10_TS Segmentation Approaches.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.8"
    },
    "colab": {
      "name": "10_TS Segmentation Approaches.ipynb",
      "provenance": []
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QYjNN0XG1xkR"
      },
      "source": [
        "HSE, Applied Time Series Forecasitng , Winter 2023-24\n",
        "\n",
        "<font color=\"green\"> Lesson #10: TS Segmentation approaches</font>\n",
        "\n",
        "<span style=\"color:black; font-size: 12pt\"></span>\n",
        "\n",
        "Alexey Romanenko,\n",
        "<font color=\"blue\">alexromsput@gmail.com</font>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0bEXtbW_19Tx"
      },
      "source": [
        "**Key words:**\n",
        "    - Time Series Segmentation, TS Clustering, Intermittency Test, Seasonality Test, ABC-classification\n",
        "\n",
        "**Your feedback:**  please provide you feedback  <a href=\"https://forms.gle/bEV5iwmTqdM9rUoy8\"> here </a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U86m2u2Q1suC"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import datetime\n",
        "\n",
        "# don't forget to upload utils file to the colab session\n",
        "import warnings\n",
        "\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "# setting of the plotting style, registers pandas date converters for matplotlib and the default figure size\n",
        "import seaborn as sns\n",
        "sns.set_style(\"darkgrid\")\n",
        "pd.plotting.register_matplotlib_converters()\n",
        "# Default figure size\n",
        "sns.mpl.rc(\"figure\", figsize=(25, 5))\n",
        "sns.mpl.rc(\"font\", size=14)"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Time Series Segmentation: Overview\n",
        "\n",
        "**Question**\n",
        " * What is the purpose of TS segmenation? What TS can we call as \"similar\"?\n",
        "   - Two time series are similar if they have about the same level (mean) value\n",
        "   - Two time series are similar if they have the same hidden component (trend, seasonality, intermittency)\n",
        "\n"
      ],
      "metadata": {
        "id": "h9xzDnXX5AfC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Clustering based on Demand Behaviour to define ML Training pipeline\n",
        "**Question:** How to split all timeseries with about the same structure?\n",
        "\n",
        "*Idea: apply clustering algorithms to lagged features.\n",
        "\n"
      ],
      "metadata": {
        "id": "02BayO5cGdzc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Loading data\n",
        "ts_retail = pd.read_csv('https://raw.githubusercontent.com/aromanenko/ATSF/main/data/retail_2products.csv', sep=';')\n",
        "ts_retail['Date'] = pd.to_datetime(ts_retail['Date'], dayfirst = True)\n",
        "ts_retail.set_index(['Date'], inplace=True)\n",
        "ts_retail.head()"
      ],
      "metadata": {
        "id": "bOpI2tIK9-Ti",
        "outputId": "e5f048b3-7555-400c-fe34-13000fea5386",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        }
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Store_id  SKU_id  Promo  Demand  Regular_Price  Promo_Price\n",
              "Date                                                                   \n",
              "2015-01-01         1       1    NaN    22.0         163.78          NaN\n",
              "2015-01-02         1       1    NaN    41.0         163.78          NaN\n",
              "2015-01-03         1       1    NaN    35.0         163.78          NaN\n",
              "2015-01-04         1       1    NaN    72.0         163.78          NaN\n",
              "2015-01-05         1       1    NaN    25.0         163.78          NaN"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0a3ef971-eb07-437a-b6bf-c86bce118cfa\" 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>Store_id</th>\n",
              "      <th>SKU_id</th>\n",
              "      <th>Promo</th>\n",
              "      <th>Demand</th>\n",
              "      <th>Regular_Price</th>\n",
