Create_Viz_with_PandasAI.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Read Data and Cleaning Data"
      ],
      "metadata": {
        "id": "tTOiJGiodNOE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pandasai"
      ],
      "metadata": {
        "id": "EXGMB3djAZEm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fcb7c67b-768f-4262-989c-b5354dae7bcd"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pandasai in /usr/local/lib/python3.10/dist-packages (2.2.10)\n",
            "Requirement already satisfied: astor<0.9.0,>=0.8.1 in /usr/local/lib/python3.10/dist-packages (from pandasai) (0.8.1)\n",
            "Requirement already satisfied: duckdb<1 in /usr/local/lib/python3.10/dist-packages (from pandasai) (0.10.3)\n",
            "Requirement already satisfied: faker<20.0.0,>=19.12.0 in /usr/local/lib/python3.10/dist-packages (from pandasai) (19.13.0)\n",
            "Requirement already satisfied: jinja2<4.0.0,>=3.1.3 in /usr/local/lib/python3.10/dist-packages (from pandasai) (3.1.4)\n",
            "Requirement already satisfied: matplotlib<4.0.0,>=3.7.1 in /usr/local/lib/python3.10/dist-packages (from pandasai) (3.7.1)\n",
            "Requirement already satisfied: openai<2 in /usr/local/lib/python3.10/dist-packages (from pandasai) (1.35.13)\n",
            "Requirement already satisfied: pandas==1.5.3 in /usr/local/lib/python3.10/dist-packages (from pandasai) (1.5.3)\n",
            "Requirement already satisfied: pillow<11.0.0,>=10.1.0 in /usr/local/lib/python3.10/dist-packages (from pandasai) (10.4.0)\n",
            "Requirement already satisfied: pydantic<3,>=1 in /usr/local/lib/python3.10/dist-packages (from pandasai) (2.8.2)\n",
            "Requirement already satisfied: python-dotenv<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from pandasai) (1.0.1)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.31.0 in /usr/local/lib/python3.10/dist-packages (from pandasai) (2.31.0)\n",
            "Requirement already satisfied: scipy<2.0.0,>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from pandasai) (1.11.4)\n",
            "Requirement already satisfied: sqlalchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from pandasai) (2.0.31)\n",
            "Requirement already satisfied: sqlglot[rs]<26.0.0,>=25.0.3 in /usr/local/lib/python3.10/dist-packages (from pandasai) (25.5.1)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas==1.5.3->pandasai) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas==1.5.3->pandasai) (2023.4)\n",
            "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from pandas==1.5.3->pandasai) (1.25.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2<4.0.0,>=3.1.3->pandasai) (2.1.5)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib<4.0.0,>=3.7.1->pandasai) (1.2.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib<4.0.0,>=3.7.1->pandasai) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib<4.0.0,>=3.7.1->pandasai) (4.53.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib<4.0.0,>=3.7.1->pandasai) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib<4.0.0,>=3.7.1->pandasai) (24.1)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib<4.0.0,>=3.7.1->pandasai) (3.1.2)\n",
            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai<2->pandasai) (3.7.1)\n",
            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from openai<2->pandasai) (1.7.0)\n",
            "Requirement already satisfied: httpx<1,>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from openai<2->pandasai) (0.27.0)\n",
            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from openai<2->pandasai) (1.3.1)\n",
            "Requirement already satisfied: tqdm>4 in /usr/local/lib/python3.10/dist-packages (from openai<2->pandasai) (4.66.4)\n",
            "Requirement already satisfied: typing-extensions<5,>=4.7 in /usr/local/lib/python3.10/dist-packages (from openai<2->pandasai) (4.12.2)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->pandasai) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.20.1 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->pandasai) (2.20.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.31.0->pandasai) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.31.0->pandasai) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.31.0->pandasai) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.31.0->pandasai) (2024.7.4)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from sqlalchemy<3,>=1.4->pandasai) (3.0.3)\n",
            "Requirement already satisfied: sqlglotrs==0.2.8 in /usr/local/lib/python3.10/dist-packages (from sqlglot[rs]<26.0.0,>=25.0.3->pandasai) (0.2.8)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->openai<2->pandasai) (1.2.1)\n",
            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->openai<2->pandasai) (1.0.5)\n",
            "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.10/dist-packages (from httpcore==1.*->httpx<1,>=0.23.0->openai<2->pandasai) (0.14.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas==1.5.3->pandasai) (1.16.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from pandasai import SmartDataframe\n",
        "from pandasai.llm.openai import OpenAI\n",
        "\n",
        "\n",
        "\n",
        "# Initialize PandasAI with your OpenAI key\n",
        "key = \"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\"  # Replace with your OpenAI API key\n",
        "llm = OpenAI(api_token=key)\n",
        "# pandas_ai = SmartDataframe(sales_by_country, config={\"llm\": llm})\n",
        "# pandas_ai.chat('which country has the highest sales?')\n",
        "\n"
      ],
      "metadata": {
        "id": "nkWx_XpzYdfD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#how to read data in google sheet\n",
