descriptive_overview.ipynb

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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Template Explanation\n",
        "I use this notebook multiple times across the life of project, both as a starting overview and a point of reference between various cleaning and transformation steps.\n",
        "\n",
        "It uses a personalized version of the [cookiecutter data science](https://drivendata.github.io/cookiecutter-data-science/) file structure to simplify file selection.\n",
        "\n",
        "In addition to basic built-in `pandas` overview tools, like `.info()` and `.describe()`, I added my own functions for common tasks including:\n",
        "*  Creating a singular table of the same data from `.info()` and `.describe()`\n",
        "    * Writing the table to `.xlsx` with frozen column headers and empty columns for note-taking.\n",
        "        * `Notes` - General info that I need to remember, including questions\n",
        "        * `Drop?` - Mark if the column can be dropped\n",
        "        * `Change Dtype?` - Add what the column data type should be changed to\n",
        "*  Displaying an overview of unique values by column"
      ],
      "metadata": {
        "id": "Q7o520_sh-1z"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Notebook Conclusions\n",
        "Update this section with any findings and notes."
      ],
      "metadata": {
        "id": "PDhydTFeh1x0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Set Up"
      ],
      "metadata": {
        "id": "vMpGkN9Ejr5X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Authorize Google Drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive/')"
      ],
      "metadata": {
        "id": "ZB0b1jy-hk0t",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "946853e8-100c-421b-c22e-8c9e3e81889f"
      },
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive/; to attempt to forcibly remount, call drive.mount(\"/content/drive/\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Library imports"
      ],
      "metadata": {
        "id": "TSyy_-LYjzG7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#general analysis\n",
        "import pandas as pd\n",
        "import pprint as pp\n",
        "import re\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "\n",
        "#file management\n",
        "from pathlib import Path\n",
        "from datetime import datetime\n",
        "\n",
        "#stop words counter\n",
        "#from collections import Counter"
      ],
      "metadata": {
        "id": "nvVQzWERjxy7"
      },
      "execution_count": 125,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#unique marker for new files\n",
        "today = datetime.now().strftime(\"%Y-%m-%d\")"
      ],
      "metadata": {
        "id": "78lUjkfbkDcS"
      },
      "execution_count": 126,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Display Preferences"
      ],
      "metadata": {
        "id": "3pD_yaw7kFlo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#current preferences\n",
        "pd.set_option('display.max_rows', 100)\n",
        "pd.set_option('display.max_columns', None)\n",
        "#pd.set_option('display.max_colwidth', None) #change column display width\n",
        "#pd.set_option('display.precision', 2) #displays 2 decimal places on all numbers\n",
        "pd.set_option('display.float_format',  '{:.2f}'.format)\n",
        "pd.set_option('display.memory_usage', 'deep')"
      ],
      "metadata": {
        "id": "2_0GFBZkkIql"
      },
      "execution_count": 127,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# File Handling"
      ],
      "metadata": {
        "id": "sTxwJz8jkNYz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# @title File Selection\n",
        "# @markdown 1. Navigate to original file location in sidebar\n",
        "# @markdown 2. right-click 'Copy path'\n",
        "# @markdown 3. Paste into 'file_path' field\n",
        "\n",
        "file_path = '/content/drive/MyDrive/data_analysis/dunnhumby/data/raw/transactions_200607.csv'  # @param {type: \"string\"}\n",
        "\n",
        "# @markdown ---"
      ],
      "metadata": {
        "id": "EFABrX_llYU3"
      },
      "execution_count": 128,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#set up file_path\n",
        "file_path = Path(file_path)"
      ],
      "metadata": {
        "id": "AYxUZQW8liz6"
      },
      "execution_count": 129,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "file_path"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G5YLVHAYwzW5",
        "outputId": "e1585212-2704-4010-affa-2b14fad2d347"
      },
      "execution_count": 130,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PosixPath('/content/drive/MyDrive/data_analysis/dunnhumby/data/raw/transactions_200607.csv')"
            ]
          },
          "metadata": {},
          "execution_count": 130
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#select main drive path\n",
        "main_drive = file_path.parent.parent.parent\n",
        "print(main_drive)\n",
        "\n",
        "#create output filename string using today for unique id\n",
        "output_filename = f'{file_path.stem}_{today}'\n",
        "print(output_filename)"
      ],
      "metadata": {
        "id": "1L_oLspHjlhh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5b97cf80-4019-4fd4-9893-af9fe314b26b"
      },
      "execution_count": 150,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/data_analysis/dunnhumby\n",
            "transactions_200607_2024-03-15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Read into pandas dataframe"
      ],
      "metadata": {
        "id": "UT7fCcHulpFZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "keep_cols = []\n",
        "\n",
        "df = pd.read_csv(file_path,\n",
        "#                     usecols= keep_cols,\n",
        "#                      sep='\\t',\n",
        "#                        nrows=100,\n",
        "#                       engine='python',\n",
        "#                     encoding='ISO-8859-1'\n",
        "                        )"
      ],
      "metadata": {
        "id": "uax-4FPvlswL"
      },
      "execution_count": 132,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# DataFrame Overview"
      ],
      "metadata": {
        "id": "swkyQ1KbWKgv"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Row and Column Count"
      ],
      "metadata": {
        "id": "-6bdODYR_65L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZAsH8L3p_9zp",
        "outputId": "70597fca-735d-42a6-b300-f3600ff20d5a"
      },
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(250546, 22)"
            ]
          },
          "metadata": {},
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## `.info()`"
      ],
      "metadata": {
        "id": "K5jXVe9-UmAR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1khd9nKSWV9U",
        "outputId": "a1947b18-0287-41ba-ba89-f612940aa669"
      },
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 250546 entries, 0 to 250545\n",
            "Data columns (total 22 columns):\n",
            " #   Column                    Non-Null Count   Dtype  \n",
            "---  ------                    --------------   -----  \n",
            " 0   SHOP_WEEK                 250546 non-null  int64  \n",
            " 1   SHOP_DATE                 250546 non-null  int64  \n",
            " 2   SHOP_WEEKDAY              250546 non-null  int64  \n",
            " 3   SHOP_HOUR                 250546 non-null  int64  \n",
            " 4   QUANTITY                  250546 non-null  int64  \n",
            " 5   SPEND                     250546 non-null  float64\n",
            " 6   PROD_CODE                 250546 non-null  object \n",
            " 7   PROD_CODE_10              250546 non-null  object \n",
            " 8   PROD_CODE_20              250546 non-null  object \n",
            " 9   PROD_CODE_30              250546 non-null  object \n",
            " 10  PROD_CODE_40              250546 non-null  object \n",
            " 11  CUST_CODE                 202211 non-null  object \n",
            " 12  CUST_PRICE_SENSITIVITY    202211 non-null  object \n",
            " 13  CUST_LIFESTAGE            175047 non-null  object \n",
            " 14  BASKET_ID                 250546 non-null  int64  \n",
            " 15  BASKET_SIZE               250546 non-null  object \n",
            " 16  BASKET_PRICE_SENSITIVITY  250546 non-null  object \n",
            " 17  BASKET_TYPE               250546 non-null  object \n",
            " 18  BASKET_DOMINANT_MISSION   250546 non-null  object \n",
            " 19  STORE_CODE                250546 non-null  object \n",
            " 20  STORE_FORMAT              250546 non-null  object \n",
            " 21  STORE_REGION              250546 non-null  object \n",
            "dtypes: float64(1), int64(6), object(15)\n",
            "memory usage: 233.3 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Head and Tail Rows\n",
        "First and last 5 rows"
      ],
      "metadata": {
        "id": "tdjYhZ71y7pJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(5)"
      ],
      "metadata": {
        "id": "90aQqci4SmCg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "outputId": "a4ed999d-f61d-424f-9107-b1541886cb37"
      },
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   SHOP_WEEK  SHOP_DATE  SHOP_WEEKDAY  SHOP_HOUR  QUANTITY  SPEND   PROD_CODE  \\\n",
              "0     200607   20060411             3         16         1   1.05  PRD0900011   \n",
              "1     200607   20060411             3         19         3   1.65  PRD0900035   \n",
              "2     200607   20060414             6         21         1   0.71  PRD0900043   \n",
              "3     200607   20060414             6         14         1   0.46  PRD0900057   \n",
              "4     200607   20060411             3         16         1   1.87  PRD0900058   \n",
              "\n",
              "  PROD_CODE_10 PROD_CODE_20 PROD_CODE_30 PROD_CODE_40       CUST_CODE  \\\n",
              "0      CL00033     DEP00008       G00004       D00002             NaN   \n",
              "1      CL00113     DEP00040       G00011       D00003  CUST0000173993   \n",
              "2      CL00148     DEP00052       G00015       D00003             NaN   \n",
              "3      CL00107     DEP00037       G00010       D00003  CUST0000644893   \n",
              "4      CL00020     DEP00005       G00003       D00001             NaN   \n",
              "\n",
              "  CUST_PRICE_SENSITIVITY CUST_LIFESTAGE        BASKET_ID BASKET_SIZE  \\\n",
              "0                    NaN            NaN  994100100100943           L   \n",
              "1                     UM             OA  994100100257041           L   \n",
              "2                    NaN            NaN  994100100052871           L   \n",
              "3                     LA             PE  994100100539059           L   \n",
              "4                    NaN            NaN  994100100100943           L   \n",
              "\n",
              "  BASKET_PRICE_SENSITIVITY BASKET_TYPE BASKET_DOMINANT_MISSION  STORE_CODE  \\\n",
              "0                       UM      Top Up                   Fresh  STORE00001   \n",
              "1                       MM   Full Shop                   Mixed  STORE00001   \n",
              "2                       LA      Top Up                   Mixed  STORE00001   \n",
              "3                       LA   Full Shop                   Fresh  STORE00001   \n",
              "4                       UM      Top Up                   Fresh  STORE00001   \n",
              "\n",
              "  STORE_FORMAT STORE_REGION  \n",
              "0           LS          E02  \n",
              "1           LS          E02  \n",
              "2           LS          E02  \n",
              "3           LS          E02  \n",
              "4           LS          E02  "
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SHOP_WEEK</th>\n",
              "      <th>SHOP_DATE</th>\n",
              "      <th>SHOP_WEEKDAY</th>\n",
              "      <th>SHOP_HOUR</th>\n",
              "      <th>QUANTITY</th>\n",
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              "      <th>CUST_PRICE_SENSITIVITY</th>\n",
              "      <th>CUST_LIFESTAGE</th>\n",
              "      <th>BASKET_ID</th>\n",
              "      <th>BASKET_SIZE</th>\n",
              "      <th>BASKET_PRICE_SENSITIVITY</th>\n",
              "      <th>BASKET_TYPE</th>\n",
              "      <th>BASKET_DOMINANT_MISSION</th>\n",
              "      <th>STORE_CODE</th>\n",
              "      <th>STORE_FORMAT</th>\n",
              "      <th>STORE_REGION</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060411</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1.05</td>\n",
              "      <td>PRD0900011</td>\n",
              "      <td>CL00033</td>\n",
              "      <td>DEP00008</td>\n",
