{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "BTC_predict.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyP5thH85zBWognO/ZVRe6Ve",
      "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/youtube-jocoding/pyupbit-autotrade/blob/main/BTC_predict.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HV0SrOgcHMw_"
      },
      "source": [
        "!pip install pyupbit"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OPo1hQ62HcxA"
      },
      "source": [
        "import pyupbit"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "sjI3ac9tT7D2",
        "outputId": "142ff09e-6574-4dc7-f117-e1c2e565eba1"
      },
      "source": [
        "#BTC 최근 200시간의 데이터 불러옴\n",
        "df = pyupbit.get_ohlcv(\"KRW-BTC\", interval=\"minute60\")\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2021-05-08 20:00:00</th>\n",
              "      <td>70080000.0</td>\n",
              "      <td>70397000.0</td>\n",
              "      <td>70031000.0</td>\n",
              "      <td>70278000.0</td>\n",
              "      <td>282.481680</td>\n",
              "      <td>1.983373e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-08 21:00:00</th>\n",
              "      <td>70202000.0</td>\n",
              "      <td>70600000.0</td>\n",
              "      <td>69775000.0</td>\n",
              "      <td>70353000.0</td>\n",
              "      <td>512.864414</td>\n",
              "      <td>3.595321e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-08 22:00:00</th>\n",
              "      <td>70353000.0</td>\n",
              "      <td>71400000.0</td>\n",
              "      <td>70261000.0</td>\n",
              "      <td>70402000.0</td>\n",
              "      <td>1074.924200</td>\n",
              "      <td>7.618756e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-08 23:00:00</th>\n",
              "      <td>70467000.0</td>\n",
              "      <td>70586000.0</td>\n",
              "      <td>70101000.0</td>\n",
              "      <td>70264000.0</td>\n",
              "      <td>495.536391</td>\n",
              "      <td>3.485509e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-09 00:00:00</th>\n",
              "      <td>70245000.0</td>\n",
              "      <td>70732000.0</td>\n",
              "      <td>69377000.0</td>\n",
              "      <td>69561000.0</td>\n",
              "      <td>674.450592</td>\n",
              "      <td>4.724700e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-16 23:00:00</th>\n",
              "      <td>59941000.0</td>\n",
              "      <td>60155000.0</td>\n",
              "      <td>59293000.0</td>\n",
              "      <td>59355000.0</td>\n",
              "      <td>417.846935</td>\n",
              "      <td>2.493730e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-17 00:00:00</th>\n",
              "      <td>59370000.0</td>\n",
              "      <td>59440000.0</td>\n",
              "      <td>58800000.0</td>\n",
              "      <td>58810000.0</td>\n",
              "      <td>417.550735</td>\n",
              "      <td>2.465069e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-17 01:00:00</th>\n",
              "      <td>58811000.0</td>\n",
              "      <td>59000000.0</td>\n",
              "      <td>58327000.0</td>\n",
              "      <td>58480000.0</td>\n",
              "      <td>494.023674</td>\n",
              "      <td>2.897628e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-17 02:00:00</th>\n",
              "      <td>58513000.0</td>\n",
              "      <td>58638000.0</td>\n",
              "      <td>57900000.0</td>\n",
              "      <td>57996000.0</td>\n",
              "      <td>675.896966</td>\n",
              "      <td>3.928135e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-17 03:00:00</th>\n",
              "      <td>57997000.0</td>\n",
              "      <td>58278000.0</td>\n",
              "      <td>57501000.0</td>\n",
              "      <td>57550000.0</td>\n",
              "      <td>231.009586</td>\n",
              "      <td>1.336449e+10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           open        high  ...       volume         value\n",
              "2021-05-08 20:00:00  70080000.0  70397000.0  ...   282.481680  1.983373e+10\n",
              "2021-05-08 21:00:00  70202000.0  70600000.0  ...   512.864414  3.595321e+10\n",
              "2021-05-08 22:00:00  70353000.0  71400000.0  ...  1074.924200  7.618756e+10\n",
              "2021-05-08 23:00:00  70467000.0  70586000.0  ...   495.536391  3.485509e+10\n",
              "2021-05-09 00:00:00  70245000.0  70732000.0  ...   674.450592  4.724700e+10\n",
              "...                         ...         ...  ...          ...           ...\n",