        "sheet_url = 'https://docs.google.com/spreadsheets/d/1mSslatBwaydYUdZYdJSHkZA-wisvV1ViXhpQkGBgH6o/edit#gid=1903509374'\n",
        "sheet_url_trf = sheet_url.replace('/edit#gid=', '/export?format=csv&gid=')\n",
        "print(sheet_url_trf)\n",
        "\n",
        "df = pd.read_csv(sheet_url_trf)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 223
        },
        "id": "OLX7Tg1EdRKA",
        "outputId": "93daa87a-e668-49a5-c728-9de0686982c6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "https://docs.google.com/spreadsheets/d/1mSslatBwaydYUdZYdJSHkZA-wisvV1ViXhpQkGBgH6o/export?format=csv&gid=1903509374\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date      Payment   Invoice ID Branch       City Customer type  \\\n",
              "0   1/5/2019      Ewallet  750-67-8428      A     Yangon        Member   \n",
              "1   3/8/2019         Cash  226-31-3081      C  Naypyitaw        Normal   \n",
              "2   3/3/2019  Credit card  631-41-3108      A     Yangon        Normal   \n",
              "3  1/27/2019      Ewallet  123-19-1176      A     Yangon        Member   \n",
              "4   2/8/2019      Ewallet  373-73-7910      A     Yangon        Normal   \n",
              "\n",
              "   Gender            Product line  Unit price  Quantity  \n",
              "0  Female       Health and beauty       74.69         7  \n",
              "1  Female  Electronic accessories       15.28         5  \n",
              "2    Male      Home and lifestyle       46.33         7  \n",
              "3    Male       Health and beauty       58.22         8  \n",
              "4    Male       Sports and travel       86.31         7  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5228debc-601b-4fd5-853c-dc121d49c9dd\" 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>Date</th>\n",
              "      <th>Payment</th>\n",
              "      <th>Invoice ID</th>\n",
              "      <th>Branch</th>\n",
              "      <th>City</th>\n",
              "      <th>Customer type</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Product line</th>\n",
              "      <th>Unit price</th>\n",
              "      <th>Quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1/5/2019</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>750-67-8428</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Female</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>74.69</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3/8/2019</td>\n",
              "      <td>Cash</td>\n",
              "      <td>226-31-3081</td>\n",
              "      <td>C</td>\n",
              "      <td>Naypyitaw</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Female</td>\n",
              "      <td>Electronic accessories</td>\n",
              "      <td>15.28</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3/3/2019</td>\n",
              "      <td>Credit card</td>\n",
              "      <td>631-41-3108</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>46.33</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1/27/2019</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>123-19-1176</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Male</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>58.22</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2/8/2019</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>373-73-7910</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Sports and travel</td>\n",
              "      <td>86.31</td>\n",
              "      <td>7</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-5228debc-601b-4fd5-853c-dc121d49c9dd')\"\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-5228debc-601b-4fd5-853c-dc121d49c9dd 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-5228debc-601b-4fd5-853c-dc121d49c9dd');\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-c3760a04-b47b-4b19-9b79-54877a62e33f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c3760a04-b47b-4b19-9b79-54877a62e33f')\"\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-c3760a04-b47b-4b19-9b79-54877a62e33f 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",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 1000,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 89,\n        \"samples\": [\n          \"2/14/2019\",\n          \"1/26/2019\",\n          \"2/2/2019\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Payment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Ewallet\",\n          \"Cash\",\n          \"Credit card\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Invoice ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          \"451-28-5717\",\n          \"137-63-5492\",\n          \"733-29-1227\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Branch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"C\",\n          \"B\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Yangon\",\n          \"Naypyitaw\",\n          \"Mandalay\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Customer type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Normal\",\n          \"Member\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Male\",\n          \"female\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Product line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Health and beauty\",\n          \"Electronic accessories\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Unit price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26.49462834791978,\n        \"min\": 10.08,\n        \"max\": 99.96,\n        \"num_unique_values\": 943,\n        \"samples\": [\n          12.45,\n          70.74\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 10,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          1,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DPib6WJneM44",