              "      <td>G00004</td>\n",
              "      <td>D00002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100100943</td>\n",
              "      <td>L</td>\n",
              "      <td>UM</td>\n",
              "      <td>Top Up</td>\n",
              "      <td>Fresh</td>\n",
              "      <td>STORE00001</td>\n",
              "      <td>LS</td>\n",
              "      <td>E02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060411</td>\n",
              "      <td>3</td>\n",
              "      <td>19</td>\n",
              "      <td>3</td>\n",
              "      <td>1.65</td>\n",
              "      <td>PRD0900035</td>\n",
              "      <td>CL00113</td>\n",
              "      <td>DEP00040</td>\n",
              "      <td>G00011</td>\n",
              "      <td>D00003</td>\n",
              "      <td>CUST0000173993</td>\n",
              "      <td>UM</td>\n",
              "      <td>OA</td>\n",
              "      <td>994100100257041</td>\n",
              "      <td>L</td>\n",
              "      <td>MM</td>\n",
              "      <td>Full Shop</td>\n",
              "      <td>Mixed</td>\n",
              "      <td>STORE00001</td>\n",
              "      <td>LS</td>\n",
              "      <td>E02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060414</td>\n",
              "      <td>6</td>\n",
              "      <td>21</td>\n",
              "      <td>1</td>\n",
              "      <td>0.71</td>\n",
              "      <td>PRD0900043</td>\n",
              "      <td>CL00148</td>\n",
              "      <td>DEP00052</td>\n",
              "      <td>G00015</td>\n",
              "      <td>D00003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100052871</td>\n",
              "      <td>L</td>\n",
              "      <td>LA</td>\n",
              "      <td>Top Up</td>\n",
              "      <td>Mixed</td>\n",
              "      <td>STORE00001</td>\n",
              "      <td>LS</td>\n",
              "      <td>E02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060414</td>\n",
              "      <td>6</td>\n",
              "      <td>14</td>\n",
              "      <td>1</td>\n",
              "      <td>0.46</td>\n",
              "      <td>PRD0900057</td>\n",
              "      <td>CL00107</td>\n",
              "      <td>DEP00037</td>\n",
              "      <td>G00010</td>\n",
              "      <td>D00003</td>\n",
              "      <td>CUST0000644893</td>\n",
              "      <td>LA</td>\n",
              "      <td>PE</td>\n",
              "      <td>994100100539059</td>\n",
              "      <td>L</td>\n",
              "      <td>LA</td>\n",
              "      <td>Full Shop</td>\n",
              "      <td>Fresh</td>\n",
              "      <td>STORE00001</td>\n",
              "      <td>LS</td>\n",
              "      <td>E02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060411</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1.87</td>\n",
              "      <td>PRD0900058</td>\n",
              "      <td>CL00020</td>\n",
              "      <td>DEP00005</td>\n",
              "      <td>G00003</td>\n",
              "      <td>D00001</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>LS</td>\n",
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              "      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-aacab39e-a439-40ea-825b-9aa6a8795653 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-aacab39e-a439-40ea-825b-9aa6a8795653');\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-5a6491f2-b835-4f50-9bb4-91c114785ebc\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5a6491f2-b835-4f50-9bb4-91c114785ebc')\"\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",
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              "    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-5a6491f2-b835-4f50-9bb4-91c114785ebc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            }
          },
          "metadata": {},
          "execution_count": 135
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.tail(5)"
      ],
      "metadata": {
        "id": "eXQAdrHVy6Bq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "outputId": "aca46923-c7ba-48ad-851a-da25c133334b"
      },
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        SHOP_WEEK  SHOP_DATE  SHOP_WEEKDAY  SHOP_HOUR  QUANTITY  SPEND  \\\n",
              "250541     200607   20060412             4         21         1   1.54   \n",
              "250542     200607   20060411             3         21         1   1.54   \n",
              "250543     200607   20060413             5          8         1   0.31   \n",
              "250544     200607   20060416             1         10         7   5.95   \n",
              "250545     200607   20060411             3         17         3   9.81   \n",
              "\n",
              "         PROD_CODE PROD_CODE_10 PROD_CODE_20 PROD_CODE_30 PROD_CODE_40  \\\n",
              "250541  PRD0904358      CL00063     DEP00019       G00007       D00002   \n",
              "250542  PRD0904358      CL00063     DEP00019       G00007       D00002   \n",
              "250543  PRD0904471      CL00218     DEP00073       G00023       D00005   \n",
              "250544  PRD0904660      CL00161     DEP00054       G00016       D00003   \n",
              "250545  PRD0904933      CL00150     DEP00052       G00015       D00003   \n",
              "\n",
              "             CUST_CODE CUST_PRICE_SENSITIVITY CUST_LIFESTAGE        BASKET_ID  \\\n",
              "250541             NaN                    NaN            NaN  994100100007204   \n",
              "250542             NaN                    NaN            NaN  994100100037346   \n",
              "250543  CUST0000325603                     MM             YA  994100100347826   \n",
              "250544             NaN                    NaN            NaN  994100100107776   \n",
              "250545             NaN                    NaN            NaN  994100100038770   \n",
              "\n",
              "       BASKET_SIZE BASKET_PRICE_SENSITIVITY BASKET_TYPE  \\\n",
              "250541           M                       LA      Top Up   \n",
              "250542           L                       UM      Top Up   \n",
              "250543           S                       MM  Small Shop   \n",
              "250544           M                       MM  Small Shop   \n",
              "250545           L                       UM      Top Up   \n",
              "\n",
              "       BASKET_DOMINANT_MISSION  STORE_CODE STORE_FORMAT STORE_REGION  \n",
              "250541                   Mixed  STORE02908           SS          N02  \n",
              "250542                   Fresh  STORE02908           SS          N02  \n",
              "250543                   Mixed  STORE02908           SS          N02  \n",
              "250544                 Grocery  STORE02908           SS          N02  \n",
              "250545                 Grocery  STORE02908           SS          N02  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e02253ed-4ccf-4d65-82f0-07d10d9d0e88\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "      <th></th>\n",
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              "      <th>SHOP_WEEKDAY</th>\n",
              "      <th>SHOP_HOUR</th>\n",
              "      <th>QUANTITY</th>\n",
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              "      <th>PROD_CODE_10</th>\n",
              "      <th>PROD_CODE_20</th>\n",
              "      <th>PROD_CODE_30</th>\n",
              "      <th>PROD_CODE_40</th>\n",
              "      <th>CUST_CODE</th>\n",
              "      <th>CUST_PRICE_SENSITIVITY</th>\n",
              "      <th>CUST_LIFESTAGE</th>\n",
              "      <th>BASKET_ID</th>\n",
              "      <th>BASKET_SIZE</th>\n",
              "      <th>BASKET_PRICE_SENSITIVITY</th>\n",
              "      <th>BASKET_TYPE</th>\n",
              "      <th>BASKET_DOMINANT_MISSION</th>\n",
              "      <th>STORE_CODE</th>\n",
              "      <th>STORE_FORMAT</th>\n",
              "      <th>STORE_REGION</th>\n",
              "    </tr>\n",
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              "      <th>250541</th>\n",
              "      <td>200607</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100007204</td>\n",
              "      <td>M</td>\n",
              "      <td>LA</td>\n",
              "      <td>Top Up</td>\n",
              "      <td>Mixed</td>\n",
              "      <td>STORE02908</td>\n",
              "      <td>SS</td>\n",
              "      <td>N02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250542</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060411</td>\n",
              "      <td>3</td>\n",
              "      <td>21</td>\n",
              "      <td>1</td>\n",
              "      <td>1.54</td>\n",
              "      <td>PRD0904358</td>\n",
              "      <td>CL00063</td>\n",
              "      <td>DEP00019</td>\n",
              "      <td>G00007</td>\n",
              "      <td>D00002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100037346</td>\n",
              "      <td>L</td>\n",
              "      <td>UM</td>\n",
              "      <td>Top Up</td>\n",
              "      <td>Fresh</td>\n",
              "      <td>STORE02908</td>\n",
              "      <td>SS</td>\n",
              "      <td>N02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250543</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060413</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>1</td>\n",
              "      <td>0.31</td>\n",
              "      <td>PRD0904471</td>\n",
              "      <td>CL00218</td>\n",
              "      <td>DEP00073</td>\n",
              "      <td>G00023</td>\n",
              "      <td>D00005</td>\n",
              "      <td>CUST0000325603</td>\n",
              "      <td>MM</td>\n",
              "      <td>YA</td>\n",
              "      <td>994100100347826</td>\n",
              "      <td>S</td>\n",
              "      <td>MM</td>\n",
              "      <td>Small Shop</td>\n",
              "      <td>Mixed</td>\n",
              "      <td>STORE02908</td>\n",
              "      <td>SS</td>\n",
              "      <td>N02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250544</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060416</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>7</td>\n",
              "      <td>5.95</td>\n",
              "      <td>PRD0904660</td>\n",
              "      <td>CL00161</td>\n",
              "      <td>DEP00054</td>\n",
              "      <td>G00016</td>\n",
              "      <td>D00003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100107776</td>\n",
              "      <td>M</td>\n",
              "      <td>MM</td>\n",
              "      <td>Small Shop</td>\n",
              "      <td>Grocery</td>\n",
              "      <td>STORE02908</td>\n",
              "      <td>SS</td>\n",
              "      <td>N02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250545</th>\n",
              "      <td>200607</td>\n",
              "      <td>20060411</td>\n",
              "      <td>3</td>\n",
              "      <td>17</td>\n",
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              "      <td>9.81</td>\n",
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              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "  <style>\n",
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              "      display:flex;\n",
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              "\n",
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              "      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",
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              "\n",
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              "      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-e02253ed-4ccf-4d65-82f0-07d10d9d0e88 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
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              "        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",
              "<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-6d65beb6-4be7-4e36-a846-c0fb30f19aeb button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe"
            }
          },
          "metadata": {},
          "execution_count": 136
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Descriptive Stats"
      ],
      "metadata": {
        "id": "wbF5UO8Vyv-P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe(include='all')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "aP94cZ7mUyD3",
        "outputId": "6fff8535-fde4-4045-9490-5d1661a838cf"
      },
      "execution_count": 137,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        SHOP_WEEK   SHOP_DATE  SHOP_WEEKDAY  SHOP_HOUR  QUANTITY     SPEND  \\\n",
