1               Fruit Chewy Bites            14.0         3986   \n",
              "2               Fruit Chewy Bites             3.0         1547   \n",
              "3       Gummy Carnival Assortment             2.0          357   \n",
              "4               Fruit Chewy Bites            18.0         2798   \n",
              "...                           ...             ...          ...   \n",
              "137343          Fruit Chewy Bites             5.0         1078   \n",
              "137344          Fruit Chewy Bites             8.0         1158   \n",
              "137345          Fruit Chewy Bites            15.0          845   \n",
              "137346          Fruit Chewy Bites             3.0          350   \n",
              "137347         Sweet Delights Mix             6.0         3247   \n",
              "\n",
              "        population_density  number_of_skus_sold  average_household_income  \\\n",
              "0                      344                   14                     71756   \n",
              "1                      399                   20                     99655   \n",
              "2                      302                   18                     92360   \n",
              "3                      139                   18                     89280   \n",
              "4                     3397                   36                    114924   \n",
              "...                    ...                  ...                       ...   \n",
              "137343                 245                   14                     68895   \n",
              "137344                 255                   15                     72876   \n",
              "137345                 217                   11                     57227   \n",
              "137346                 138                   18                     87590   \n",
              "137347                 575                   26                     48705   \n",
              "\n",
              "        expected_rainfall_num  region_outstation  region_upcountry  \\\n",
              "0                        25.0                  1                 0   \n",
              "1                        56.0                  1                 0   \n",
              "2                        50.0                  1                 0   \n",
              "3                        48.0                  1                 0   \n",
              "4                        24.0                  0                 0   \n",
              "...                       ...                ...               ...   \n",
              "137343                   56.0                  1                 0   \n",
              "137344                   51.0                  1                 0   \n",
              "137345                   77.0                  1                 0   \n",
              "137346                   86.0                  1                 0   \n",
              "137347                    7.0                  0                 1   \n",
              "\n",
              "        region_western  \n",
              "0                    0  \n",
              "1                    0  \n",
              "2                    0  \n",
              "3                    0  \n",
              "4                    1  \n",
              "...                ...  \n",
              "137343               0  \n",
              "137344               0  \n",
              "137345               0  \n",
              "137346               0  \n",
              "137347               0  \n",
              "\n",
              "[137348 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-cdddf255-a273-4c88-97c6-1ea59d7a583b\" 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>outlet_id</th>\n",
              "      <th>transaction_time</th>\n",
              "      <th>expected_rainfall</th>\n",
              "      <th>freezer_status</th>\n",
              "      <th>sku_name</th>\n",
              "      <th>sales_quantity</th>\n",
              "      <th>outlet_size</th>\n",
              "      <th>population_density</th>\n",
              "      <th>number_of_skus_sold</th>\n",
              "      <th>average_household_income</th>\n",
              "      <th>expected_rainfall_num</th>\n",
              "      <th>region_outstation</th>\n",
              "      <th>region_upcountry</th>\n",
              "      <th>region_western</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>1</td>\n",
              "      <td>25mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2870</td>\n",
              "      <td>344</td>\n",
              "      <td>14</td>\n",
              "      <td>71756</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>outlet_code_4060</td>\n",
              "      <td>1</td>\n",
              "      <td>56mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3986</td>\n",
              "      <td>399</td>\n",
              "      <td>20</td>\n",
              "      <td>99655</td>\n",
              "      <td>56.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>outlet_code_4070</td>\n",
              "      <td>1</td>\n",
              "      <td>50mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1547</td>\n",
              "      <td>302</td>\n",
              "      <td>18</td>\n",
              "      <td>92360</td>\n",
              "      <td>50.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>outlet_code_2949</td>\n",
              "      <td>1</td>\n",
              "      <td>48mm</td>\n",
              "      <td>0</td>\n",
              "      <td>Gummy Carnival Assortment</td>\n",
              "      <td>2.0</td>\n",
              "      <td>357</td>\n",
              "      <td>139</td>\n",
              "      <td>18</td>\n",
              "      <td>89280</td>\n",
              "      <td>48.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>outlet_code_698</td>\n",
              "      <td>1</td>\n",
              "      <td>24mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2798</td>\n",
              "      <td>3397</td>\n",
              "      <td>36</td>\n",