        "outputId": "5e2e34c9-94ee-4461-d34a-5f738e1674ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1000 entries, 0 to 999\n",
            "Data columns (total 10 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   Date           1000 non-null   object \n",
            " 1   Payment        1000 non-null   object \n",
            " 2   Invoice ID     1000 non-null   object \n",
            " 3   Branch         1000 non-null   object \n",
            " 4   City           1000 non-null   object \n",
            " 5   Customer type  1000 non-null   object \n",
            " 6   Gender         1000 non-null   object \n",
            " 7   Product line   1000 non-null   object \n",
            " 8   Unit price     1000 non-null   float64\n",
            " 9   Quantity       1000 non-null   int64  \n",
            "dtypes: float64(1), int64(1), object(8)\n",
            "memory usage: 78.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "49MSxNgEfAWj",
        "outputId": "2d1121a8-3d60-4211-8394-7e7ece1c448a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Date', 'Payment', 'Invoice ID', 'Branch', 'City', 'Customer type',\n",
              "       'Gender', 'Product line', 'Unit price', 'Quantity'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#change type date\n",
        "df_cleaned = df.copy()\n",
        "\n",
        "df_cleaned['Date'] = pd.to_datetime(df_cleaned['Date'])\n",
        "df_cleaned['Revenue'] = df_cleaned['Unit price'] * df_cleaned['Quantity']\n",
        "\n",
        "print(df_cleaned.info())\n",
        "df_cleaned.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 536
        },
        "id": "jcU6DdkXfYhN",
        "outputId": "971061d7-a4df-4a94-f1c1-823cdb2d55aa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1000 entries, 0 to 999\n",
            "Data columns (total 11 columns):\n",
            " #   Column         Non-Null Count  Dtype         \n",
            "---  ------         --------------  -----         \n",
            " 0   Date           1000 non-null   datetime64[ns]\n",
            " 1   Payment        1000 non-null   object        \n",
            " 2   Invoice ID     1000 non-null   object        \n",
            " 3   Branch         1000 non-null   object        \n",
            " 4   City           1000 non-null   object        \n",
            " 5   Customer type  1000 non-null   object        \n",
            " 6   Gender         1000 non-null   object        \n",
            " 7   Product line   1000 non-null   object        \n",
            " 8   Unit price     1000 non-null   float64       \n",
            " 9   Quantity       1000 non-null   int64         \n",
            " 10  Revenue        1000 non-null   float64       \n",
            "dtypes: datetime64[ns](1), float64(2), int64(1), object(7)\n",
            "memory usage: 86.1+ KB\n",
            "None\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date      Payment   Invoice ID Branch       City Customer type  \\\n",
              "0 2019-01-05      Ewallet  750-67-8428      A     Yangon        Member   \n",
              "1 2019-03-08         Cash  226-31-3081      C  Naypyitaw        Normal   \n",
              "2 2019-03-03  Credit card  631-41-3108      A     Yangon        Normal   \n",
              "3 2019-01-27      Ewallet  123-19-1176      A     Yangon        Member   \n",
              "4 2019-02-08      Ewallet  373-73-7910      A     Yangon        Normal   \n",
              "\n",
              "   Gender            Product line  Unit price  Quantity  Revenue  \n",
              "0  Female       Health and beauty       74.69         7   522.83  \n",
              "1  Female  Electronic accessories       15.28         5    76.40  \n",
              "2    Male      Home and lifestyle       46.33         7   324.31  \n",
              "3    Male       Health and beauty       58.22         8   465.76  \n",
              "4    Male       Sports and travel       86.31         7   604.17  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2251c414-b796-44c1-a72c-2603f85604bf\" 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>Date</th>\n",
              "      <th>Payment</th>\n",
              "      <th>Invoice ID</th>\n",
              "      <th>Branch</th>\n",
              "      <th>City</th>\n",
              "      <th>Customer type</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Product line</th>\n",
              "      <th>Unit price</th>\n",
              "      <th>Quantity</th>\n",
              "      <th>Revenue</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-05</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>750-67-8428</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Female</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>74.69</td>\n",
              "      <td>7</td>\n",
              "      <td>522.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-03-08</td>\n",
              "      <td>Cash</td>\n",
              "      <td>226-31-3081</td>\n",
              "      <td>C</td>\n",
              "      <td>Naypyitaw</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Female</td>\n",
              "      <td>Electronic accessories</td>\n",
              "      <td>15.28</td>\n",
              "      <td>5</td>\n",
              "      <td>76.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-03-03</td>\n",
              "      <td>Credit card</td>\n",
              "      <td>631-41-3108</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>46.33</td>\n",
              "      <td>7</td>\n",