              "count   250546.00   250546.00     250546.00  250546.00 250546.00 250546.00   \n",
              "unique        NaN         NaN           NaN        NaN       NaN       NaN   \n",
              "top           NaN         NaN           NaN        NaN       NaN       NaN   \n",
              "freq          NaN         NaN           NaN        NaN       NaN       NaN   \n",
              "mean    200607.00 20060413.02          4.00      14.99      1.47      1.93   \n",
              "std          0.00        2.01          2.01       3.72      1.41      4.00   \n",
              "min     200607.00 20060410.00          1.00       8.00      1.00      0.01   \n",
              "25%     200607.00 20060411.00          2.00      12.00      1.00      0.76   \n",
              "50%     200607.00 20060413.00          4.00      15.00      1.00      1.23   \n",
              "75%     200607.00 20060415.00          6.00      18.00      1.00      2.11   \n",
              "max     200607.00 20060416.00          7.00      21.00    275.00   1397.64   \n",
              "\n",
              "         PROD_CODE PROD_CODE_10 PROD_CODE_20 PROD_CODE_30 PROD_CODE_40  \\\n",
              "count       250546       250546       250546       250546       250546   \n",
              "unique        3809          242           89           31            9   \n",
              "top     PRD0903052      CL00063     DEP00019       G00007       D00002   \n",
              "freq          5968        11041        21616        56825       123764   \n",
              "mean           NaN          NaN          NaN          NaN          NaN   \n",
              "std            NaN          NaN          NaN          NaN          NaN   \n",
              "min            NaN          NaN          NaN          NaN          NaN   \n",
              "25%            NaN          NaN          NaN          NaN          NaN   \n",
              "50%            NaN          NaN          NaN          NaN          NaN   \n",
              "75%            NaN          NaN          NaN          NaN          NaN   \n",
              "max            NaN          NaN          NaN          NaN          NaN   \n",
              "\n",
              "             CUST_CODE CUST_PRICE_SENSITIVITY CUST_LIFESTAGE  \\\n",
              "count           202211                 202211         175047   \n",
              "unique           17243                      4              6   \n",
              "top     CUST0000701659                     MM             OT   \n",
              "freq               101                  91176          51914   \n",
              "mean               NaN                    NaN            NaN   \n",
              "std                NaN                    NaN            NaN   \n",
              "min                NaN                    NaN            NaN   \n",
              "25%                NaN                    NaN            NaN   \n",
              "50%                NaN                    NaN            NaN   \n",
              "75%                NaN                    NaN            NaN   \n",
              "max                NaN                    NaN            NaN   \n",
              "\n",
              "                BASKET_ID BASKET_SIZE BASKET_PRICE_SENSITIVITY BASKET_TYPE  \\\n",
              "count           250546.00      250546                   250546      250546   \n",
              "unique                NaN           3                        4           4   \n",
              "top                   NaN           L                       MM      Top Up   \n",
              "freq                  NaN      178405                   119486      113151   \n",
              "mean   994100100379997.62         NaN                      NaN         NaN   \n",
              "std             216601.67         NaN                      NaN         NaN   \n",
              "min    994100100000007.00         NaN                      NaN         NaN   \n",
              "25%    994100100193201.00         NaN                      NaN         NaN   \n",
              "50%    994100100379527.00         NaN                      NaN         NaN   \n",
              "75%    994100100568819.75         NaN                      NaN         NaN   \n",
              "max    994100100752358.00         NaN                      NaN         NaN   \n",
              "\n",
              "       BASKET_DOMINANT_MISSION  STORE_CODE STORE_FORMAT STORE_REGION  \n",
              "count                   250546      250546       250546       250546  \n",
              "unique                       5         748            4           12  \n",
              "top                      Fresh  STORE01423           LS          S02  \n",
              "freq                    129265        1224       160648        26370  \n",
              "mean                       NaN         NaN          NaN          NaN  \n",
              "std                        NaN         NaN          NaN          NaN  \n",
              "min                        NaN         NaN          NaN          NaN  \n",
              "25%                        NaN         NaN          NaN          NaN  \n",
              "50%                        NaN         NaN          NaN          NaN  \n",
              "75%                        NaN         NaN          NaN          NaN  \n",
              "max                        NaN         NaN          NaN          NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e710e19d-1f90-49fd-81b0-aedddb25c12c\" 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>SHOP_WEEK</th>\n",
              "      <th>SHOP_DATE</th>\n",
              "      <th>SHOP_WEEKDAY</th>\n",
              "      <th>SHOP_HOUR</th>\n",
              "      <th>QUANTITY</th>\n",
              "      <th>SPEND</th>\n",
              "      <th>PROD_CODE</th>\n",
              "      <th>PROD_CODE_10</th>\n",
              "      <th>PROD_CODE_20</th>\n",
              "      <th>PROD_CODE_30</th>\n",
              "      <th>PROD_CODE_40</th>\n",
              "      <th>CUST_CODE</th>\n",
              "      <th>CUST_PRICE_SENSITIVITY</th>\n",
              "      <th>CUST_LIFESTAGE</th>\n",
              "      <th>BASKET_ID</th>\n",
              "      <th>BASKET_SIZE</th>\n",
              "      <th>BASKET_PRICE_SENSITIVITY</th>\n",
              "      <th>BASKET_TYPE</th>\n",
              "      <th>BASKET_DOMINANT_MISSION</th>\n",
              "      <th>STORE_CODE</th>\n",
              "      <th>STORE_FORMAT</th>\n",
              "      <th>STORE_REGION</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>202211</td>\n",
              "      <td>202211</td>\n",
              "      <td>175047</td>\n",
              "      <td>250546.00</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "      <td>250546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unique</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3809</td>\n",
              "      <td>242</td>\n",
              "      <td>89</td>\n",
              "      <td>31</td>\n",
              "      <td>9</td>\n",
              "      <td>17243</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>748</td>\n",
              "      <td>4</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>top</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PRD0903052</td>\n",
              "      <td>CL00063</td>\n",
              "      <td>DEP00019</td>\n",
              "      <td>G00007</td>\n",
              "      <td>D00002</td>\n",
              "      <td>CUST0000701659</td>\n",
              "      <td>MM</td>\n",
              "      <td>OT</td>\n",
              "      <td>NaN</td>\n",
              "      <td>L</td>\n",
              "      <td>MM</td>\n",
              "      <td>Top Up</td>\n",
              "      <td>Fresh</td>\n",
              "      <td>STORE01423</td>\n",
              "      <td>LS</td>\n",
              "      <td>S02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>freq</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5968</td>\n",
              "      <td>11041</td>\n",
              "      <td>21616</td>\n",
              "      <td>56825</td>\n",
              "      <td>123764</td>\n",
              "      <td>101</td>\n",
              "      <td>91176</td>\n",
              "      <td>51914</td>\n",
              "      <td>NaN</td>\n",
              "      <td>178405</td>\n",
              "      <td>119486</td>\n",
              "      <td>113151</td>\n",
              "      <td>129265</td>\n",
              "      <td>1224</td>\n",
              "      <td>160648</td>\n",
              "      <td>26370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>200607.00</td>\n",
              "      <td>20060413.02</td>\n",
              "      <td>4.00</td>\n",
              "      <td>14.99</td>\n",
              "      <td>1.47</td>\n",
              "      <td>1.93</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100379997.62</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.00</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.01</td>\n",
              "      <td>3.72</td>\n",
              "      <td>1.41</td>\n",
              "      <td>4.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>216601.67</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>200607.00</td>\n",
              "      <td>20060410.00</td>\n",
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              "      <td>1.00</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100000007.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>200607.00</td>\n",
              "      <td>20060411.00</td>\n",
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              "      <td>12.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.76</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100193201.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>200607.00</td>\n",
              "      <td>20060413.00</td>\n",
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              "      <td>15.00</td>\n",
              "      <td>1.00</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100379527.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>200607.00</td>\n",
              "      <td>20060415.00</td>\n",
              "      <td>6.00</td>\n",
              "      <td>18.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>2.11</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100568819.75</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>200607.00</td>\n",
              "      <td>20060416.00</td>\n",
              "      <td>7.00</td>\n",
              "      <td>21.00</td>\n",
              "      <td>275.00</td>\n",
              "      <td>1397.64</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>994100100752358.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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-e710e19d-1f90-49fd-81b0-aedddb25c12c')\"\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-e710e19d-1f90-49fd-81b0-aedddb25c12c 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-e710e19d-1f90-49fd-81b0-aedddb25c12c');\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-567dd4f6-79d9-4fe6-8b53-99483ba8c928\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-567dd4f6-79d9-4fe6-8b53-99483ba8c928')\"\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-567dd4f6-79d9-4fe6-8b53-99483ba8c928 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe"
            }
          },
          "metadata": {},
          "execution_count": 137
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Testing"
      ],
      "metadata": {
        "id": "WDt15RV8ZKkT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Types, Memory Usage, Nulls, Value Counts"
      ],
      "metadata": {
        "id": "ycnuPed-zK4C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#pandas documention re memory usage: base-2 representation; i.e. 1KB = 1024 bytes"
      ],
      "metadata": {
        "id": "XW1G1lsVfjzR"
      },
      "execution_count": 138,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_dataframe_info(df):\n",
        "    \"\"\"\n",
        "Recreates column-wise info from df.info() as a DataFrame to allow for easier viewing from CSV\n",
        "    \"\"\"\n",
        "    df_dtypes = pd.DataFrame(df.dtypes, columns=['Data Types'])\n",
        "\n",
        "    df_memory_usage = df.memory_usage(index=False, deep=True).to_frame(name='Memory Use')\n",
        "    df_memory_usage['Memory Use'] = df_memory_usage['Memory Use']/1024/1024\n",
        "\n",
        "    df_percent_null = ((1 - df.count() / len(df)) * 100).to_frame(name='Percent Null')\n",
        "\n",
        "    df_described = df.describe(include='all').T\n",
        "\n",
        "\n",
        "    df_info = pd.concat([df_dtypes, df_memory_usage, df_percent_null, df_described], axis=1)\n",
        "\n",
        "    # Reassign column names\n",