              "      <td>114924</td>\n",
              "      <td>24.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137343</th>\n",
              "      <td>outlet_code_445</td>\n",
              "      <td>22</td>\n",
              "      <td>56mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1078</td>\n",
              "      <td>245</td>\n",
              "      <td>14</td>\n",
              "      <td>68895</td>\n",
              "      <td>56.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137344</th>\n",
              "      <td>outlet_code_983</td>\n",
              "      <td>22</td>\n",
              "      <td>51mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>8.0</td>\n",
              "      <td>1158</td>\n",
              "      <td>255</td>\n",
              "      <td>15</td>\n",
              "      <td>72876</td>\n",
              "      <td>51.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137345</th>\n",
              "      <td>outlet_code_920</td>\n",
              "      <td>22</td>\n",
              "      <td>77mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>15.0</td>\n",
              "      <td>845</td>\n",
              "      <td>217</td>\n",
              "      <td>11</td>\n",
              "      <td>57227</td>\n",
              "      <td>77.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137346</th>\n",
              "      <td>outlet_code_1962</td>\n",
              "      <td>22</td>\n",
              "      <td>86mm</td>\n",
              "      <td>0</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>3.0</td>\n",
              "      <td>350</td>\n",
              "      <td>138</td>\n",
              "      <td>18</td>\n",
              "      <td>87590</td>\n",
              "      <td>86.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137347</th>\n",
              "      <td>outlet_code_3994</td>\n",
              "      <td>22</td>\n",
              "      <td>7mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3247</td>\n",
              "      <td>575</td>\n",
              "      <td>26</td>\n",
              "      <td>48705</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>137348 rows × 14 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cdddf255-a273-4c88-97c6-1ea59d7a583b')\"\n",
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              "  </svg>\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "      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",
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              "      fill: #D2E3FC;\n",
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              "      background-color: #434B5C;\n",
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              "      fill: #FFFFFF;\n",
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              "        document.querySelector('#df-cdddf255-a273-4c88-97c6-1ea59d7a583b 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-cdddf255-a273-4c88-97c6-1ea59d7a583b');\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",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
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              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --hover-bg-color: #434B5C;\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-bf9b93b1-121b-4cce-bb0a-7bceb61e9500 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_ef9108d5-48a7-4bf9-9875-a786c03a86fc\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\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=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_ef9108d5-48a7-4bf9-9875-a786c03a86fc button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "OS4VoJqb_Gdh"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "boxplot=df.boxplot(column=[\"sales_quantity\",\"outlet_size\",\"population_density\",\"number_of_skus_sold\",\"average_household_income\",\"transaction_time\",\"freezer_status\",\"expected_rainfall_num\",\"region_outstation\",\"region_upcountry\",\"region_western\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "x5oD8mc4_Gjz",
        "outputId": "b97a90bf-66ac-45bf-e441-711889130ae8"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.quantile(0.25)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zw4Nja6K_GmL",
        "outputId": "46473c59-dd91-4ff7-89fd-194f92f2b671"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-46-29e18f3a7353>:1: FutureWarning: The default value of numeric_only in DataFrame.quantile is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  df.quantile(0.25)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "transaction_time                6.0\n",
              "freezer_status                  0.0\n",
              "sales_quantity                  3.0\n",
              "outlet_size                   395.0\n",
              "population_density            255.0\n",
              "number_of_skus_sold            14.0\n",
              "average_household_income    55320.0\n",
              "expected_rainfall_num          28.0\n",
              "region_outstation               0.0\n",
              "region_upcountry                0.0\n",
              "region_western                  0.0\n",
              "Name: 0.25, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.quantile(0.75)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aT_kKmCk_Goi",
        "outputId": "cc6fbe02-ffe7-423f-dd91-3f2a49ad8be8"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-47-396ba156e02a>:1: FutureWarning: The default value of numeric_only in DataFrame.quantile is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  df.quantile(0.75)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "transaction_time               17.0\n",
              "freezer_status                  1.0\n",
              "sales_quantity                 10.0\n",
              "outlet_size                  1691.0\n",
              "population_density           1334.0\n",
              "number_of_skus_sold            27.0\n",
              "average_household_income    96300.0\n",
              "expected_rainfall_num          90.0\n",
              "region_outstation               1.0\n",