              "      <td>324.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-27</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>123-19-1176</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Male</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>58.22</td>\n",
              "      <td>8</td>\n",
              "      <td>465.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-02-08</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>373-73-7910</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Sports and travel</td>\n",
              "      <td>86.31</td>\n",
              "      <td>7</td>\n",
              "      <td>604.17</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-2251c414-b796-44c1-a72c-2603f85604bf')\"\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-2251c414-b796-44c1-a72c-2603f85604bf 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-2251c414-b796-44c1-a72c-2603f85604bf');\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-f1b125c2-4ad0-4133-9f58-18eedb545e48\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f1b125c2-4ad0-4133-9f58-18eedb545e48')\"\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-f1b125c2-4ad0-4133-9f58-18eedb545e48 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_cleaned",
              "summary": "{\n  \"name\": \"df_cleaned\",\n  \"rows\": 1000,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2019-01-01 00:00:00\",\n        \"max\": \"2019-03-30 00:00:00\",\n        \"num_unique_values\": 89,\n        \"samples\": [\n          \"2019-02-14 00:00:00\",\n          \"2019-01-26 00:00:00\",\n          \"2019-02-02 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Payment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Ewallet\",\n          \"Cash\",\n          \"Credit card\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Invoice ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          \"451-28-5717\",\n          \"137-63-5492\",\n          \"733-29-1227\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Branch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"C\",\n          \"B\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Yangon\",\n          \"Naypyitaw\",\n          \"Mandalay\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Customer type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Normal\",\n          \"Member\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Male\",\n          \"female\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Product line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Health and beauty\",\n          \"Electronic accessories\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Unit price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26.49462834791978,\n        \"min\": 10.08,\n        \"max\": 99.96,\n        \"num_unique_values\": 943,\n        \"samples\": [\n          12.45,\n          70.74\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 10,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          1,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Revenue\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 234.1765096199732,\n        \"min\": 10.17,\n        \"max\": 993.0,\n        \"num_unique_values\": 991,\n        \"samples\": [\n          207.26999999999998,\n          385.09999999999997\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#check typo\n",
        "\n",
        "df_cleaned['Gender'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dwL8hV-sgcLE",
        "outputId": "619b9d92-b7bf-48ac-ef99-02886ec0c94c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Female    498\n",
              "Male      490\n",
              "male        9\n",
              "female      2\n",
              "fml         1\n",
              "Name: Gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for col_name in ['Payment',  'Branch', 'City', 'Customer type',\n",
        "       'Gender', 'Product line']:\n",
        "  print(df_cleaned[col_name].value_counts(), '\\n')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IPSYIPQOhN4u",
        "outputId": "7406caae-cf2a-403f-9747-63b07165e333"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Ewallet        345\n",
            "Cash           344\n",
            "Credit card    311\n",
            "Name: Payment, dtype: int64 \n",
            "\n",
            "A    340\n",
            "B    332\n",
            "C    328\n",
            "Name: Branch, dtype: int64 \n",
            "\n",
            "Yangon       340\n",
            "Mandalay     332\n",
            "Naypyitaw    328\n",
            "Name: City, dtype: int64 \n",
            "\n",
            "Member    501\n",
            "Normal    499\n",
            "Name: Customer type, dtype: int64 \n",
            "\n",
            "Female    498\n",
            "Male      490\n",
            "male        9\n",
            "female      2\n",
            "fml         1\n",
            "Name: Gender, dtype: int64 \n",
            "\n",
            "Fashion accessories       178\n",
            "Food and beverages        174\n",
            "Electronic accessories    170\n",
            "Sports and travel         166\n",
            "Home and lifestyle        160\n",
            "Health and beauty         152\n",
            "Name: Product line, dtype: int64 \n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#replace\n",
        "dict_typo = {'male' : 'Male',\n",
        "             'female':'Female',\n",
        "             'fml': 'Female'}\n",
        "\n",
        "df_replaced = df_cleaned.replace(dict_typo)\n",
        "df_replaced.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "UgAP_MFViA3-",