              "      <th>Promo_Price</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-01</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>41.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-03</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>35.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-04</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>72.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0a3ef971-eb07-437a-b6bf-c86bce118cfa')\"\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-0a3ef971-eb07-437a-b6bf-c86bce118cfa 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-0a3ef971-eb07-437a-b6bf-c86bce118cfa');\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-fb08b292-bd20-4faa-8958-bec4203f2d2c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fb08b292-bd20-4faa-8958-bec4203f2d2c')\"\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-fb08b292-bd20-4faa-8958-bec4203f2d2c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts_retail[(ts_retail['SKU_id']==1) & (ts_retail['Store_id']==1)][['Demand']].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 348
        },
        "id": "yb6qodntgSXp",
        "outputId": "ed197c6d-faca-4c52-e9a9-b95793bd07db"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Date'>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2500x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(ts_retail['Store_id'].unique())"
      ],
      "metadata": {
        "id": "3TrwDPtI-25o",
        "outputId": "6845acdb-3e7d-43f6-b08a-4f78d9be31c9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "110"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_sum = ts_retail.groupby('SKU_id').sum()[['Demand']]\n",
        "top_sum['percent'] = top_sum['Demand']/top_sum['Demand'].sum()\n",
        "top_SKU = list((top_sum['percent'] >= 0.01).index)\n",
        "demand_top_sku = ts_retail.index\n",
        "# # [ SKU in top_SKU for SKU in ts_retail['SKU_id'] ]\n",
        "demand_top_sku_pivot = pd.pivot_table(ts_retail.groupby(['SKU_id', 'Store_id']).mean()['Demand'].reset_index(),\n",
        "                                      index='Store_id', values='Demand', columns='SKU_id', fill_value=0).rename_axis(None, axis=1)\n",
        "demand_top_sku_pivot\n"
      ],
      "metadata": {
        "id": "7E2PwMYWzxXL",
        "outputId": "671c1a3b-f82e-41a3-dacd-b1636fd802bb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        }
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   1          2\n",
              "Store_id                       \n",
              "1         260.531496  14.726378\n",
              "2         625.015748  19.470472\n",
              "3         378.708661   9.431102\n",
              "4         422.751969  10.895669\n",
              "5         570.673228  18.431102\n",
              "...              ...        ...\n",
              "99        378.585106   7.500000\n",
              "100       173.166667  22.333333\n",
              "104       188.791667   4.291667\n",
              "105       156.580645  18.129032\n",
              "106       167.745455  15.545455\n",
              "\n",
              "[103 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-edb36a2b-db72-4583-a012-66ee9ce46f01\" 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>1</th>\n",
              "      <th>2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Store_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>260.531496</td>\n",
              "      <td>14.726378</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>625.015748</td>\n",
              "      <td>19.470472</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>378.708661</td>\n",
              "      <td>9.431102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>422.751969</td>\n",
              "      <td>10.895669</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>570.673228</td>\n",
              "      <td>18.431102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>378.585106</td>\n",
              "      <td>7.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>173.166667</td>\n",
              "      <td>22.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>188.791667</td>\n",
              "      <td>4.291667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>156.580645</td>\n",
              "      <td>18.129032</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>167.745455</td>\n",
              "      <td>15.545455</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>103 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-edb36a2b-db72-4583-a012-66ee9ce46f01')\"\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-edb36a2b-db72-4583-a012-66ee9ce46f01 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-edb36a2b-db72-4583-a012-66ee9ce46f01');\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-b821b6de-e3cf-49c0-a9f8-018ad31febec\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b821b6de-e3cf-49c0-a9f8-018ad31febec')\"\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-b821b6de-e3cf-49c0-a9f8-018ad31febec button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.cluster.hierarchy import dendrogram\n",