              "region_upcountry                0.0\n",
              "region_western                  1.0\n",
              "Name: 0.75, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Q1 = df.quantile(0.25)\n",
        "Q3 = df.quantile(0.75)\n",
        "IQR = Q3 - Q1\n",
        "print(IQR)\n",
        "\n",
        "filtered_entries = ~((df < (Q1 - 1.5 * IQR)) | (df > (Q3 + 1.5 * IQR)))\n",
        "clean_data = df[filtered_entries]\n",
        "clean_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "YSSaVvb6BS7B",
        "outputId": "2898d1e6-d4d9-4d90-c093-a7ba83c0b7ee"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "transaction_time               11.0\n",
            "freezer_status                  1.0\n",
            "sales_quantity                  7.0\n",
            "outlet_size                  1296.0\n",
            "population_density           1079.0\n",
            "number_of_skus_sold            13.0\n",
            "average_household_income    40980.0\n",
            "expected_rainfall_num          62.0\n",
            "region_outstation               1.0\n",
            "region_upcountry                0.0\n",
            "region_western                  1.0\n",
            "dtype: float64\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-48-b5720c771195>:1: FutureWarning: The default value of numeric_only in DataFrame.quantile is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  Q1 = df.quantile(0.25)\n",
            "<ipython-input-48-b5720c771195>:2: FutureWarning: The default value of numeric_only in DataFrame.quantile is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  Q3 = df.quantile(0.75)\n",
            "<ipython-input-48-b5720c771195>:6: FutureWarning: Automatic reindexing on DataFrame vs Series comparisons is deprecated and will raise ValueError in a future version. Do `left, right = left.align(right, axis=1, copy=False)` before e.g. `left == right`\n",
            "  filtered_entries = ~((df < (Q1 - 1.5 * IQR)) | (df > (Q3 + 1.5 * IQR)))\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               outlet_id  transaction_time expected_rainfall  freezer_status  \\\n",
              "0         outlet_code_78                 1              25mm               1   \n",
              "1       outlet_code_4060                 1              56mm               1   \n",
              "2       outlet_code_4070                 1              50mm               1   \n",
              "3       outlet_code_2949                 1              48mm               0   \n",
              "4        outlet_code_698                 1              24mm               1   \n",
              "...                  ...               ...               ...             ...   \n",
              "137343   outlet_code_445                22              56mm               1   \n",
              "137344   outlet_code_983                22              51mm               1   \n",
              "137345   outlet_code_920                22              77mm               1   \n",
              "137346  outlet_code_1962                22              86mm               0   \n",
              "137347  outlet_code_3994                22               7mm               1   \n",
              "\n",
              "                         sku_name  sales_quantity  outlet_size  \\\n",
              "0              Sweet Delights Mix             3.0       2870.0   \n",
              "1               Fruit Chewy Bites            14.0          NaN   \n",
              "2               Fruit Chewy Bites             3.0       1547.0   \n",
              "3       Gummy Carnival Assortment             2.0        357.0   \n",
              "4               Fruit Chewy Bites            18.0       2798.0   \n",
              "...                           ...             ...          ...   \n",
              "137343          Fruit Chewy Bites             5.0       1078.0   \n",
              "137344          Fruit Chewy Bites             8.0       1158.0   \n",
              "137345          Fruit Chewy Bites            15.0        845.0   \n",
              "137346          Fruit Chewy Bites             3.0        350.0   \n",
              "137347         Sweet Delights Mix             6.0       3247.0   \n",
              "\n",
              "        population_density  number_of_skus_sold  average_household_income  \\\n",
              "0                    344.0                 14.0                   71756.0   \n",
              "1                    399.0                 20.0                   99655.0   \n",
              "2                    302.0                 18.0                   92360.0   \n",
              "3                    139.0                 18.0                   89280.0   \n",
              "4                      NaN                 36.0                  114924.0   \n",
              "...                    ...                  ...                       ...   \n",
              "137343               245.0                 14.0                   68895.0   \n",
              "137344               255.0                 15.0                   72876.0   \n",
              "137345               217.0                 11.0                   57227.0   \n",
              "137346               138.0                 18.0                   87590.0   \n",
              "137347               575.0                 26.0                   48705.0   \n",
              "\n",
              "        expected_rainfall_num  region_outstation  region_upcountry  \\\n",
              "0                        25.0                  1               0.0   \n",
              "1                        56.0                  1               0.0   \n",
              "2                        50.0                  1               0.0   \n",
              "3                        48.0                  1               0.0   \n",
              "4                        24.0                  0               0.0   \n",
              "...                       ...                ...               ...   \n",
              "137343                   56.0                  1               0.0   \n",
              "137344                   51.0                  1               0.0   \n",