        "outputId": "4fc212e1-976b-4a44-ce71-1c69872747df"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date      Payment   Invoice ID Branch       City Customer type  \\\n",
              "0 2019-01-05      Ewallet  750-67-8428      A     Yangon        Member   \n",
              "1 2019-03-08         Cash  226-31-3081      C  Naypyitaw        Normal   \n",
              "2 2019-03-03  Credit card  631-41-3108      A     Yangon        Normal   \n",
              "3 2019-01-27      Ewallet  123-19-1176      A     Yangon        Member   \n",
              "4 2019-02-08      Ewallet  373-73-7910      A     Yangon        Normal   \n",
              "\n",
              "   Gender            Product line  Unit price  Quantity  Revenue  \n",
              "0  Female       Health and beauty       74.69         7   522.83  \n",
              "1  Female  Electronic accessories       15.28         5    76.40  \n",
              "2    Male      Home and lifestyle       46.33         7   324.31  \n",
              "3    Male       Health and beauty       58.22         8   465.76  \n",
              "4    Male       Sports and travel       86.31         7   604.17  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5007cee9-af85-40ad-b2a2-ea408b167c40\" 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>Date</th>\n",
              "      <th>Payment</th>\n",
              "      <th>Invoice ID</th>\n",
              "      <th>Branch</th>\n",
              "      <th>City</th>\n",
              "      <th>Customer type</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Product line</th>\n",
              "      <th>Unit price</th>\n",
              "      <th>Quantity</th>\n",
              "      <th>Revenue</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-05</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>750-67-8428</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Female</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>74.69</td>\n",
              "      <td>7</td>\n",
              "      <td>522.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-03-08</td>\n",
              "      <td>Cash</td>\n",
              "      <td>226-31-3081</td>\n",
              "      <td>C</td>\n",
              "      <td>Naypyitaw</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Female</td>\n",
              "      <td>Electronic accessories</td>\n",
              "      <td>15.28</td>\n",
              "      <td>5</td>\n",
              "      <td>76.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-03-03</td>\n",
              "      <td>Credit card</td>\n",
              "      <td>631-41-3108</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>46.33</td>\n",
              "      <td>7</td>\n",
              "      <td>324.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-27</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>123-19-1176</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Male</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>58.22</td>\n",
              "      <td>8</td>\n",
              "      <td>465.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-02-08</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>373-73-7910</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Sports and travel</td>\n",
              "      <td>86.31</td>\n",
              "      <td>7</td>\n",
              "      <td>604.17</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-5007cee9-af85-40ad-b2a2-ea408b167c40')\"\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-5007cee9-af85-40ad-b2a2-ea408b167c40 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-5007cee9-af85-40ad-b2a2-ea408b167c40');\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-ee4da68e-4c31-44a9-a29f-cf41f38428da\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ee4da68e-4c31-44a9-a29f-cf41f38428da')\"\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-ee4da68e-4c31-44a9-a29f-cf41f38428da 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_replaced",
              "summary": "{\n  \"name\": \"df_replaced\",\n  \"rows\": 1000,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2019-01-01 00:00:00\",\n        \"max\": \"2019-03-30 00:00:00\",\n        \"num_unique_values\": 89,\n        \"samples\": [\n          \"2019-02-14 00:00:00\",\n          \"2019-01-26 00:00:00\",\n          \"2019-02-02 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Payment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Ewallet\",\n          \"Cash\",\n          \"Credit card\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Invoice ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1000,\n        \"samples\": [\n          \"451-28-5717\",\n          \"137-63-5492\",\n          \"733-29-1227\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Branch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"C\",\n          \"B\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Yangon\",\n          \"Naypyitaw\",\n          \"Mandalay\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Customer type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Normal\",\n          \"Member\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Male\",\n          \"Female\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Product line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Health and beauty\",\n          \"Electronic accessories\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Unit price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26.49462834791978,\n        \"min\": 10.08,\n        \"max\": 99.96,\n        \"num_unique_values\": 943,\n        \"samples\": [\n          12.45,\n          70.74\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 10,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          1,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Revenue\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 234.1765096199732,\n        \"min\": 10.17,\n        \"max\": 993.0,\n        \"num_unique_values\": 991,\n        \"samples\": [\n          207.26999999999998,\n          385.09999999999997\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_replaced['Gender'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8uo6Z96eiyXL",
