1_5_1.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyM2ViR15Iaf65XTstdJvR9c",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Sinrez/PythonProjects/blob/main/1_5_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Загрузка временного ряда из файла\n",
        "data = pd.read_csv('/content/task5_224427.csv')\n",
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "77-ZlZPSjCug",
        "outputId": "635f914e-95c2-4b9d-fb2d-57a53f435110"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    y\n",
              "0   2\n",
              "1  21\n",
              "2  34\n",
              "3  37\n",
              "4  37"
            ],
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              "      <td>34</td>\n",
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              "      <td>37</td>\n",
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              "      <td>37</td>\n",
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              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "\n",
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              "\n",
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              "    domScope.querySelector('#df-f449bc7a-e82d-4a02-a114-43451777a782 button.colab-df-quickchart');\n",
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              "      display: none;\n",
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              "      height: 32px;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
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              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-e7bd2472-0a7f-47fe-bd13-1a4cabd243a6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-e7bd2472-0a7f-47fe-bd13-1a4cabd243a6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 508
        },
        "id": "QQ6vcKiBi51v",
        "outputId": "fc5e4e32-acf8-48ca-d1c1-3f3a7712fc98"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Сглаженное значение для 51-ой точки ряда: 137.67157702019625\n",
            "Сглаженное окр значение для 51-ой точки ряда: 137.67\n"
          ]
        }
      ],
      "source": [
        "# Применение экспоненциального сглаживания\n",
        "smoothing_factor = 0.23\n",
        "smoothed_data = data.ewm(alpha=smoothing_factor).mean()\n",
        "\n",
        "# Получение значения для 51-ой точки\n",
        "point_51 = smoothed_data.iloc[50]['y']\n",
        "\n",
        "# Визуализация исходного ряда и сглаженного ряда\n",
        "plt.plot(data.index, data['y'], label='Original')\n",
        "plt.plot(smoothed_data.index, smoothed_data['y'], label='Smoothed')\n",
        "plt.legend()\n",
        "plt.xlabel('Time')\n",
        "plt.ylabel('Value')\n",
        "plt.title('Exponential Smoothing')\n",
        "plt.show()\n",
        "\n",
        "print(f\"Сглаженное значение для 51-ой точки ряда: {point_51}\")\n",
        "print(f\"Сглаженное окр значение для 51-ой точки ряда: {round(point_51,2)}\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "last_point = smoothed_data.iloc[-1]\n",
        "print(f\"Сглаженное значение для последней точки ряда: {last_point}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rIgLQEeLjEb2",
        "outputId": "0e97e0d5-82ec-41d6-cf1d-af50b020eadc"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Сглаженное значение для последней точки ряда: y    262.762618\n",
            "Name: 99, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Получение значений x и y для линейного тренда\n",
        "x = np.arange(len(data))\n",
        "y = data['y']\n",
        "\n",
        "# Подгонка линейного тренда\n",
        "coefficients = np.polyfit(x, y, 1)\n",
        "a = coefficients[0]\n",
        "b = coefficients[1]\n",
        "\n",
        "# Построение линейного тренда\n",
        "trend = a * x + b\n",
        "\n",
        "# Визуализация исходного ряда и линейного тренда\n",
        "plt.plot(x, y, label='Original')\n",
        "plt.plot(x, trend, label='Trend')\n",
        "plt.legend()\n",
        "plt.xlabel('Time')\n",
        "plt.ylabel('Value')\n",
        "plt.title('Linear Trend')\n",
        "plt.show()\n",
        "\n",
        "print(f\"Коэффициенты линейного тренда: a = {a:.2f}, b = {b:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "OqL3Gyjyk98s",
        "outputId": "68ae47ea-92ae-46cc-8da4-e441852e3bbf"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Коэффициенты линейного тренда: a = 2.53, b = 19.04\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Коэффициент детерминации (R-квадрат)\n",
        "y_mean = np.mean(y)\n",
        "ss_total = np.sum((y - y_mean) ** 2)\n",
        "ss_residual = np.sum((y - trend) ** 2)\n",
        "r_squared = 1 - (ss_residual / ss_total)\n",
        "print(f\"Коэффициент детерминации (R-квадрат): {r_squared:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nLroN3x_lqUn",
        "outputId": "944c2344-47cb-4e3b-ed61-1410b8674de9"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Коэффициент детерминации (R-квадрат): 0.99\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Прогнозирование 101-ого значения ряда\n",
        "next_x = 100  # 101-ое значение имеет индекс 100\n",
        "forecast = a * next_x + b\n",
        "\n",
        "print(f\"Прогноз 101-ого значения ряда: {forecast:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qx6N-GPml_7u",
        "outputId": "69b62a64-44ca-4ee6-dcf1-85d31eb5a988"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Прогноз 101-ого значения ряда: 271.99\n"
          ]
        }
      ]
    }
  ]
}