        "from sklearn.cluster import AgglomerativeClustering\n",
        "\n",
        "def plot_dendrogram(model, **kwargs):\n",
        "    # Create linkage matrix and then plot the dendrogram\n",
        "\n",
        "    # create the counts of samples under each node\n",
        "    counts = np.zeros(model.children_.shape[0])\n",
        "    n_samples = len(model.labels_)\n",
        "    for i, merge in enumerate(model.children_):\n",
        "        current_count = 0\n",
        "        for child_idx in merge:\n",
        "            if child_idx < n_samples:\n",
        "                current_count += 1  # leaf node\n",
        "            else:\n",
        "                current_count += counts[child_idx - n_samples]\n",
        "        counts[i] = current_count\n",
        "\n",
        "    linkage_matrix = np.column_stack(\n",
        "        [model.children_, model.distances_, counts]\n",
        "    ).astype(float)\n",
        "\n",
        "    # Plot the corresponding dendrogram\n",
        "    dendrogram(linkage_matrix, **kwargs)"
      ],
      "metadata": {
        "id": "jtqoS_eVBA8M"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# for SKU in ts_retail['SKU_id'].unique():\n",
        "# select TOP SKU (in case there are a lot of SKU)\n",
        "top_sum = ts_retail.groupby('SKU_id').sum()[['Demand']]\n",
        "top_sum['percent'] = top_sum['Demand']/top_sum['Demand'].sum()\n",
        "top_SKU = list((top_sum['percent'] >= 0.01).index)\n",
        "demand_top_sku = ts_retail[[ SKU in top_SKU for SKU in ts_retail['SKU_id'] ]]\n",
        "\n",
        "demand_top_sku_pivot = pd.pivot_table(demand_top_sku.groupby(['SKU_id', 'Store_id']).mean()['Demand'].reset_index(),\n",
        "                                      index='Store_id', values='Demand', columns='SKU_id', fill_value=0).rename_axis(None, axis=1)\n",
        "\n",
        "\n",
        "# Select Clustering method: tbd, e.g. AgglomerativeClustering\n",
        "agcl =  AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
        "agcl = agcl.fit(demand_top_sku_pivot)\n",
        "# plot the top three levels of the dendrogram\n",
        "plot_dendrogram(agcl, truncate_mode=\"level\", p=3)"
      ],
      "metadata": {
        "id": "GHVywM6L8w7A",
        "outputId": "70c885d3-a508-49a9-bcff-fbb722813f54",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        }
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2500x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "N_CLUSTERS = 4 # number of custers can be defined using dendrogram\n",
        "agcl =  AgglomerativeClustering(n_clusters=N_CLUSTERS)\n",
        "cluster_labels = agcl.fit_predict(demand_top_sku_pivot)\n",
        "# cluster_labels = cluster_labels\n",
        "# clustered_store = pd.DataFrame(cluster_labels, index=demand_top_sku_pivot.index, columns=['cluster_label'])"
      ],
      "metadata": {
        "id": "BOfu3usWBPtZ"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# plot clusters\n",
        "colors = ['orange','blue', 'red', 'green']\n",
        "plt.scatter(demand_top_sku_pivot[1], demand_top_sku_pivot[2], c=[colors[x] for x in cluster_labels], alpha = 0.6, s=10)"
      ],
      "metadata": {
        "id": "SrFQ83MU7fCI",
        "outputId": "c61e494d-8bf8-4878-f852-078078646241",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        }
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7b68b41d3d30>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2500x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## One more research regarding ML pipeline segmentation\n",
        "https://github.com/aromanenko/ML-pipeline-segmentation/tree/Ian"
      ],
      "metadata": {
        "id": "Df4_pHixiZxF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Intermittent Demand Forecasting Models\n",
        "Times Series with intermittent-demand-pattern contains non-zero actual values in random time points (non-zero actual values occur occasionaly).\n",
        "\n",
        "\n",
        "<img src = \"https://github.com/aromanenko/ATSF/blob/main/pic/IntermittentExample.PNG?raw=true\">\n",