              "2021-05-16 23:00:00  59941000.0  60155000.0  ...   417.846935  2.493730e+10\n",
              "2021-05-17 00:00:00  59370000.0  59440000.0  ...   417.550735  2.465069e+10\n",
              "2021-05-17 01:00:00  58811000.0  59000000.0  ...   494.023674  2.897628e+10\n",
              "2021-05-17 02:00:00  58513000.0  58638000.0  ...   675.896966  3.928135e+10\n",
              "2021-05-17 03:00:00  57997000.0  58278000.0  ...   231.009586  1.336449e+10\n",
              "\n",
              "[200 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "eDaG0GWkVO3N",
        "outputId": "af8c6c98-0b8c-41a9-cb85-0dbea994f230"
      },
      "source": [
        "#시간(ds)와 종가(y)값만 남김\n",
        "df = df.reset_index()\n",
        "df['ds'] = df['index']\n",
        "df['y'] = df['close']\n",
        "data = df[['ds','y']]\n",
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-05-08 20:00:00</td>\n",
              "      <td>70278000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-05-08 21:00:00</td>\n",
              "      <td>70353000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-05-08 22:00:00</td>\n",
              "      <td>70402000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-05-08 23:00:00</td>\n",
              "      <td>70264000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-05-09 00:00:00</td>\n",
              "      <td>69561000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>2021-05-16 23:00:00</td>\n",
              "      <td>59355000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>2021-05-17 00:00:00</td>\n",
              "      <td>58810000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>2021-05-17 01:00:00</td>\n",
              "      <td>58480000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>2021-05-17 02:00:00</td>\n",
              "      <td>57996000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>2021-05-17 03:00:00</td>\n",
              "      <td>57550000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                     ds           y\n",
              "0   2021-05-08 20:00:00  70278000.0\n",
              "1   2021-05-08 21:00:00  70353000.0\n",
              "2   2021-05-08 22:00:00  70402000.0\n",
              "3   2021-05-08 23:00:00  70264000.0\n",
              "4   2021-05-09 00:00:00  69561000.0\n",
              "..                  ...         ...\n",
              "195 2021-05-16 23:00:00  59355000.0\n",
              "196 2021-05-17 00:00:00  58810000.0\n",
              "197 2021-05-17 01:00:00  58480000.0\n",
              "198 2021-05-17 02:00:00  57996000.0\n",
              "199 2021-05-17 03:00:00  57550000.0\n",
              "\n",
              "[200 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NeNx5_hhXbR1"
      },
      "source": [
        "#prophet 불러옴\n",
        "from fbprophet import Prophet"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lLe7j7jnVep2",
        "outputId": "c7062e3f-e632-4743-e809-ab993a7ebe2b"
      },
      "source": [
        "#학습\n",
        "model = Prophet()\n",
        "model.fit(data)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n",
            "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<fbprophet.forecaster.Prophet at 0x7fc15ca2ee90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ylP8nXwEYBxK"
      },
      "source": [
        "#24시간 미래 예측\n",
        "future = model.make_future_dataframe(periods=24, freq='H')\n",
        "forecast = model.predict(future)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "_zzI5o0OXN5H",
        "outputId": "11e9714a-d07d-4c95-dddf-eb24d734b629"
      },
      "source": [
        "#그래프1\n",
        "fig1 = model.plot(forecast)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "DkVLmIsPXOl6",
        "outputId": "ac9f645a-105b-444c-89ac-11a554e6e082"
      },
      "source": [
        "#그래프2\n",
        "fig2 = model.plot_components(forecast)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 648x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GJgSNaOcr5_t",
        "outputId": "3cf9b79d-94d6-4da8-dac0-24edd0b0c57d"
      },
      "source": [
        "#매수 시점의 가격\n",
        "nowValue = pyupbit.get_current_price(\"KRW-BTC\")\n",
        "nowValue"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "57098000.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SPXCEMj4ma6h",
        "outputId": "1918f82e-5d28-4f0d-cf79-d8c457671d96"
      },
      "source": [
        "#종가의 가격을 구함\n",
        "\n",
        "#현재 시간이 자정 이전\n",
        "closeDf = forecast[forecast['ds'] == forecast.iloc[-1]['ds'].replace(hour=9)]\n",
        "\n",
        "#현재 시간이 자정 이후\n",
        "if len(closeDf) == 0:\n",
        "  closeDf = forecast[forecast['ds'] == data.iloc[-1]['ds'].replace(hour=9)]\n",
        "\n",
        "#어쨋든 당일 종가\n",