        "    df_info = df_info.rename_axis('Column Names').round(2)\n",
        "\n",
        "#    df_info = df_info.set_index('column_names')\n",
        "\n",
        "    return df_info"
      ],
      "metadata": {
        "id": "q05UyJLfV0_I"
      },
      "execution_count": 139,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_info = get_dataframe_info(df)"
      ],
      "metadata": {
        "id": "9CKmfp_Df3mN"
      },
      "execution_count": 140,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_info.style \\\n",
        "    .format(precision=2) \\\n",
        "    .set_sticky(axis='index') \\\n",
        "    .bar(color='#89d8e0')"
      ],
      "metadata": {
        "id": "sAzjh2J1CuGf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 808
        },
        "outputId": "3173dc18-225e-44c2-afca-1d13ab94af56"
      },
      "execution_count": 141,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x79971da5b0a0>"
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              "#T_4563a tbody tr th:nth-child(1) {\n",
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              "  width: 10em;\n",
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              "#T_4563a_row0_col2, #T_4563a_row1_col2, #T_4563a_row2_col2, #T_4563a_row3_col2, #T_4563a_row4_col2, #T_4563a_row5_col2, #T_4563a_row6_col2, #T_4563a_row7_col2, #T_4563a_row8_col2, #T_4563a_row9_col2, #T_4563a_row10_col2, #T_4563a_row14_col2, #T_4563a_row15_col2, #T_4563a_row16_col2, #T_4563a_row17_col2, #T_4563a_row18_col2, #T_4563a_row19_col2, #T_4563a_row20_col2, #T_4563a_row21_col2 {\n",
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              "</style>\n",
              "<table id=\"T_4563a\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_4563a_level0_col0\" class=\"col_heading level0 col0\" >Data Types</th>\n",
              "      <th id=\"T_4563a_level0_col1\" class=\"col_heading level0 col1\" >Memory Use</th>\n",
              "      <th id=\"T_4563a_level0_col2\" class=\"col_heading level0 col2\" >Percent Null</th>\n",
              "      <th id=\"T_4563a_level0_col3\" class=\"col_heading level0 col3\" >count</th>\n",
              "      <th id=\"T_4563a_level0_col4\" class=\"col_heading level0 col4\" >unique</th>\n",
              "      <th id=\"T_4563a_level0_col5\" class=\"col_heading level0 col5\" >top</th>\n",
              "      <th id=\"T_4563a_level0_col6\" class=\"col_heading level0 col6\" >freq</th>\n",
              "      <th id=\"T_4563a_level0_col7\" class=\"col_heading level0 col7\" >mean</th>\n",
              "      <th id=\"T_4563a_level0_col8\" class=\"col_heading level0 col8\" >std</th>\n",
              "      <th id=\"T_4563a_level0_col9\" class=\"col_heading level0 col9\" >min</th>\n",
              "      <th id=\"T_4563a_level0_col10\" class=\"col_heading level0 col10\" >25%</th>\n",
              "      <th id=\"T_4563a_level0_col11\" class=\"col_heading level0 col11\" >50%</th>\n",
              "      <th id=\"T_4563a_level0_col12\" class=\"col_heading level0 col12\" >75%</th>\n",
              "      <th id=\"T_4563a_level0_col13\" class=\"col_heading level0 col13\" >max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >Column Names</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "      <th class=\"blank col7\" >&nbsp;</th>\n",
              "      <th class=\"blank col8\" >&nbsp;</th>\n",
              "      <th class=\"blank col9\" >&nbsp;</th>\n",
              "      <th class=\"blank col10\" >&nbsp;</th>\n",
              "      <th class=\"blank col11\" >&nbsp;</th>\n",
              "      <th class=\"blank col12\" >&nbsp;</th>\n",
              "      <th class=\"blank col13\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row0\" class=\"row_heading level0 row0\" >SHOP_WEEK</th>\n",
              "      <td id=\"T_4563a_row0_col0\" class=\"data row0 col0\" >int64</td>\n",
              "      <td id=\"T_4563a_row0_col1\" class=\"data row0 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row0_col2\" class=\"data row0 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row0_col3\" class=\"data row0 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row0_col4\" class=\"data row0 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row0_col5\" class=\"data row0 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row0_col6\" class=\"data row0 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row0_col7\" class=\"data row0 col7\" >200607.00</td>\n",
              "      <td id=\"T_4563a_row0_col8\" class=\"data row0 col8\" >0.00</td>\n",
              "      <td id=\"T_4563a_row0_col9\" class=\"data row0 col9\" >200607.00</td>\n",
              "      <td id=\"T_4563a_row0_col10\" class=\"data row0 col10\" >200607.00</td>\n",
              "      <td id=\"T_4563a_row0_col11\" class=\"data row0 col11\" >200607.00</td>\n",
              "      <td id=\"T_4563a_row0_col12\" class=\"data row0 col12\" >200607.00</td>\n",
              "      <td id=\"T_4563a_row0_col13\" class=\"data row0 col13\" >200607.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row1\" class=\"row_heading level0 row1\" >SHOP_DATE</th>\n",
              "      <td id=\"T_4563a_row1_col0\" class=\"data row1 col0\" >int64</td>\n",
              "      <td id=\"T_4563a_row1_col1\" class=\"data row1 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row1_col2\" class=\"data row1 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row1_col3\" class=\"data row1 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row1_col4\" class=\"data row1 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row1_col5\" class=\"data row1 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row1_col6\" class=\"data row1 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row1_col7\" class=\"data row1 col7\" >20060413.02</td>\n",
              "      <td id=\"T_4563a_row1_col8\" class=\"data row1 col8\" >2.01</td>\n",
              "      <td id=\"T_4563a_row1_col9\" class=\"data row1 col9\" >20060410.00</td>\n",
              "      <td id=\"T_4563a_row1_col10\" class=\"data row1 col10\" >20060411.00</td>\n",
              "      <td id=\"T_4563a_row1_col11\" class=\"data row1 col11\" >20060413.00</td>\n",
              "      <td id=\"T_4563a_row1_col12\" class=\"data row1 col12\" >20060415.00</td>\n",
              "      <td id=\"T_4563a_row1_col13\" class=\"data row1 col13\" >20060416.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row2\" class=\"row_heading level0 row2\" >SHOP_WEEKDAY</th>\n",
              "      <td id=\"T_4563a_row2_col0\" class=\"data row2 col0\" >int64</td>\n",
              "      <td id=\"T_4563a_row2_col1\" class=\"data row2 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row2_col2\" class=\"data row2 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row2_col3\" class=\"data row2 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row2_col4\" class=\"data row2 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row2_col5\" class=\"data row2 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row2_col6\" class=\"data row2 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row2_col7\" class=\"data row2 col7\" >4.00</td>\n",
              "      <td id=\"T_4563a_row2_col8\" class=\"data row2 col8\" >2.01</td>\n",
              "      <td id=\"T_4563a_row2_col9\" class=\"data row2 col9\" >1.00</td>\n",
              "      <td id=\"T_4563a_row2_col10\" class=\"data row2 col10\" >2.00</td>\n",
              "      <td id=\"T_4563a_row2_col11\" class=\"data row2 col11\" >4.00</td>\n",
              "      <td id=\"T_4563a_row2_col12\" class=\"data row2 col12\" >6.00</td>\n",
              "      <td id=\"T_4563a_row2_col13\" class=\"data row2 col13\" >7.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row3\" class=\"row_heading level0 row3\" >SHOP_HOUR</th>\n",
              "      <td id=\"T_4563a_row3_col0\" class=\"data row3 col0\" >int64</td>\n",
              "      <td id=\"T_4563a_row3_col1\" class=\"data row3 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row3_col2\" class=\"data row3 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row3_col3\" class=\"data row3 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row3_col4\" class=\"data row3 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row3_col5\" class=\"data row3 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row3_col6\" class=\"data row3 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row3_col7\" class=\"data row3 col7\" >14.99</td>\n",
              "      <td id=\"T_4563a_row3_col8\" class=\"data row3 col8\" >3.72</td>\n",
              "      <td id=\"T_4563a_row3_col9\" class=\"data row3 col9\" >8.00</td>\n",
              "      <td id=\"T_4563a_row3_col10\" class=\"data row3 col10\" >12.00</td>\n",
              "      <td id=\"T_4563a_row3_col11\" class=\"data row3 col11\" >15.00</td>\n",
              "      <td id=\"T_4563a_row3_col12\" class=\"data row3 col12\" >18.00</td>\n",
              "      <td id=\"T_4563a_row3_col13\" class=\"data row3 col13\" >21.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row4\" class=\"row_heading level0 row4\" >QUANTITY</th>\n",
              "      <td id=\"T_4563a_row4_col0\" class=\"data row4 col0\" >int64</td>\n",
              "      <td id=\"T_4563a_row4_col1\" class=\"data row4 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row4_col2\" class=\"data row4 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row4_col3\" class=\"data row4 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row4_col4\" class=\"data row4 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row4_col5\" class=\"data row4 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row4_col6\" class=\"data row4 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row4_col7\" class=\"data row4 col7\" >1.47</td>\n",
              "      <td id=\"T_4563a_row4_col8\" class=\"data row4 col8\" >1.41</td>\n",
              "      <td id=\"T_4563a_row4_col9\" class=\"data row4 col9\" >1.00</td>\n",
              "      <td id=\"T_4563a_row4_col10\" class=\"data row4 col10\" >1.00</td>\n",
              "      <td id=\"T_4563a_row4_col11\" class=\"data row4 col11\" >1.00</td>\n",
              "      <td id=\"T_4563a_row4_col12\" class=\"data row4 col12\" >1.00</td>\n",
              "      <td id=\"T_4563a_row4_col13\" class=\"data row4 col13\" >275.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row5\" class=\"row_heading level0 row5\" >SPEND</th>\n",
              "      <td id=\"T_4563a_row5_col0\" class=\"data row5 col0\" >float64</td>\n",
              "      <td id=\"T_4563a_row5_col1\" class=\"data row5 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row5_col2\" class=\"data row5 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row5_col3\" class=\"data row5 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row5_col4\" class=\"data row5 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row5_col5\" class=\"data row5 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row5_col6\" class=\"data row5 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row5_col7\" class=\"data row5 col7\" >1.93</td>\n",
              "      <td id=\"T_4563a_row5_col8\" class=\"data row5 col8\" >4.00</td>\n",
              "      <td id=\"T_4563a_row5_col9\" class=\"data row5 col9\" >0.01</td>\n",
              "      <td id=\"T_4563a_row5_col10\" class=\"data row5 col10\" >0.76</td>\n",
              "      <td id=\"T_4563a_row5_col11\" class=\"data row5 col11\" >1.23</td>\n",
              "      <td id=\"T_4563a_row5_col12\" class=\"data row5 col12\" >2.11</td>\n",
              "      <td id=\"T_4563a_row5_col13\" class=\"data row5 col13\" >1397.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row6\" class=\"row_heading level0 row6\" >PROD_CODE</th>\n",
              "      <td id=\"T_4563a_row6_col0\" class=\"data row6 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row6_col1\" class=\"data row6 col1\" >16.01</td>\n",
              "      <td id=\"T_4563a_row6_col2\" class=\"data row6 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row6_col3\" class=\"data row6 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row6_col4\" class=\"data row6 col4\" >3809</td>\n",
              "      <td id=\"T_4563a_row6_col5\" class=\"data row6 col5\" >PRD0903052</td>\n",
              "      <td id=\"T_4563a_row6_col6\" class=\"data row6 col6\" >5968</td>\n",
              "      <td id=\"T_4563a_row6_col7\" class=\"data row6 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row6_col8\" class=\"data row6 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row6_col9\" class=\"data row6 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row6_col10\" class=\"data row6 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row6_col11\" class=\"data row6 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row6_col12\" class=\"data row6 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row6_col13\" class=\"data row6 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row7\" class=\"row_heading level0 row7\" >PROD_CODE_10</th>\n",