        "<img src = \"https://github.com/aromanenko/ATSF/blob/main/pic/IntermittentExample2.PNG?raw=true\">"
      ],
      "metadata": {
        "id": "wC8QbPx15JCh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Intermittent Demand Time Series model\n",
        "\n",
        "$$ y_t = x_t\\cdot z_t +\\varepsilon_t$$\n",
        "\n",
        "   - $x_t$ - random variable (1 or 0) to have non-zero actual value       \n",
        "   - $z_t$ - actual volume\n",
        "\n",
        "\n",
        "**Note:**\n",
        " - sometimes intermittent time series are classified to more classes https://frepple.com/blog/demand-classification/\n",
        " - don't confuse intermittent and highly-causal driven time series:\n",
        "     -- we don't know time"
      ],
      "metadata": {
        "id": "XglPEG6X5NIt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Croston Model\n",
        "<img src = \"https://github.com/aromanenko/ATSF/blob/main/pic/CrostonIdea.PNG?raw=true\">\n",
        "\n",
        "**Croston Algorithm for Time Series Forecasting**\n",
        "\n",
        "$$ \\hat{y}_{t+1}=\\hat z_t/\\hat{n}_t$$\n",
        "where\n",
        "$$ \\hat z_t = \\begin{cases}z_{t-1}, & y_t==0 \\\\ \\alpha\\cdot{y_t}+(1-\\alpha) z_{t-1}, & y_t <>0 \\end{cases}$$\n",
        "\n",
        "$$ \\hat{n}_t = \\begin{cases}\\hat{n}_t, & y_t==0 \\\\ \\beta\\cdot{\\color{red}{n_t}}+(1-\\beta) \\hat{n}_{t-1}, & y_t <>0 \\end{cases}$$\n",
        "\n",
        "$\\alpha$ - smoothing parameter for time level value\n",
        "$\\beta$ - smoothing parameter for 0-intervals length forecasting\n",
        "\n",
        "<img src = \"https://github.com/aromanenko/ATSF/blob/main/pic/CrostonIdea2.PNG?raw=true\">\n",
        "\n",
        "\n",
        "**Example of Realization**\n",
        "- https://towardsdatascience.com/croston-forecast-model-for-intermittent-demand-360287a17f5f"
      ],
      "metadata": {
        "id": "ZGf9OgHF5Val"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install croston\n",
        "from croston import croston\n",
        "import random\n",
        "\n",
        "a = np.zeros(50)\n",
        "val = np.array(random.sample(range(100,200), 10))\n",
        "idxs = random.sample(range(50), 10)\n",
        "\n",
        "ts = np.insert(a, idxs, val)\n",
        "\n",
        "fit_pred = croston.fit_croston(ts, 10,'original')\n",
        "\n",
        "yhat = np.concatenate([fit_pred['croston_fittedvalues'], fit_pred['croston_forecast']])\n",
        "\n",
        "plt.plot(ts)\n",
        "plt.plot(yhat)"
      ],
      "metadata": {
        "id": "_MnmNbrU6Et7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 505
        },
        "outputId": "5096a75b-7e7f-4aca-eb5a-f8d15b0c8c4f"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting croston\n",
            "  Downloading croston-0.1.2.4-py3-none-any.whl (3.8 kB)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from croston) (1.23.5)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from croston) (1.5.3)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from croston) (1.11.4)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->croston) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->croston) (2023.4)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->croston) (1.16.0)\n",
            "Installing collected packages: croston\n",
            "Successfully installed croston-0.1.2.4\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7b68ac410eb0>]"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2500x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# TS Segmentation to define TS-Forecasting Pipeline\n",
        "\n",
        "\n",
        "**Question**\n",
        " * What is the main reason of overfitting problem?\n",
        "   <!-- Too big complexity of the algorithm. -->\n",
        " * Can you describe complexity of ESM/ARIMA/Intermittent Models?\n",
        "    <!-- The more hidden components including drivers we need to estimate by the algorithm the more complicated the algorithm is. -->\n",
        " * Is it possible to decrease complexity of train ts-algorithm assuming that we use all known models in the training process ESM/ARIMA/Intermittent models?\n",
        "  <!-- Idea: let's exclude excessive models from training set of models -->\n"
      ],
      "metadata": {
        "id": "XCS_BMcY9Q5U"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## One more way how to select ts-models family before training process\n",