        "closeValue = closeDf['yhat'].values[0]\n",
        "closeValue"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "58097882.673339084"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bUOLBXFNm2cd",
        "outputId": "be8d1c13-ad5a-46ec-bdb7-006098b9057a"
      },
      "source": [
        "#구체적인 가격\n",
        "print(\"현재 시점 가격: \", nowValue)\n",
        "print(\"종가의 가격: \", closeValue)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "현재 시점 가격:  57098000.0\n",
            "종가의 가격:  58097882.673339084\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 758
        },
        "id": "BS_M58SRt94s",
        "outputId": "13b02e67-563d-4956-baf0-8cc58bbc64da"
      },
      "source": [
        "forecast"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>trend</th>\n",
              "      <th>yhat_lower</th>\n",
              "      <th>yhat_upper</th>\n",
              "      <th>trend_lower</th>\n",
              "      <th>trend_upper</th>\n",
              "      <th>additive_terms</th>\n",
              "      <th>additive_terms_lower</th>\n",
              "      <th>additive_terms_upper</th>\n",
              "      <th>daily</th>\n",
              "      <th>daily_lower</th>\n",
              "      <th>daily_upper</th>\n",
              "      <th>multiplicative_terms</th>\n",
              "      <th>multiplicative_terms_lower</th>\n",
              "      <th>multiplicative_terms_upper</th>\n",
              "      <th>yhat</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-05-08 20:00:00</td>\n",
              "      <td>7.049319e+07</td>\n",
              "      <td>6.978264e+07</td>\n",
              "      <td>7.145666e+07</td>\n",
              "      <td>7.049319e+07</td>\n",
              "      <td>7.049319e+07</td>\n",
              "      <td>73763.938017</td>\n",
              "      <td>73763.938017</td>\n",
              "      <td>73763.938017</td>\n",
              "      <td>73763.938017</td>\n",
              "      <td>73763.938017</td>\n",
              "      <td>73763.938017</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.056695e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-05-08 21:00:00</td>\n",
              "      <td>7.054058e+07</td>\n",
              "      <td>6.981790e+07</td>\n",
              "      <td>7.151720e+07</td>\n",
              "      <td>7.054058e+07</td>\n",
              "      <td>7.054058e+07</td>\n",
              "      <td>155154.366642</td>\n",
              "      <td>155154.366642</td>\n",
              "      <td>155154.366642</td>\n",
              "      <td>155154.366642</td>\n",
              "      <td>155154.366642</td>\n",
              "      <td>155154.366642</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.069573e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-05-08 22:00:00</td>\n",
              "      <td>7.058797e+07</td>\n",
              "      <td>6.993552e+07</td>\n",
              "      <td>7.159752e+07</td>\n",
              "      <td>7.058797e+07</td>\n",
              "      <td>7.058797e+07</td>\n",
              "      <td>200297.460741</td>\n",
              "      <td>200297.460741</td>\n",
              "      <td>200297.460741</td>\n",
              "      <td>200297.460741</td>\n",
              "      <td>200297.460741</td>\n",
              "      <td>200297.460741</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.078827e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-05-08 23:00:00</td>\n",
              "      <td>7.063536e+07</td>\n",
              "      <td>6.995876e+07</td>\n",
              "      <td>7.160555e+07</td>\n",
              "      <td>7.063536e+07</td>\n",
              "      <td>7.063536e+07</td>\n",
              "      <td>127033.847973</td>\n",
              "      <td>127033.847973</td>\n",
              "      <td>127033.847973</td>\n",
              "      <td>127033.847973</td>\n",
              "      <td>127033.847973</td>\n",
              "      <td>127033.847973</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.076239e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-05-09 00:00:00</td>\n",
              "      <td>7.068275e+07</td>\n",
              "      <td>6.977696e+07</td>\n",
              "      <td>7.145736e+07</td>\n",
              "      <td>7.068275e+07</td>\n",
              "      <td>7.068275e+07</td>\n",
              "      <td>-64004.026527</td>\n",
              "      <td>-64004.026527</td>\n",
              "      <td>-64004.026527</td>\n",
              "      <td>-64004.026527</td>\n",
              "      <td>-64004.026527</td>\n",
              "      <td>-64004.026527</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.061875e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>2021-05-17 23:00:00</td>\n",
              "      <td>5.741650e+07</td>\n",