        "outputId": "5a575aa5-825a-47d0-cce6-593d239b9f54"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Female    501\n",
              "Male      499\n",
              "Name: Gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_replaced['Invoice ID'].duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QfbFidkPi-4Z",
        "outputId": "3e23ef15-1702-48b1-cb74-2e6b59e7b22b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "ZRr7SNmnjTSb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# EDA"
      ],
      "metadata": {
        "id": "udmc3u65jp2c"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## daily trend overall"
      ],
      "metadata": {
        "id": "s5BIwFRkjx3A"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agg_daily = df_replaced.groupby('Date', as_index=False)['Revenue', 'Quantity'].sum()\n",
        "agg_daily.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "ym39wq6Yjweo",
        "outputId": "ef124eec-e373-489a-a414-7952c6ad227d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-15-316445d7fbb2>:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  agg_daily = df_replaced.groupby('Date', as_index=False)['Revenue', 'Quantity'].sum()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date  Revenue  Quantity\n",
              "0 2019-01-01  4519.22        81\n",
              "1 2019-01-02  1852.86        48\n",
              "2 2019-01-03  1979.17        37\n",
              "3 2019-01-04  1546.37        32\n",
              "4 2019-01-05  3368.27        55"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e19824e4-9a1a-49ee-bd14-bcc8b1f70e35\" 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>Date</th>\n",
              "      <th>Revenue</th>\n",
              "      <th>Quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-01</td>\n",
              "      <td>4519.22</td>\n",
              "      <td>81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-01-02</td>\n",
              "      <td>1852.86</td>\n",
              "      <td>48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-01-03</td>\n",
              "      <td>1979.17</td>\n",
              "      <td>37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-04</td>\n",
              "      <td>1546.37</td>\n",
              "      <td>32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-01-05</td>\n",
              "      <td>3368.27</td>\n",
              "      <td>55</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-e19824e4-9a1a-49ee-bd14-bcc8b1f70e35')\"\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-e19824e4-9a1a-49ee-bd14-bcc8b1f70e35 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-e19824e4-9a1a-49ee-bd14-bcc8b1f70e35');\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-24746aa6-74e1-491d-ad29-416324cfd151\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-24746aa6-74e1-491d-ad29-416324cfd151')\"\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-24746aa6-74e1-491d-ad29-416324cfd151 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": "agg_daily",
              "summary": "{\n  \"name\": \"agg_daily\",\n  \"rows\": 89,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2019-01-01 00:00:00\",\n        \"max\": \"2019-03-30 00:00:00\",\n        \"num_unique_values\": 89,\n        \"samples\": [\n          \"2019-02-14 00:00:00\",\n          \"2019-02-23 00:00:00\",\n          \"2019-01-31 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Revenue\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1454.894858780945,\n        \"min\": 889.75,\n        \"max\": 7118.14,\n        \"num_unique_values\": 89,\n        \"samples\": [\n          2337.23,\n          2228.1800000000003,\n          4983.33\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 22,\n        \"min\": 18,\n        \"max\": 128,\n        \"num_unique_values\": 54,\n        \"samples\": [\n          34,\n          57,\n          99\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.rcParams[\"figure.figsize\"] = (20,5)\n",
        "\n",
        "plt.plot('Date','Revenue', data=agg_daily)\n",
        "plt.title('Revenue trend')\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Rev($)')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "qPPSQhIYkEmY",
        "outputId": "251942c3-b40e-487c-d297-08722144096a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "revenue of our data has seasonality"
      ],
      "metadata": {
        "id": "T5G7ixZOkg6z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.lineplot(data = agg_daily, x= 'Date', y='Quantity')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "WT72CTNlkdw-",
        "outputId": "d95d05c9-135b-4d82-bd4e-21b1ae39919d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Date', ylabel='Quantity'>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pandas_ai = SmartDataframe(df_replaced, config={\"llm\": llm})\n",
        "chart_ai = pandas_ai.chat('create trend line for revenue with seaborn with dark background')\n",
        "chart_ai"
      ],
      "metadata": {
        "id": "k4de7MZJkzYF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "outputId": "b8444d1b-2350-4096-f8f8-a6ae5b7ad5cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/exports/charts/temp_chart.png'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 87