        "\n",
        "<img src = 'https://github.com/aromanenko/ATSF/blob/main/pic/ts_pipeline_segmentation.png?raw=true' width = 800pt>\n",
        "\n",
        "**Правило сопоставления сегмента TS и семейства моделей, учесвующих в обучении**\n",
        "\n",
        "|   Сегмент     |   Семейство алгоритмов   |\n",
        "|-------------------------|----------------|\n",
        "|RETIRED                               |zero-model (прогноз =0)|\n",
        "|LOW_VOLUME                           |Simple ES|\n",
        "|INSEASON_NON_INTERMITTENT|           Seasonal ES and ARIMA|\n",
        "|INSEASON_INTERMITTENT    |         Croston model|\n",
        "|YEAR_ROUND_SEASONAL                   |Seasonal ES and ARIMA|\n",
        "|YEAR_ROUND_SEASONAL_INTERMITTENT      |Croston Model|\n",
        "|YEAR_ROUND_NOT_SEASONAL               |not-seasonal ES annd ARIMA|\n",
        "|YEAR_ROUND_INTERMITTENT                |Croston Model|\n",
        "|Short                |ML (out of the scope)|\n",
        "\n",
        "Detailes see here: https://github.com/aromanenko/ts-segmentation"
      ],
      "metadata": {
        "id": "0m4f1uAq36FJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Building Time Series Forecastability Index\n",
        "Those Time Series that have about the same accuracy level should have the same $\\color{red}{Forecastability~Index}$.\n",
        "\n",
        "\n",
        "\n",
        "<img src = 'https://github.com/aromanenko/ATSF/blob/main/pic/Forecastability%20Index.png?raw=true' width = 500pt>\n",
        "\n",
        "Techniques to do it\n",
        "* STL decomposition (detecting trend and seasonality) https://www.statsmodels.org/devel/examples/notebooks/generated/stl_decomposition.html\n",
        "\n",
        "* ABC splitting (to segment by Demand Velocity and Demand Variability) https://pypi.org/project/abc-analysis/\n",
        "\n",
        "or <a href = 'https://excel.city/2015/01/methods-of-classification-in-abc-analysis/'>more advanced tecniques </a>\n",
        "\n",
        "* Intermittency time series tests\n"
      ],
      "metadata": {
        "id": "JjFmmS_TGtKT"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "QaBSqiiv6C0l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install abc_analysis"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xTFUdkB8SLcW",
        "outputId": "232bfb77-1841-4896-afda-2b17c1524cd2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting abc_analysis\n",
            "  Downloading abc_analysis-0.1.22-py3-none-any.whl (17 kB)\n",
            "Requirement already satisfied: pandas>=0.22 in /usr/local/lib/python3.10/dist-packages (from abc_analysis) (1.5.3)\n",
            "Requirement already satisfied: numpy>=1.14 in /usr/local/lib/python3.10/dist-packages (from abc_analysis) (1.23.5)\n",
            "Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from abc_analysis) (1.11.4)\n",
            "Requirement already satisfied: matplotlib>=2.2.2 in /usr/local/lib/python3.10/dist-packages (from abc_analysis) (3.7.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (1.2.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (4.47.2)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (23.2)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (3.1.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.2.2->abc_analysis) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.22->abc_analysis) (2023.3.post1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=2.2.2->abc_analysis) (1.16.0)\n",
            "Installing collected packages: abc_analysis\n",
            "Successfully installed abc_analysis-0.1.22\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import abc_analysis\n",
        "from abc_analysis import abc_analysis, abc_plot\n",
        "\n",
        "# Perform an ABC analysis with plotting\n",
        "dctAnalysis = abc_analysis([1, 15, 25, 17, 2, 3, 5, 6, 2, 3, 22], True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "Axph9eFEMZjb",
        "outputId": "473de78e-2527-443b-8be9-9bd9a5a911c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts_retail = pd.read_csv('https://raw.githubusercontent.com/aromanenko/ATSF/main/data/retail_2products.csv', sep=';')\n",
        "ts_retail['Date'] = pd.to_datetime(ts_retail['Date'], dayfirst = True)\n",
        "ts_retail.set_index(['Date'], inplace=True)\n",
        "\n",