              "      <td>5.620334e+07</td>\n",
              "      <td>5.893053e+07</td>\n",
              "      <td>5.640791e+07</td>\n",
              "      <td>5.859450e+07</td>\n",
              "      <td>127033.847977</td>\n",
              "      <td>127033.847977</td>\n",
              "      <td>127033.847977</td>\n",
              "      <td>127033.847977</td>\n",
              "      <td>127033.847977</td>\n",
              "      <td>127033.847977</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.754353e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>220</th>\n",
              "      <td>2021-05-18 00:00:00</td>\n",
              "      <td>5.735429e+07</td>\n",
              "      <td>5.587900e+07</td>\n",
              "      <td>5.883842e+07</td>\n",
              "      <td>5.624516e+07</td>\n",
              "      <td>5.862328e+07</td>\n",
              "      <td>-64004.026533</td>\n",
              "      <td>-64004.026533</td>\n",
              "      <td>-64004.026533</td>\n",
              "      <td>-64004.026533</td>\n",
              "      <td>-64004.026533</td>\n",
              "      <td>-64004.026533</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.729029e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>221</th>\n",
              "      <td>2021-05-18 01:00:00</td>\n",
              "      <td>5.729208e+07</td>\n",
              "      <td>5.553360e+07</td>\n",
              "      <td>5.871707e+07</td>\n",
              "      <td>5.610166e+07</td>\n",
              "      <td>5.864511e+07</td>\n",
              "      <td>-264151.046571</td>\n",
              "      <td>-264151.046571</td>\n",
              "      <td>-264151.046571</td>\n",
              "      <td>-264151.046571</td>\n",
              "      <td>-264151.046571</td>\n",
              "      <td>-264151.046571</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.702793e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>222</th>\n",
              "      <td>2021-05-18 02:00:00</td>\n",
              "      <td>5.722988e+07</td>\n",
              "      <td>5.527597e+07</td>\n",
              "      <td>5.845177e+07</td>\n",
              "      <td>5.594232e+07</td>\n",
              "      <td>5.868056e+07</td>\n",
              "      <td>-331244.053737</td>\n",
              "      <td>-331244.053737</td>\n",
              "      <td>-331244.053737</td>\n",
              "      <td>-331244.053737</td>\n",
              "      <td>-331244.053737</td>\n",
              "      <td>-331244.053737</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.689863e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>2021-05-18 03:00:00</td>\n",
              "      <td>5.716767e+07</td>\n",
              "      <td>5.526153e+07</td>\n",
              "      <td>5.871909e+07</td>\n",
              "      <td>5.577408e+07</td>\n",
              "      <td>5.873862e+07</td>\n",
              "      <td>-207139.503841</td>\n",
              "      <td>-207139.503841</td>\n",
              "      <td>-207139.503841</td>\n",
              "      <td>-207139.503841</td>\n",
              "      <td>-207139.503841</td>\n",
              "      <td>-207139.503841</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.696053e+07</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>224 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                     ds         trend  ...  multiplicative_terms_upper          yhat\n",
              "0   2021-05-08 20:00:00  7.049319e+07  ...                         0.0  7.056695e+07\n",
              "1   2021-05-08 21:00:00  7.054058e+07  ...                         0.0  7.069573e+07\n",
              "2   2021-05-08 22:00:00  7.058797e+07  ...                         0.0  7.078827e+07\n",
              "3   2021-05-08 23:00:00  7.063536e+07  ...                         0.0  7.076239e+07\n",
              "4   2021-05-09 00:00:00  7.068275e+07  ...                         0.0  7.061875e+07\n",
              "..                  ...           ...  ...                         ...           ...\n",
              "219 2021-05-17 23:00:00  5.741650e+07  ...                         0.0  5.754353e+07\n",
              "220 2021-05-18 00:00:00  5.735429e+07  ...                         0.0  5.729029e+07\n",
              "221 2021-05-18 01:00:00  5.729208e+07  ...                         0.0  5.702793e+07\n",
              "222 2021-05-18 02:00:00  5.722988e+07  ...                         0.0  5.689863e+07\n",
              "223 2021-05-18 03:00:00  5.716767e+07  ...                         0.0  5.696053e+07\n",
              "\n",
              "[224 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JB_UYNJ-uYZr"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}