              "137345                   77.0                  1               0.0   \n",
              "137346                   86.0                  1               0.0   \n",
              "137347                    7.0                  0               NaN   \n",
              "\n",
              "        region_western  \n",
              "0                    0  \n",
              "1                    0  \n",
              "2                    0  \n",
              "3                    0  \n",
              "4                    1  \n",
              "...                ...  \n",
              "137343               0  \n",
              "137344               0  \n",
              "137345               0  \n",
              "137346               0  \n",
              "137347               0  \n",
              "\n",
              "[137348 rows x 14 columns]"
            ],
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              "\n",
              "  <div id=\"df-11159045-9ed8-477e-9c00-eae75d088a73\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>outlet_id</th>\n",
              "      <th>transaction_time</th>\n",
              "      <th>expected_rainfall</th>\n",
              "      <th>freezer_status</th>\n",
              "      <th>sku_name</th>\n",
              "      <th>sales_quantity</th>\n",
              "      <th>outlet_size</th>\n",
              "      <th>population_density</th>\n",
              "      <th>number_of_skus_sold</th>\n",
              "      <th>average_household_income</th>\n",
              "      <th>expected_rainfall_num</th>\n",
              "      <th>region_outstation</th>\n",
              "      <th>region_upcountry</th>\n",
              "      <th>region_western</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>outlet_code_78</td>\n",
              "      <td>1</td>\n",
              "      <td>25mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2870.0</td>\n",
              "      <td>344.0</td>\n",
              "      <td>14.0</td>\n",
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              "      <td>25.0</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>outlet_code_4060</td>\n",
              "      <td>1</td>\n",
              "      <td>56mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>14.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>399.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>99655.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>outlet_code_4070</td>\n",
              "      <td>1</td>\n",
              "      <td>50mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1547.0</td>\n",
              "      <td>302.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>92360.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>outlet_code_2949</td>\n",
              "      <td>1</td>\n",
              "      <td>48mm</td>\n",
              "      <td>0</td>\n",
              "      <td>Gummy Carnival Assortment</td>\n",
              "      <td>2.0</td>\n",
              "      <td>357.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>89280.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>outlet_code_698</td>\n",
              "      <td>1</td>\n",
              "      <td>24mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2798.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>36.0</td>\n",
              "      <td>114924.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137343</th>\n",
              "      <td>outlet_code_445</td>\n",
              "      <td>22</td>\n",
              "      <td>56mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1078.0</td>\n",
              "      <td>245.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>68895.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137344</th>\n",
              "      <td>outlet_code_983</td>\n",
              "      <td>22</td>\n",
              "      <td>51mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>8.0</td>\n",
              "      <td>1158.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>72876.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>137345</th>\n",
              "      <td>outlet_code_920</td>\n",
              "      <td>22</td>\n",
              "      <td>77mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
              "      <td>15.0</td>\n",
              "      <td>845.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>57227.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>137346</th>\n",
              "      <td>outlet_code_1962</td>\n",
              "      <td>22</td>\n",
              "      <td>86mm</td>\n",
              "      <td>0</td>\n",
              "      <td>Fruit Chewy Bites</td>\n",
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              "      <td>350.0</td>\n",
              "      <td>138.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>87590.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>137347</th>\n",
              "      <td>outlet_code_3994</td>\n",
              "      <td>22</td>\n",
              "      <td>7mm</td>\n",
              "      <td>1</td>\n",
              "      <td>Sweet Delights Mix</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3247.0</td>\n",
              "      <td>575.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>48705.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>137348 rows × 14 columns</p>\n",
              "</div>\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c8de2163-e135-4df7-a8d1-875c0c476c3f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_b0939805-032c-4095-8a4a-9f0779b45190\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('clean_data')\"\n",
              "            title=\"Generate code using this dataframe.\"\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=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_b0939805-032c-4095-8a4a-9f0779b45190 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('clean_data');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "TaEg2KooBS9G"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "iyP_JnTYBS_X"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}