        "ts_id_columns = ['Store_id', 'SKU_id']\n",
        "ts_retail.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "vCRETVRc0IUE",
        "outputId": "82616ef6-ae0b-4e67-852f-03ba55156bfd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Store_id  SKU_id  Promo  Demand  Regular_Price  Promo_Price\n",
              "Date                                                                   \n",
              "2015-01-01         1       1    NaN    22.0         163.78          NaN\n",
              "2015-01-02         1       1    NaN    41.0         163.78          NaN\n",
              "2015-01-03         1       1    NaN    35.0         163.78          NaN\n",
              "2015-01-04         1       1    NaN    72.0         163.78          NaN\n",
              "2015-01-05         1       1    NaN    25.0         163.78          NaN"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4455f739-8a12-4805-b39e-21485c26cae4\" 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>Store_id</th>\n",
              "      <th>SKU_id</th>\n",
              "      <th>Promo</th>\n",
              "      <th>Demand</th>\n",
              "      <th>Regular_Price</th>\n",
              "      <th>Promo_Price</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-01</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>41.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-03</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>35.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-04</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>72.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.0</td>\n",
              "      <td>163.78</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4455f739-8a12-4805-b39e-21485c26cae4')\"\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-4455f739-8a12-4805-b39e-21485c26cae4 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-4455f739-8a12-4805-b39e-21485c26cae4');\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-6d4742c5-f153-4501-8355-07001abb523a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6d4742c5-f153-4501-8355-07001abb523a')\"\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-6d4742c5-f153-4501-8355-07001abb523a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# split TS by Demand Volume\n",
        "ts_mean_values = ts_retail.groupby(ts_id_columns)['Demand'].mean()\n",
        "\n",
        "# Plot saved results of an ABC analysis\n",
        "ts_demand_abc  = abc_analysis(ts_mean_values.fillna(0), True)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "3vQmCveo0OsJ",
        "outputId": "cab0958a-6626-4952-b4d1-d388e4a49141"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# split TS by Coefficient of Volatility (CV)\n",
        "ts_cv_values = ts_retail.groupby(ts_id_columns)['Demand'].std().fillna(0).div(ts_retail.groupby(ts_id_columns)['Demand'].mean().fillna(1))\n",
        "\n",
        "# Plot saved results of an ABC analysis\n",
        "ts_demand_abc  = abc_analysis(ts_cv_values.fillna(0), True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "32g5k5YVW-I1",
        "outputId": "10e83446-0666-40f6-ee01-b32263ef8f1b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dynamic Time Series Warping algorithms\n",
        "https://paul-mora.com/classification/time-series/clustering/python/Dynamic-Time-Warping-Explanation-and-Testing-on-Audio-and-Tabular-Data/"
      ],
      "metadata": {
        "id": "Kclrdpnay2Fx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Conclusion"
      ],
      "metadata": {
        "id": "5V--p1pWxPKB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "* TS segmentation can be done by many different approaches\n",
        "  - Building of ML models dimensions can be perfomed with Clustering algorithms\n",
        "  - TS segmentation can be beneficial for TS algorithms training pipeline\n",
        "  - Building of Forecastability groups can be done with some conservative segmentation techniques\n",
        "  - DTW algorithms can be used to split time series based on profiles\n"
      ],
      "metadata": {
        "id": "Y4lqNYNY8WBS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Self-check questions\n",
        "1. Why ML pipeline segmentation has advantage vs one-ml-model pipeline?\n",
        "2. What is intermittent-demand-patterned time series?\n",
        "3. Describe how croston model works"
      ],
      "metadata": {
        "id": "yr7ISINaKsK_"
      }
    }
  ]
}