              "      <td id=\"T_4563a_row7_col0\" class=\"data row7 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row7_col1\" class=\"data row7 col1\" >15.29</td>\n",
              "      <td id=\"T_4563a_row7_col2\" class=\"data row7 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row7_col3\" class=\"data row7 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row7_col4\" class=\"data row7 col4\" >242</td>\n",
              "      <td id=\"T_4563a_row7_col5\" class=\"data row7 col5\" >CL00063</td>\n",
              "      <td id=\"T_4563a_row7_col6\" class=\"data row7 col6\" >11041</td>\n",
              "      <td id=\"T_4563a_row7_col7\" class=\"data row7 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row7_col8\" class=\"data row7 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row7_col9\" class=\"data row7 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row7_col10\" class=\"data row7 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row7_col11\" class=\"data row7 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row7_col12\" class=\"data row7 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row7_col13\" class=\"data row7 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row8\" class=\"row_heading level0 row8\" >PROD_CODE_20</th>\n",
              "      <td id=\"T_4563a_row8_col0\" class=\"data row8 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row8_col1\" class=\"data row8 col1\" >15.53</td>\n",
              "      <td id=\"T_4563a_row8_col2\" class=\"data row8 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row8_col3\" class=\"data row8 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row8_col4\" class=\"data row8 col4\" >89</td>\n",
              "      <td id=\"T_4563a_row8_col5\" class=\"data row8 col5\" >DEP00019</td>\n",
              "      <td id=\"T_4563a_row8_col6\" class=\"data row8 col6\" >21616</td>\n",
              "      <td id=\"T_4563a_row8_col7\" class=\"data row8 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row8_col8\" class=\"data row8 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row8_col9\" class=\"data row8 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row8_col10\" class=\"data row8 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row8_col11\" class=\"data row8 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row8_col12\" class=\"data row8 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row8_col13\" class=\"data row8 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row9\" class=\"row_heading level0 row9\" >PROD_CODE_30</th>\n",
              "      <td id=\"T_4563a_row9_col0\" class=\"data row9 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row9_col1\" class=\"data row9 col1\" >15.05</td>\n",
              "      <td id=\"T_4563a_row9_col2\" class=\"data row9 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row9_col3\" class=\"data row9 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row9_col4\" class=\"data row9 col4\" >31</td>\n",
              "      <td id=\"T_4563a_row9_col5\" class=\"data row9 col5\" >G00007</td>\n",
              "      <td id=\"T_4563a_row9_col6\" class=\"data row9 col6\" >56825</td>\n",
              "      <td id=\"T_4563a_row9_col7\" class=\"data row9 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row9_col8\" class=\"data row9 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row9_col9\" class=\"data row9 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row9_col10\" class=\"data row9 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row9_col11\" class=\"data row9 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row9_col12\" class=\"data row9 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row9_col13\" class=\"data row9 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row10\" class=\"row_heading level0 row10\" >PROD_CODE_40</th>\n",
              "      <td id=\"T_4563a_row10_col0\" class=\"data row10 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row10_col1\" class=\"data row10 col1\" >15.05</td>\n",
              "      <td id=\"T_4563a_row10_col2\" class=\"data row10 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row10_col3\" class=\"data row10 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row10_col4\" class=\"data row10 col4\" >9</td>\n",
              "      <td id=\"T_4563a_row10_col5\" class=\"data row10 col5\" >D00002</td>\n",
              "      <td id=\"T_4563a_row10_col6\" class=\"data row10 col6\" >123764</td>\n",
              "      <td id=\"T_4563a_row10_col7\" class=\"data row10 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row10_col8\" class=\"data row10 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row10_col9\" class=\"data row10 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row10_col10\" class=\"data row10 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row10_col11\" class=\"data row10 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row10_col12\" class=\"data row10 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row10_col13\" class=\"data row10 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row11\" class=\"row_heading level0 row11\" >CUST_CODE</th>\n",
              "      <td id=\"T_4563a_row11_col0\" class=\"data row11 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row11_col1\" class=\"data row11 col1\" >15.17</td>\n",
              "      <td id=\"T_4563a_row11_col2\" class=\"data row11 col2\" >19.29</td>\n",
              "      <td id=\"T_4563a_row11_col3\" class=\"data row11 col3\" >202211</td>\n",
              "      <td id=\"T_4563a_row11_col4\" class=\"data row11 col4\" >17243</td>\n",
              "      <td id=\"T_4563a_row11_col5\" class=\"data row11 col5\" >CUST0000701659</td>\n",
              "      <td id=\"T_4563a_row11_col6\" class=\"data row11 col6\" >101</td>\n",
              "      <td id=\"T_4563a_row11_col7\" class=\"data row11 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row11_col8\" class=\"data row11 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row11_col9\" class=\"data row11 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row11_col10\" class=\"data row11 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row11_col11\" class=\"data row11 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row11_col12\" class=\"data row11 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row11_col13\" class=\"data row11 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row12\" class=\"row_heading level0 row12\" >CUST_PRICE_SENSITIVITY</th>\n",
              "      <td id=\"T_4563a_row12_col0\" class=\"data row12 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row12_col1\" class=\"data row12 col1\" >12.85</td>\n",
              "      <td id=\"T_4563a_row12_col2\" class=\"data row12 col2\" >19.29</td>\n",
              "      <td id=\"T_4563a_row12_col3\" class=\"data row12 col3\" >202211</td>\n",
              "      <td id=\"T_4563a_row12_col4\" class=\"data row12 col4\" >4</td>\n",
              "      <td id=\"T_4563a_row12_col5\" class=\"data row12 col5\" >MM</td>\n",
              "      <td id=\"T_4563a_row12_col6\" class=\"data row12 col6\" >91176</td>\n",
              "      <td id=\"T_4563a_row12_col7\" class=\"data row12 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row12_col8\" class=\"data row12 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row12_col9\" class=\"data row12 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row12_col10\" class=\"data row12 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row12_col11\" class=\"data row12 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row12_col12\" class=\"data row12 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row12_col13\" class=\"data row12 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row13\" class=\"row_heading level0 row13\" >CUST_LIFESTAGE</th>\n",
              "      <td id=\"T_4563a_row13_col0\" class=\"data row13 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row13_col1\" class=\"data row13 col1\" >12.15</td>\n",
              "      <td id=\"T_4563a_row13_col2\" class=\"data row13 col2\" >30.13</td>\n",
              "      <td id=\"T_4563a_row13_col3\" class=\"data row13 col3\" >175047</td>\n",
              "      <td id=\"T_4563a_row13_col4\" class=\"data row13 col4\" >6</td>\n",
              "      <td id=\"T_4563a_row13_col5\" class=\"data row13 col5\" >OT</td>\n",
              "      <td id=\"T_4563a_row13_col6\" class=\"data row13 col6\" >51914</td>\n",
              "      <td id=\"T_4563a_row13_col7\" class=\"data row13 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row13_col8\" class=\"data row13 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row13_col9\" class=\"data row13 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row13_col10\" class=\"data row13 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row13_col11\" class=\"data row13 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row13_col12\" class=\"data row13 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row13_col13\" class=\"data row13 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row14\" class=\"row_heading level0 row14\" >BASKET_ID</th>\n",
              "      <td id=\"T_4563a_row14_col0\" class=\"data row14 col0\" >int64</td>\n",
              "      <td id=\"T_4563a_row14_col1\" class=\"data row14 col1\" >1.91</td>\n",
              "      <td id=\"T_4563a_row14_col2\" class=\"data row14 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row14_col3\" class=\"data row14 col3\" >250546.00</td>\n",
              "      <td id=\"T_4563a_row14_col4\" class=\"data row14 col4\" >nan</td>\n",
              "      <td id=\"T_4563a_row14_col5\" class=\"data row14 col5\" >nan</td>\n",
              "      <td id=\"T_4563a_row14_col6\" class=\"data row14 col6\" >nan</td>\n",
              "      <td id=\"T_4563a_row14_col7\" class=\"data row14 col7\" >994100100379997.62</td>\n",
              "      <td id=\"T_4563a_row14_col8\" class=\"data row14 col8\" >216601.67</td>\n",
              "      <td id=\"T_4563a_row14_col9\" class=\"data row14 col9\" >994100100000007.00</td>\n",
              "      <td id=\"T_4563a_row14_col10\" class=\"data row14 col10\" >994100100193201.00</td>\n",
              "      <td id=\"T_4563a_row14_col11\" class=\"data row14 col11\" >994100100379527.00</td>\n",
              "      <td id=\"T_4563a_row14_col12\" class=\"data row14 col12\" >994100100568819.75</td>\n",
              "      <td id=\"T_4563a_row14_col13\" class=\"data row14 col13\" >994100100752358.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row15\" class=\"row_heading level0 row15\" >BASKET_SIZE</th>\n",
              "      <td id=\"T_4563a_row15_col0\" class=\"data row15 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row15_col1\" class=\"data row15 col1\" >13.86</td>\n",
              "      <td id=\"T_4563a_row15_col2\" class=\"data row15 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row15_col3\" class=\"data row15 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row15_col4\" class=\"data row15 col4\" >3</td>\n",
              "      <td id=\"T_4563a_row15_col5\" class=\"data row15 col5\" >L</td>\n",
              "      <td id=\"T_4563a_row15_col6\" class=\"data row15 col6\" >178405</td>\n",
              "      <td id=\"T_4563a_row15_col7\" class=\"data row15 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row15_col8\" class=\"data row15 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row15_col9\" class=\"data row15 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row15_col10\" class=\"data row15 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row15_col11\" class=\"data row15 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row15_col12\" class=\"data row15 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row15_col13\" class=\"data row15 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row16\" class=\"row_heading level0 row16\" >BASKET_PRICE_SENSITIVITY</th>\n",
              "      <td id=\"T_4563a_row16_col0\" class=\"data row16 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row16_col1\" class=\"data row16 col1\" >14.10</td>\n",
              "      <td id=\"T_4563a_row16_col2\" class=\"data row16 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row16_col3\" class=\"data row16 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row16_col4\" class=\"data row16 col4\" >4</td>\n",
              "      <td id=\"T_4563a_row16_col5\" class=\"data row16 col5\" >MM</td>\n",
              "      <td id=\"T_4563a_row16_col6\" class=\"data row16 col6\" >119486</td>\n",
              "      <td id=\"T_4563a_row16_col7\" class=\"data row16 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row16_col8\" class=\"data row16 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row16_col9\" class=\"data row16 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row16_col10\" class=\"data row16 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row16_col11\" class=\"data row16 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row16_col12\" class=\"data row16 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row16_col13\" class=\"data row16 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row17\" class=\"row_heading level0 row17\" >BASKET_TYPE</th>\n",