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## By Payment"
      ],
      "metadata": {
        "id": "gWAsnx8vk4CJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agg_payment = df_replaced.groupby('Payment', as_index=False).agg({'Revenue':'sum', 'Invoice ID':'nunique'})\n",
        "agg_payment.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "V2Lmuq9Nk6BS",
        "outputId": "0aaffab9-b448-4130-a355-2d30259c0923"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Payment    Revenue  Invoice ID\n",
              "0         Cash  106863.40         344\n",
              "1  Credit card   95968.64         311\n",
              "2      Ewallet  104755.34         345"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-dfb2267e-86ba-4f43-bbbb-5936bf09b487\" 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>Payment</th>\n",
              "      <th>Revenue</th>\n",
              "      <th>Invoice ID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Cash</td>\n",
              "      <td>106863.40</td>\n",
              "      <td>344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Credit card</td>\n",
              "      <td>95968.64</td>\n",
              "      <td>311</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Ewallet</td>\n",
              "      <td>104755.34</td>\n",
              "      <td>345</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-dfb2267e-86ba-4f43-bbbb-5936bf09b487')\"\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-dfb2267e-86ba-4f43-bbbb-5936bf09b487 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-dfb2267e-86ba-4f43-bbbb-5936bf09b487');\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-5e1179b6-69ce-45c5-8525-8d0949bbfcd7\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5e1179b6-69ce-45c5-8525-8d0949bbfcd7')\"\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-5e1179b6-69ce-45c5-8525-8d0949bbfcd7 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": "agg_payment",
              "summary": "{\n  \"name\": \"agg_payment\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"Payment\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Cash\",\n          \"Credit card\",\n          \"Ewallet\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Revenue\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5778.491863672848,\n        \"min\": 95968.64,\n        \"max\": 106863.4,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          106863.4,\n          95968.64,\n          104755.34\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Invoice ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19,\n        \"min\": 311,\n        \"max\": 345,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          344,\n          311,\n          345\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.rcParams[\"figure.figsize\"] = (10,5)\n",
        "sns.barplot( x='Payment', y='Revenue', data = agg_payment.sort_values('Revenue', ascending=False))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "id": "0BrSnK-5lDyA",
        "outputId": "cffb7f1a-470c-47e1-8618-7ebbf173d030"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Payment', ylabel='Revenue'>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pandas_ai = SmartDataframe(df_replaced, config={\"llm\": llm})\n",
        "chart_ai = pandas_ai.chat('create bar chart for each payment revenue with dark background')\n",
        "chart_ai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 583
        },
        "id": "4i37hVS5jB-A",
        "outputId": "5906fc97-b680-4960-9be2-5fd37005f143"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/exports/charts/temp_chart.png'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 86
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "highest revenue datang dari Cash"
      ],
      "metadata": {
        "id": "B35k_-RDlwtn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.barplot(x='Payment', y='Invoice ID', data = agg_payment.sort_values('Invoice ID', ascending=False))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "id": "MD03XrMnlfrP",
        "outputId": "9abc56e9-f4b2-4b42-fc8c-66e81685b0a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Payment', ylabel='Invoice ID'>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "dari count transaction, ewallet paling banyak"
      ],
      "metadata": {
        "id": "R6z-54WHmAk6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.pie(agg_payment['Revenue'], labels = agg_payment['Payment'],autopct='%.1f%%')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 578
        },
        "id": "0KW-gCG8l9L4",
        "outputId": "166cfcf7-0110-46a9-eb48-774684f14cbc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "([<matplotlib.patches.Wedge at 0x7a574609b8e0>,\n",
              "  <matplotlib.patches.Wedge at 0x7a574609b7c0>,\n",
              "  <matplotlib.patches.Wedge at 0x7a57460d0580>],\n",
              " [Text(0.5073032188378986, 0.976034550698236, 'Cash'),\n",
              "  Text(-1.0997450371451651, -0.023682340986048763, 'Credit card'),\n",
              "  Text(0.5281991633287692, -0.9648863372743903, 'Ewallet')],\n",
              " [Text(0.27671084663885376, 0.5323824821990377, '34.7%'),\n",
              "  Text(-0.5998609293519083, -0.012917640537844778, '31.2%'),\n",
              "  Text(0.288108634542965, -0.5263016385133037, '34.1%')])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pandas_ai = SmartDataframe(df_replaced, config={\"llm\": llm})\n",
        "chart_ai = pandas_ai.chat('create pie chart of renevue each payment type with dark background')\n",
        "chart_ai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 694
