{
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    "kernelspec": {
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "pip install prophet"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4vMywkKtc1AK",
        "outputId": "1365ebfd-1215-4cbc-831c-6ae394d8cd1d"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: prophet in /usr/local/lib/python3.10/dist-packages (1.1.5)\n",
            "Requirement already satisfied: cmdstanpy>=1.0.4 in /usr/local/lib/python3.10/dist-packages (from prophet) (1.2.0)\n",
            "Requirement already satisfied: numpy>=1.15.4 in /usr/local/lib/python3.10/dist-packages (from prophet) (1.23.5)\n",
            "Requirement already satisfied: matplotlib>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from prophet) (3.7.1)\n",
            "Requirement already satisfied: pandas>=1.0.4 in /usr/local/lib/python3.10/dist-packages (from prophet) (1.5.3)\n",
            "Requirement already satisfied: holidays>=0.25 in /usr/local/lib/python3.10/dist-packages (from prophet) (0.41)\n",
            "Requirement already satisfied: tqdm>=4.36.1 in /usr/local/lib/python3.10/dist-packages (from prophet) (4.66.1)\n",
            "Requirement already satisfied: importlib-resources in /usr/local/lib/python3.10/dist-packages (from prophet) (6.1.1)\n",
            "Requirement already satisfied: stanio~=0.3.0 in /usr/local/lib/python3.10/dist-packages (from cmdstanpy>=1.0.4->prophet) (0.3.0)\n",
            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from holidays>=0.25->prophet) (2.8.2)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (1.2.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (4.47.2)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (23.2)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.0.0->prophet) (3.1.1)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.0.4->prophet) (2023.3.post1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil->holidays>=0.25->prophet) (1.16.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from prophet import Prophet"
      ],
      "metadata": {
        "id": "dyl5C37PnU33"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "df_data = pd.read_csv(\"https://raw.githubusercontent.com/jonasdieckmann/prophet_tutorial/main/passengers.csv\")\n",
        "\n",
        "df_data_train = df_data[df_data[\"Month\"] < \"2023-01\"]\n",
        "df_data_test = df_data[df_data[\"Month\"] >= \"2023-01\"]\n",
        "\n",
        "display(df_data_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "J9xB-Ob4KzUg",
        "outputId": "8fc52ed4-aa0f-44e3-d94b-116b60f5680c"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "       Month  Passengers\n",
              "0    2012-01         112\n",
              "1    2012-02         118\n",
              "2    2012-03         132\n",
              "3    2012-04         129\n",
              "4    2012-05         121\n",
              "..       ...         ...\n",
              "127  2022-08         559\n",
              "128  2022-09         463\n",
              "129  2022-10         407\n",
              "130  2022-11         362\n",
              "131  2022-12         405\n",
              "\n",
              "[132 rows x 2 columns]"
            ],
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              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
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              "  </div>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "\n",
        "decompose = seasonal_decompose(df_data_train.Passengers, model='additive', extrapolate_trend='freq', period=12)\n",
        "\n",
        "decompose.plot().show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "9jVMbwYFpkWw",
        "outputId": "67dbca82-7c0b-4a1b-e0c2-3aadb0ec6446"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# date variable needs to be named \"ds\" for prophet\n",
        "df_train_prophet = df_data_train\n",
        "\n",
        "df_train_prophet = df_train_prophet.rename(columns={\"Month\": \"ds\"})\n",
        "\n",
        "# target variable needs to be named \"y\" for prophet\n",
        "df_train_prophet = df_train_prophet.rename(columns={\"Passengers\": \"y\"})\n"
      ],
      "metadata": {
        "id": "81W6yVeyiIvU"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_prophet  = Prophet()\n",
        "model_prophet.fit(df_train_prophet)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r2pw-QwNie1J",
        "outputId": "1b05ca86-8c75-4885-bc0d-449d6b7b3d6b"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:prophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
            "INFO:prophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n",
            "DEBUG:cmdstanpy:input tempfile: /tmp/tmplf5plpol/ed6h68e6.json\n",
            "DEBUG:cmdstanpy:input tempfile: /tmp/tmplf5plpol/top9x2jy.json\n",
            "DEBUG:cmdstanpy:idx 0\n",
            "DEBUG:cmdstanpy:running CmdStan, num_threads: None\n",
            "DEBUG:cmdstanpy:CmdStan args: ['/usr/local/lib/python3.10/dist-packages/prophet/stan_model/prophet_model.bin', 'random', 'seed=25148', 'data', 'file=/tmp/tmplf5plpol/ed6h68e6.json', 'init=/tmp/tmplf5plpol/top9x2jy.json', 'output', 'file=/tmp/tmplf5plpol/prophet_modelh1ewjej2/prophet_model-20240127121808.csv', 'method=optimize', 'algorithm=lbfgs', 'iter=10000']\n",
            "12:18:08 - cmdstanpy - INFO - Chain [1] start processing\n",
            "INFO:cmdstanpy:Chain [1] start processing\n",
            "12:18:08 - cmdstanpy - INFO - Chain [1] done processing\n",
            "INFO:cmdstanpy:Chain [1] done processing\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<prophet.forecaster.Prophet at 0x7e01fb9882b0>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_future = model_prophet.make_future_dataframe(periods=12, freq='MS')\n",