              "      <td id=\"T_4563a_row17_col0\" class=\"data row17 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row17_col1\" class=\"data row17 col1\" >15.49</td>\n",
              "      <td id=\"T_4563a_row17_col2\" class=\"data row17 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row17_col3\" class=\"data row17 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row17_col4\" class=\"data row17 col4\" >4</td>\n",
              "      <td id=\"T_4563a_row17_col5\" class=\"data row17 col5\" >Top Up</td>\n",
              "      <td id=\"T_4563a_row17_col6\" class=\"data row17 col6\" >113151</td>\n",
              "      <td id=\"T_4563a_row17_col7\" class=\"data row17 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row17_col8\" class=\"data row17 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row17_col9\" class=\"data row17 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row17_col10\" class=\"data row17 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row17_col11\" class=\"data row17 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row17_col12\" class=\"data row17 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row17_col13\" class=\"data row17 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row18\" class=\"row_heading level0 row18\" >BASKET_DOMINANT_MISSION</th>\n",
              "      <td id=\"T_4563a_row18_col0\" class=\"data row18 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row18_col1\" class=\"data row18 col1\" >14.87</td>\n",
              "      <td id=\"T_4563a_row18_col2\" class=\"data row18 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row18_col3\" class=\"data row18 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row18_col4\" class=\"data row18 col4\" >5</td>\n",
              "      <td id=\"T_4563a_row18_col5\" class=\"data row18 col5\" >Fresh</td>\n",
              "      <td id=\"T_4563a_row18_col6\" class=\"data row18 col6\" >129265</td>\n",
              "      <td id=\"T_4563a_row18_col7\" class=\"data row18 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row18_col8\" class=\"data row18 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row18_col9\" class=\"data row18 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row18_col10\" class=\"data row18 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row18_col11\" class=\"data row18 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row18_col12\" class=\"data row18 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row18_col13\" class=\"data row18 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row19\" class=\"row_heading level0 row19\" >STORE_CODE</th>\n",
              "      <td id=\"T_4563a_row19_col0\" class=\"data row19 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row19_col1\" class=\"data row19 col1\" >16.01</td>\n",
              "      <td id=\"T_4563a_row19_col2\" class=\"data row19 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row19_col3\" class=\"data row19 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row19_col4\" class=\"data row19 col4\" >748</td>\n",
              "      <td id=\"T_4563a_row19_col5\" class=\"data row19 col5\" >STORE01423</td>\n",
              "      <td id=\"T_4563a_row19_col6\" class=\"data row19 col6\" >1224</td>\n",
              "      <td id=\"T_4563a_row19_col7\" class=\"data row19 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row19_col8\" class=\"data row19 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row19_col9\" class=\"data row19 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row19_col10\" class=\"data row19 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row19_col11\" class=\"data row19 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row19_col12\" class=\"data row19 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row19_col13\" class=\"data row19 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row20\" class=\"row_heading level0 row20\" >STORE_FORMAT</th>\n",
              "      <td id=\"T_4563a_row20_col0\" class=\"data row20 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row20_col1\" class=\"data row20 col1\" >14.12</td>\n",
              "      <td id=\"T_4563a_row20_col2\" class=\"data row20 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row20_col3\" class=\"data row20 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row20_col4\" class=\"data row20 col4\" >4</td>\n",
              "      <td id=\"T_4563a_row20_col5\" class=\"data row20 col5\" >LS</td>\n",
              "      <td id=\"T_4563a_row20_col6\" class=\"data row20 col6\" >160648</td>\n",
              "      <td id=\"T_4563a_row20_col7\" class=\"data row20 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row20_col8\" class=\"data row20 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row20_col9\" class=\"data row20 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row20_col10\" class=\"data row20 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row20_col11\" class=\"data row20 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row20_col12\" class=\"data row20 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row20_col13\" class=\"data row20 col13\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4563a_level0_row21\" class=\"row_heading level0 row21\" >STORE_REGION</th>\n",
              "      <td id=\"T_4563a_row21_col0\" class=\"data row21 col0\" >object</td>\n",
              "      <td id=\"T_4563a_row21_col1\" class=\"data row21 col1\" >14.34</td>\n",
              "      <td id=\"T_4563a_row21_col2\" class=\"data row21 col2\" >0.00</td>\n",
              "      <td id=\"T_4563a_row21_col3\" class=\"data row21 col3\" >250546</td>\n",
              "      <td id=\"T_4563a_row21_col4\" class=\"data row21 col4\" >12</td>\n",
              "      <td id=\"T_4563a_row21_col5\" class=\"data row21 col5\" >S02</td>\n",
              "      <td id=\"T_4563a_row21_col6\" class=\"data row21 col6\" >26370</td>\n",
              "      <td id=\"T_4563a_row21_col7\" class=\"data row21 col7\" >nan</td>\n",
              "      <td id=\"T_4563a_row21_col8\" class=\"data row21 col8\" >nan</td>\n",
              "      <td id=\"T_4563a_row21_col9\" class=\"data row21 col9\" >nan</td>\n",
              "      <td id=\"T_4563a_row21_col10\" class=\"data row21 col10\" >nan</td>\n",
              "      <td id=\"T_4563a_row21_col11\" class=\"data row21 col11\" >nan</td>\n",
              "      <td id=\"T_4563a_row21_col12\" class=\"data row21 col12\" >nan</td>\n",
              "      <td id=\"T_4563a_row21_col13\" class=\"data row21 col13\" >nan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 141
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Save overview output in `.csv` and `.xlsx` format"
      ],
      "metadata": {
        "id": "cUZYf_LmOPk4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#add a empty columns for note-taking in a spreadsheet\n",
        "df_info.insert(loc=0,\n",
        "               column='Notes',\n",
        "               value = '')\n",
        "\n",
        "df_info.insert(loc=1,\n",
        "               column='Drop?',\n",
        "               value = '')\n",
        "\n",
        "df_info.insert(loc=2,\n",
        "               column='Change Dtype?',\n",
        "               value = '')"
      ],
      "metadata": {
        "id": "BYagHc_HjCbz"
      },
      "execution_count": 142,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#write to excel file\n",
        "df_info.to_excel(main_drive / 'notebooks' / 'eda' / f\"{output_filename}_ov.xlsx\",\n",
        "                 sheet_name=f'Overview {file_path.stem}',\n",
        "                 freeze_panes=(1,4)\n",
        "                 )"
      ],
      "metadata": {
        "id": "uZ0HHacXghoj"
      },
      "execution_count": 152,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Correlation Table\n",
        "For numeric columns only"
      ],
      "metadata": {
        "id": "2hEK3XTX0wZl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.corr(numeric_only=True)"
      ],
      "metadata": {
        "id": "3QMlpLSCYbi9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "228aed6a-cfc6-46a2-fe05-37ded7fabb31"
      },
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              SHOP_WEEK  SHOP_DATE  SHOP_WEEKDAY  SHOP_HOUR  QUANTITY  SPEND  \\\n",
              "SHOP_WEEK           NaN        NaN           NaN        NaN       NaN    NaN   \n",
              "SHOP_DATE           NaN       1.00          0.24       0.00     -0.00  -0.00   \n",
              "SHOP_WEEKDAY        NaN       0.24          1.00      -0.00     -0.00   0.00   \n",
              "SHOP_HOUR           NaN       0.00         -0.00       1.00     -0.02   0.00   \n",
              "QUANTITY            NaN      -0.00         -0.00      -0.02      1.00   0.35   \n",
              "SPEND               NaN      -0.00          0.00       0.00      0.35   1.00   \n",
              "BASKET_ID           NaN       0.01         -0.01      -0.06     -0.03   0.00   \n",
              "\n",
              "              BASKET_ID  \n",
              "SHOP_WEEK           NaN  \n",
              "SHOP_DATE          0.01  \n",
              "SHOP_WEEKDAY      -0.01  \n",
              "SHOP_HOUR         -0.06  \n",
              "QUANTITY          -0.03  \n",
              "SPEND              0.00  \n",
              "BASKET_ID          1.00  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ee31413c-f1f2-4295-a596-5bdc8ccc4cda\" 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>SHOP_WEEK</th>\n",
              "      <th>SHOP_DATE</th>\n",
              "      <th>SHOP_WEEKDAY</th>\n",
              "      <th>SHOP_HOUR</th>\n",
              "      <th>QUANTITY</th>\n",
              "      <th>SPEND</th>\n",
              "      <th>BASKET_ID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>SHOP_WEEK</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SHOP_DATE</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SHOP_WEEKDAY</th>\n",
              "      <td>NaN</td>\n",
              "      <td>0.24</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SHOP_HOUR</th>\n",
              "      <td>NaN</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>QUANTITY</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SPEND</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.35</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BASKET_ID</th>\n",
              "      <td>NaN</td>\n",
              "      <td>0.01</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.00</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-ee31413c-f1f2-4295-a596-5bdc8ccc4cda')\"\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-ee31413c-f1f2-4295-a596-5bdc8ccc4cda 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-ee31413c-f1f2-4295-a596-5bdc8ccc4cda');\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-068f7593-749a-4467-8a73-7a2aa2f7c50c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-068f7593-749a-4467-8a73-7a2aa2f7c50c')\"\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-068f7593-749a-4467-8a73-7a2aa2f7c50c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 7,\n  \"fields\": [\n    {\n      \"column\": \"SHOP_WEEK\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": null,\n        \"max\": null,\n        \"num_unique_values\": 0,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SHOP_DATE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4001509143511063,\n        \"min\": -0.004295610113276145,\n        \"max\": 1.0,\n        \"num_unique_values\": 6,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SHOP_WEEKDAY\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4013245765085129,\n        \"min\": -0.007261779644738352,\n        \"max\": 1.0,\n        \"num_unique_values\": 6,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SHOP_HOUR\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.41529884418655966,\n        \"min\": -0.05968936595919462,\n        \"max\": 1.0,\n        \"num_unique_values\": 6,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"QUANTITY\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4108757906836808,\n        \"min\": -0.029300501711964293,\n        \"max\": 1.0,\n        \"num_unique_values\": 6,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SPEND\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.40446263847902886,\n        \"min\": -0.00230431640498432,\n        \"max\": 1.0,\n        \"num_unique_values\": 6,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BASKET_ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4161528782413476,\n        \"min\": -0.05968936595919462,\n        \"max\": 1.0,\n        \"num_unique_values\": 6,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 153