        },
        "id": "6tFfefBYmtlH",
        "outputId": "591b8288-3525-4b82-e670-838659909bc0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/exports/charts/temp_chart.png'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 94
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x800 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "cash volume 34.7% dan itu diatas 3.5% dari credit card"
      ],
      "metadata": {
        "id": "x95zISsHmVsY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# By Gender and By Product Type"
      ],
      "metadata": {
        "id": "oOvXgZYHmhQA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agg_gend = df_replaced.groupby(['Gender', 'Product line'], as_index=False)['Invoice ID'].nunique()\n",
        "agg_gend.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "uff3guxxmjz3",
        "outputId": "16141bea-b742-4b66-849c-749c4ef84791"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Gender            Product line  Invoice ID\n",
              "0  Female  Electronic accessories          84\n",
              "1  Female     Fashion accessories          96\n",
              "2  Female      Food and beverages          90\n",
              "3  Female       Health and beauty          64\n",
              "4  Female      Home and lifestyle          79"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-29073005-00d6-4c8f-a5fe-ee8b9caad210\" 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>Gender</th>\n",
              "      <th>Product line</th>\n",
              "      <th>Invoice ID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Female</td>\n",
              "      <td>Electronic accessories</td>\n",
              "      <td>84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Female</td>\n",
              "      <td>Fashion accessories</td>\n",
              "      <td>96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Female</td>\n",
              "      <td>Food and beverages</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Female</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Female</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>79</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-29073005-00d6-4c8f-a5fe-ee8b9caad210')\"\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-29073005-00d6-4c8f-a5fe-ee8b9caad210 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-29073005-00d6-4c8f-a5fe-ee8b9caad210');\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-edeb6f0b-2abe-47ba-91a3-cfa0331896d0\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-edeb6f0b-2abe-47ba-91a3-cfa0331896d0')\"\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-edeb6f0b-2abe-47ba-91a3-cfa0331896d0 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": "agg_gend",
              "summary": "{\n  \"name\": \"agg_gend\",\n  \"rows\": 12,\n  \"fields\": [\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Male\",\n          \"Female\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Product line\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Electronic accessories\",\n          \"Fashion accessories\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Invoice ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7,\n        \"min\": 64,\n        \"max\": 96,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          81,\n          96\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.rcParams[\"figure.figsize\"] = (15,5)\n",
        "sns.barplot(x='Product line', y='Invoice ID', data = agg_gend, hue = 'Gender')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 484
        },
        "id": "v7Stit5cm22Z",
        "outputId": "f653f19f-8666-4465-c24f-2c312fcf169e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Product line', ylabel='Invoice ID'>"
            ]
          },
          "metadata": {},
          "execution_count": 83
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pandas_ai = SmartDataframe(df_replaced, config={\"llm\": llm})\n",
        "chart_ai = pandas_ai.chat('create bar chart of product line, with value of count invoice id, split by gender, with dark background')\n",
        "chart_ai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 557
        },
        "id": "5lak1QDXm1jx",
        "outputId": "3e6f9f38-98e7-4d2a-dae6-6e80d7241cfc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/exports/charts/temp_chart.png'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 93
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "vkSCW15RoW3l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## generating insight from AI"
      ],
      "metadata": {
        "id": "TYiBmKrIoXZd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pandas_ai = SmartDataframe(df_replaced, config={\"llm\": llm})\n",
        "answer = pandas_ai.chat('which product line need to be improved? and why?')\n",
        "answer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "XZ8dXKN0oRH5",
        "outputId": "ad99c568-c09a-4c9e-80de-642cc6eb0853"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'The product line that needs improvement is Health and beauty due to low revenue.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Fashion Accessories di dominasi oleh female dst"
      ],
      "metadata": {
        "id": "km7XLF20naS8"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "D3KeMaxTnKV6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "outputId": "ca17a243-eaee-4b76-9290-bb71fcc257f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'The product line that needs improvement is Health and beauty due to low revenue.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "q56-qAzsn1Dn"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}