        "display(df_future)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "2nhOL0qaixxb",
        "outputId": "fc419cca-5911-4077-e2b4-4269f1a66584"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "            ds\n",
              "0   2012-01-01\n",
              "1   2012-02-01\n",
              "2   2012-03-01\n",
              "3   2012-04-01\n",
              "4   2012-05-01\n",
              "..         ...\n",
              "139 2023-08-01\n",
              "140 2023-09-01\n",
              "141 2023-10-01\n",
              "142 2023-11-01\n",
              "143 2023-12-01\n",
              "\n",
              "[144 rows x 1 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1cb1d913-2ada-449d-b1bd-57da0e1be78f\" 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>ds</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2012-01-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2012-02-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2012-03-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2012-04-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012-05-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>2023-08-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>2023-09-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>2023-10-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>2023-11-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>2023-12-01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>144 rows × 1 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-1cb1d913-2ada-449d-b1bd-57da0e1be78f')\"\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-1cb1d913-2ada-449d-b1bd-57da0e1be78f 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-1cb1d913-2ada-449d-b1bd-57da0e1be78f');\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-286b5895-1968-4c3b-b0e3-1c64ed6bb8c1\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-286b5895-1968-4c3b-b0e3-1c64ed6bb8c1')\"\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-286b5895-1968-4c3b-b0e3-1c64ed6bb8c1 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "forecast_prophet = model_prophet.predict(df_future)\n",
        "forecast_prophet[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].round().tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "SdYRBlXTkytT",
        "outputId": "1a43285f-5eda-4602-9216-2eb17a555a31"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ds   yhat  yhat_lower  yhat_upper\n",
              "139 2023-08-01  532.0       507.0       555.0\n",
              "140 2023-09-01  484.0       461.0       509.0\n",
              "141 2023-10-01  446.0       421.0       471.0\n",
              "142 2023-11-01  416.0       390.0       443.0\n",
              "143 2023-12-01  449.0       423.0       473.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ab0a02e2-5ed0-4251-8fb7-6db629d7b039\" 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>ds</th>\n",
              "      <th>yhat</th>\n",
              "      <th>yhat_lower</th>\n",
              "      <th>yhat_upper</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>2023-08-01</td>\n",
              "      <td>532.0</td>\n",
              "      <td>507.0</td>\n",
              "      <td>555.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>2023-09-01</td>\n",
              "      <td>484.0</td>\n",
              "      <td>461.0</td>\n",
              "      <td>509.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>2023-10-01</td>\n",
              "      <td>446.0</td>\n",
              "      <td>421.0</td>\n",
              "      <td>471.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>416.0</td>\n",
              "      <td>390.0</td>\n",
              "      <td>443.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>2023-12-01</td>\n",
              "      <td>449.0</td>\n",
              "      <td>423.0</td>\n",
              "      <td>473.0</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-ab0a02e2-5ed0-4251-8fb7-6db629d7b039')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ab0a02e2-5ed0-4251-8fb7-6db629d7b039 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-ab0a02e2-5ed0-4251-8fb7-6db629d7b039');\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-01fa5a2c-27f8-4fcd-af0e-a176ee783368\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-01fa5a2c-27f8-4fcd-af0e-a176ee783368')\"\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-01fa5a2c-27f8-4fcd-af0e-a176ee783368 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": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# plot the time series\n",
        "forecast_plot = model_prophet.plot(forecast_prophet)\n",
        "\n",
        "# add a vertical line at the end of the training period\n",
        "axes = forecast_plot.gca()\n",
        "last_training_date = forecast_prophet['ds'].iloc[-12]\n",
        "axes.axvline(x=last_training_date, color='red', linestyle='--', label='Training End')\n",
        "\n",
        "# plot true test data for the period after the red line\n",
        "df_data_test['Month'] = pd.to_datetime(df_data_test['Month'])\n",
        "plt.plot(df_data_test['Month'], df_data_test['Passengers'],'ro', markersize=3, label='True Test Data')\n",
        "\n",
        "# show the legend to distinguish between the lines\n",
        "plt.legend()\n",
        ""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 729
        },
        "id": "udeY1ywRk_Fo",
        "outputId": "39f94a33-3aa6-4fd1-d410-62dca0dada19"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-28-f2bae044d8e6>:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df_data_test['Month'] = pd.to_datetime(df_data_test['Month'])\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7e01f8d2e4a0>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}