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Duplicated Rows"
      ],
      "metadata": {
        "id": "trRd5L0nyrA9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df.duplicated(keep=False)]"
      ],
      "metadata": {
        "id": "oJQsc2roEy0Q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "outputId": "1767eee8-9ace-4f56-d7dd-00b58ad87a17"
      },
      "execution_count": 154,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [SHOP_WEEK, SHOP_DATE, SHOP_WEEKDAY, SHOP_HOUR, QUANTITY, SPEND, PROD_CODE, PROD_CODE_10, PROD_CODE_20, PROD_CODE_30, PROD_CODE_40, CUST_CODE, CUST_PRICE_SENSITIVITY, CUST_LIFESTAGE, BASKET_ID, BASKET_SIZE, BASKET_PRICE_SENSITIVITY, BASKET_TYPE, BASKET_DOMINANT_MISSION, STORE_CODE, STORE_FORMAT, STORE_REGION]\n",
              "Index: []"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1525f804-af71-4b43-ae17-36883713313f\" 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>SHOP_WEEK</th>\n",
              "      <th>SHOP_DATE</th>\n",
              "      <th>SHOP_WEEKDAY</th>\n",
              "      <th>SHOP_HOUR</th>\n",
              "      <th>QUANTITY</th>\n",
              "      <th>SPEND</th>\n",
              "      <th>PROD_CODE</th>\n",
              "      <th>PROD_CODE_10</th>\n",
              "      <th>PROD_CODE_20</th>\n",
              "      <th>PROD_CODE_30</th>\n",
              "      <th>PROD_CODE_40</th>\n",
              "      <th>CUST_CODE</th>\n",
              "      <th>CUST_PRICE_SENSITIVITY</th>\n",
              "      <th>CUST_LIFESTAGE</th>\n",
              "      <th>BASKET_ID</th>\n",
              "      <th>BASKET_SIZE</th>\n",
              "      <th>BASKET_PRICE_SENSITIVITY</th>\n",
              "      <th>BASKET_TYPE</th>\n",
              "      <th>BASKET_DOMINANT_MISSION</th>\n",
              "      <th>STORE_CODE</th>\n",
              "      <th>STORE_FORMAT</th>\n",
              "      <th>STORE_REGION</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\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-1525f804-af71-4b43-ae17-36883713313f')\"\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-1525f804-af71-4b43-ae17-36883713313f 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-1525f804-af71-4b43-ae17-36883713313f');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe"
            }
          },
          "metadata": {},
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Null Columns\n",
        "List of columns with all NaN values"
      ],
      "metadata": {
        "id": "xsyA0SKm0g6M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "list(df.columns[df.isnull().all(axis=0)])"
      ],
      "metadata": {
        "id": "AHoteJ8JzYk8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "edba08b8-50fd-4b5e-c592-301e45309b31"
      },
      "execution_count": 155,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {},
          "execution_count": 155
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Columns"
      ],
      "metadata": {
        "id": "ueUwGon1hT90"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## List of Column Names"
      ],
      "metadata": {
        "id": "chR475BM-pvR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "list(df.columns)"
      ],
      "metadata": {
        "id": "8N4sCnGtP_mu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b514f085-ba12-468f-f779-4a6b774fc604"
      },
      "execution_count": 156,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['SHOP_WEEK',\n",
              " 'SHOP_DATE',\n",
              " 'SHOP_WEEKDAY',\n",
              " 'SHOP_HOUR',\n",
              " 'QUANTITY',\n",
              " 'SPEND',\n",
              " 'PROD_CODE',\n",
              " 'PROD_CODE_10',\n",
              " 'PROD_CODE_20',\n",
              " 'PROD_CODE_30',\n",
              " 'PROD_CODE_40',\n",
              " 'CUST_CODE',\n",
              " 'CUST_PRICE_SENSITIVITY',\n",
              " 'CUST_LIFESTAGE',\n",
              " 'BASKET_ID',\n",
              " 'BASKET_SIZE',\n",
              " 'BASKET_PRICE_SENSITIVITY',\n",
              " 'BASKET_TYPE',\n",
              " 'BASKET_DOMINANT_MISSION',\n",
              " 'STORE_CODE',\n",
              " 'STORE_FORMAT',\n",
              " 'STORE_REGION']"
            ]
          },
          "metadata": {},
          "execution_count": 156
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Column Overview\n",
        "This function loops over each column to produce the following info:\n",
        "* name\n",
        "* count of unique values\n",
        "* datatype\n",
        "* string to copy into a new cell, for displaying all value counts for a column\n",
        "\n",
        "For value counts under the cutoff:\n",
        "* a transposed display frame of all unique values\n",
        "\n",
        "For value counts over the cutoff:\n",
        "* transposed display frames of the top and bottom 10 values and counts\n"
      ],
      "metadata": {
        "id": "Wt5lENuEtb5G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def column_overview(df, columns, cutoff=100):\n",
        "    \"\"\"\n",
        "    Display column name, count of unique values, and an easy to read dataframe of individual unique values and their counts\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    df: dataframe\n",
        "    columns: list\n",
        "    cutoff: int, maximum unique value count to display\n",
        "    Recommend string or object columns with unclear or low expected unique values.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    Prints out one result for each column in the provided list.\n",
        "    \"\"\"\n",
        "    for col in columns:\n",
        "        print(\"\\n\")\n",
        "        print(\"Column name: \" + col)\n",
        "        num_unique = str(df[col].nunique())\n",
        "        print(f\"Number of Unique Values: {num_unique}\")\n",
        "        col_datatype = str(df[col].dtype)\n",
        "        print(f\"Column Datatype: {col_datatype}\")\n",
        "        print(\"\\n\")\n",
        "\n",
        "        if int(num_unique) < cutoff:\n",
        "          print(\"use line below for vertical results\")\n",
        "          print(f\"pd.DataFrame(df['{col}'].value_counts(dropna=False))\")\n",
        "          display(pd.DataFrame(df[col].value_counts(dropna=False)).T)\n",
        "          print(u'\\u2500' * 80)\n",
        "        else:\n",
        "          print(f\"more than {cutoff} results, showing Top 10 and Bottom 10\")\n",
        "          print(\"use line below for complete results\")\n",
        "          print(f\"pd.DataFrame(df['{col}'].value_counts(dropna=False))\")\n",
        "          print(\"\\n\")\n",
        "          print(f\"Top 10 Unique Values of {col}\")\n",
        "          display(pd.DataFrame(df[col].value_counts(dropna=False).head(10)).T)\n",
        "          print(f\"Bottom 10 Unique Values of {col}\")\n",
        "          display(pd.DataFrame(df[col].value_counts(dropna=False).tail(10)).T)\n",
        "          print(u'\\u2500' * 80)\n"
      ],
      "metadata": {
        "id": "Y23TgT7KDhSb"
      },
      "execution_count": 157,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "column_overview(df, df.columns, 200)"
      ],
      "metadata": {
        "id": "MQY8SJprP88H",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "a5ac4fa1-3550-4d56-ac1c-900e193f7312"
      },
      "execution_count": 158,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Column name: SHOP_WEEK\n",
            "Number of Unique Values: 1\n",
            "Column Datatype: int64\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['SHOP_WEEK'].value_counts(dropna=False))\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "           200607\n",
              "SHOP_WEEK  250546"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8895be12-d9c7-45cf-8528-dc8aef65502a\" 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>200607</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
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            "Column name: SHOP_DATE\n",
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              "           20060416  20060415  20060410  20060414  20060413  20060412  \\\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: SHOP_WEEKDAY\n",
            "Number of Unique Values: 7\n",
            "Column Datatype: int64\n",
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              "                  1      7      2      6      5      4      3\n",
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          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: SHOP_HOUR\n",
            "Number of Unique Values: 14\n",
            "Column Datatype: int64\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['SHOP_HOUR'].value_counts(dropna=False))\n"
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              "              21     13     15     14     16     12     17     18     11  \\\n",
              "SHOP_HOUR  25092  24337  22892  22646  20916  20478  19713  17440  16900   \n",
              "\n",
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              "      <th>9</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
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              "      <td>25092</td>\n",
              "      <td>24337</td>\n",
              "      <td>22892</td>\n",
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              "      <td>17440</td>\n",
              "      <td>16900</td>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "                                                    [key], {});\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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        {
          "output_type": "stream",
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          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: QUANTITY\n",
            "Number of Unique Values: 46\n",
            "Column Datatype: int64\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['QUANTITY'].value_counts(dropna=False))\n"
          ]
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          "data": {
            "text/plain": [
              "             1      3     4     6     5    7    8    9    11   10   12   14   \\\n",
              "QUANTITY  205634  35112  5080  1693  1018  607  455  324  112   89   84   64   \n",
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              "          13   16   17   15   18   19   21   22   27   20   23   26   24   \\\n",
              "QUANTITY   42   40   39   36   24   11    9    8    8    6    6    6    5   \n",
              "\n",
              "          40   34   32   35   28   31   30   25   29   60   33   45   53   \\\n",
              "QUANTITY    3    3    3    3    3    2    2    2    1    1    1    1    1   \n",
              "\n",
              "          36   37   59   68   81   275  76   73   \n",
              "QUANTITY    1    1    1    1    1    1    1    1  "
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              "                                                    [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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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: SPEND\n",
            "Number of Unique Values: 1797\n",
            "Column Datatype: float64\n",
            "\n",
            "\n",
            "more than 200 results, showing Top 10 and Bottom 10\n",
            "use line below for complete results\n",
            "pd.DataFrame(df['SPEND'].value_counts(dropna=False))\n",
            "\n",
            "\n",
            "Top 10 Unique Values of SPEND\n"
          ]
        },
        {
          "output_type": "display_data",
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            "text/plain": [
              "       1.54  0.97  0.98  1.01  0.86  0.40  0.70  1.02  0.84  0.53\n",
              "SPEND  4341  3269  3269  2551  2328  2236  1983  1937  1935  1912"
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            "Bottom 10 Unique Values of SPEND\n"
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            "text/plain": [
              "       17.92  26.50  29.72  28.31  26.59  8.89   25.95  33.69  19.86  11.43\n",
              "SPEND      1      1      1      1      1      1      1      1      1      1"
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          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: PROD_CODE\n",
            "Number of Unique Values: 3809\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "more than 200 results, showing Top 10 and Bottom 10\n",
            "use line below for complete results\n",
            "pd.DataFrame(df['PROD_CODE'].value_counts(dropna=False))\n",
            "\n",
            "\n",
            "Top 10 Unique Values of PROD_CODE\n"
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            "text/plain": [
              "           PRD0903052  PRD0904358  PRD0900121  PRD0901265  PRD0900830  \\\n",
              "PROD_CODE        5968        3896        3453        2388        1667   \n",
              "\n",
              "           PRD0903074  PRD0904887  PRD0900302  PRD0904976  PRD0901887  \n",
              "PROD_CODE        1389        1346        1300        1266        1252  "
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            "Bottom 10 Unique Values of PROD_CODE\n"
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              "           PRD0903752  PRD0903690  PRD0901462  PRD0904483  PRD0900847  \\\n",
              "PROD_CODE           1           1           1           1           1   \n",
              "\n",
              "           PRD0903606  PRD0901793  PRD0903572  PRD0902003  PRD0902485  \n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: PROD_CODE_10\n",
            "Number of Unique Values: 242\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "more than 200 results, showing Top 10 and Bottom 10\n",
            "use line below for complete results\n",
            "pd.DataFrame(df['PROD_CODE_10'].value_counts(dropna=False))\n",
            "\n",
            "\n",
            "Top 10 Unique Values of PROD_CODE_10\n"
          ]
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              "              CL00063  CL00031  CL00070  CL00045  CL00067  CL00073  CL00079  \\\n",
              "PROD_CODE_10    11041     7789     5748     5522     5464     5139     4984   \n",
              "\n",
              "              CL00043  CL00140  CL00201  \n",
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            "Bottom 10 Unique Values of PROD_CODE_10\n"
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              "              CL00194  CL00242  CL00184  CL00019  CL00183  CL00109  CL00168  \\\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: PROD_CODE_20\n",
            "Number of Unique Values: 89\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['PROD_CODE_20'].value_counts(dropna=False))\n"
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              "              DEP00019  DEP00008  DEP00011  DEP00022  DEP00052  DEP00067  \\\n",
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              "      <td>717</td>\n",
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              "      <td>577</td>\n",
              "      <td>567</td>\n",
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              "      <td>293</td>\n",
              "      <td>275</td>\n",
              "      <td>266</td>\n",
              "      <td>244</td>\n",
              "      <td>202</td>\n",
              "      <td>194</td>\n",
              "      <td>192</td>\n",
              "      <td>180</td>\n",
              "      <td>157</td>\n",
              "      <td>144</td>\n",
              "      <td>142</td>\n",
              "      <td>122</td>\n",
              "      <td>52</td>\n",
              "      <td>50</td>\n",
              "      <td>49</td>\n",
              "      <td>47</td>\n",
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              "      <td>28</td>\n",
              "      <td>27</td>\n",
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              "      <td>21</td>\n",
              "      <td>17</td>\n",
              "      <td>15</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>10</td>\n",
              "      <td>7</td>\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: PROD_CODE_30\n",
            "Number of Unique Values: 31\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['PROD_CODE_30'].value_counts(dropna=False))\n"
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: PROD_CODE_40\n",
            "Number of Unique Values: 9\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: CUST_CODE\n",
            "Number of Unique Values: 17243\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "more than 200 results, showing Top 10 and Bottom 10\n",
            "use line below for complete results\n",
            "pd.DataFrame(df['CUST_CODE'].value_counts(dropna=False))\n",
            "\n",
            "\n",
            "Top 10 Unique Values of CUST_CODE\n"
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              "             NaN  CUST0000701659  CUST0000640576  CUST0000756781  \\\n",
              "CUST_CODE  48335             101              71              71   \n",
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              "           CUST0000804366  CUST0000566247  CUST0000113121  CUST0000965332  \\\n",
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            "Bottom 10 Unique Values of CUST_CODE\n"
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              "           CUST0000873840  CUST0000239976  CUST0000989742  CUST0000937245  \\\n",
              "CUST_CODE               1               1               1               1   \n",
              "\n",
              "           CUST0000642010  CUST0000838133  CUST0000406552  CUST0000576814  \\\n",
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          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: CUST_PRICE_SENSITIVITY\n",
            "Number of Unique Values: 4\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['CUST_PRICE_SENSITIVITY'].value_counts(dropna=False))\n"
          ]
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              "                           MM     UM     LA    NaN    XX\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: CUST_LIFESTAGE\n",
            "Number of Unique Values: 6\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['CUST_LIFESTAGE'].value_counts(dropna=False))\n"
          ]
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          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: BASKET_ID\n",
            "Number of Unique Values: 38007\n",
            "Column Datatype: int64\n",
            "\n",
            "\n",
            "more than 200 results, showing Top 10 and Bottom 10\n",
            "use line below for complete results\n",
            "pd.DataFrame(df['BASKET_ID'].value_counts(dropna=False))\n",
            "\n",
            "\n",
            "Top 10 Unique Values of BASKET_ID\n"
          ]
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              "\n",
              "           994100100067226  994100100425072  994100100259078  994100100573449  \\\n",
              "BASKET_ID               53               53               51               51   \n",
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            "Bottom 10 Unique Values of BASKET_ID\n"
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              "           994100100125327  994100100091014  994100100703247  994100100749925  \\\n",
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              "\n",
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              "BASKET_ID                1                1                1                1   \n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
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            "Number of Unique Values: 4\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: BASKET_TYPE\n",
            "Number of Unique Values: 4\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['BASKET_TYPE'].value_counts(dropna=False))\n"
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              "      <td>113151</td>\n",
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              "      <td>46736</td>\n",
              "      <td>252</td>\n",
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              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "        document.querySelector('#df-22072af6-bf1e-47c4-958c-1432cc74f96c button.colab-df-convert');\n",
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              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-22072af6-bf1e-47c4-958c-1432cc74f96c');\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",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"column_overview(df, df\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"Top Up\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 113151,\n        \"max\": 113151,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          113151\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Full Shop\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 90407,\n        \"max\": 90407,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          90407\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Small Shop\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 46736,\n        \"max\": 46736,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          46736\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"XX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 252,\n        \"max\": 252,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          252\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: BASKET_DOMINANT_MISSION\n",
            "Number of Unique Values: 5\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "use line below for vertical results\n",
            "pd.DataFrame(df['BASKET_DOMINANT_MISSION'].value_counts(dropna=False))\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                          Fresh  Mixed  Grocery  Nonfood   XX\n",
              "BASKET_DOMINANT_MISSION  129265  92796    24900     3333  252"
            ],
            "text/html": [
              "\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-747606ff-62b6-4834-9725-a6cb7afae26d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
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              "        const element = document.querySelector('#df-747606ff-62b6-4834-9725-a6cb7afae26d');\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",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "\n",
              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"column_overview(df, df\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"Fresh\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 129265,\n        \"max\": 129265,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          129265\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Mixed\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 92796,\n        \"max\": 92796,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          92796\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Grocery\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 24900,\n        \"max\": 24900,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          24900\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Nonfood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 3333,\n        \"max\": 3333,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          3333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"XX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 252,\n        \"max\": 252,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          252\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n",
            "\n",
            "\n",
            "Column name: STORE_CODE\n",
            "Number of Unique Values: 748\n",
            "Column Datatype: object\n",
            "\n",
            "\n",
            "more than 200 results, showing Top 10 and Bottom 10\n",
            "use line below for complete results\n",
            "pd.DataFrame(df['STORE_CODE'].value_counts(dropna=False))\n",
            "\n",
            "\n",
            "Top 10 Unique Values of STORE_CODE\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "            STORE01423  STORE00696  STORE00729  STORE01604  STORE00278  \\\n",
              "STORE_CODE        1224        1109        1088        1038        1006   \n",
              "\n",
              "            STORE02797  STORE02577  STORE01707  STORE01007  STORE00030  \n",
              "STORE_CODE         948         918         911         911         902  "
            ],
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              "      background-color: #434B5C;\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",
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              "            STORE02457  STORE00843  STORE01804  STORE01769  STORE00183  \\\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
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            "────────────────────────────────────────────────────────────────────────────────\n",
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              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-19350e7c-40d0-4cb4-8f69-350508d8df9f')\"\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-19350e7c-40d0-4cb4-8f69-350508d8df9f 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-19350e7c-40d0-4cb4-8f69-350508d8df9f');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "────────────────────────────────────────────────────────────────────────────────\n"
          ]
        }
      ]
    }
  ]
}