SARIMA_1YEAR_TO_1YEAR_Predict.ipynb

{
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  "metadata": {
    "colab": {
      "name": "SARIMA_1YEAR_TO_1YEAR_Predict",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNaD0q0dxpjbMtzyJt4fmhK",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ejihoon6065/Project_TurnAround/blob/master/SARIMA_1YEAR_TO_1YEAR_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": "jctUkmk4RKyk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "e51a8590-b3df-4f91-b1b1-a8404dec7e16"
      },
      "source": [
        "import pandas as pd\n",
        "import csv\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "#sns.set() # setting seaborn default for plots\n",
        "import matplotlib.font_manager as fm\n",
        "import copy\n",
        "# 그래프에서 마이너스 폰트 깨지는 문제에 대한 대처\n",
        "mpl.rcParams['axes.unicode_minus'] = False\n",
        "import numpy as np\n",
        "\n",
        "\n",
        "from scipy import stats  # Box-Cox 검정\n",
        "import statsmodels.api as sm  # qqplot\n",
        "from statsmodels.tsa.stattools import adfuller    # adfuller : ADF그래프 그려주는 함수\n",
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "from statsmodels.tsa.arima_model import ARIMA\n",
        "from pandas.plotting import register_matplotlib_converters\n",
        "from statsmodels.stats.diagnostic import acorr_ljungbox # Ljung-Box 검정\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "import itertools\n",
        "\n",
        "\n",
        "# 돌리기전에, https://colab.research.google.com/drive/1oBXX3k3OOjdivwlDhpLmAqfq5B5dzFR1#scrollTo=AbTlhWommsXE 에 있는 코드도 참고 "
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rGV35B1ZTGgC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "outputId": "1d1779ce-cf23-49a9-e6ad-25cb2959e026"
      },
      "source": [
        "# 현재 설정되어 있는 폰트 사이즈와 글꼴을 알아보자    ( https://colab.research.google.com/github/nicewook/datascience_exercise/blob/master/korean_font_on_matplotlib.ipynb#scrollTo=nzZ6wGntXBrP 참고)\n",
        "!python --version\n",
        "def current_font():\n",
        "  print(f\"설정 폰트 글꼴: {plt.rcParams['font.family']}, 설정 폰트 사이즈: {plt.rcParams['font.size']}\")  # 파이썬 3.6 이상 사용가능하다\n",
        "        \n",
        "current_font()\n",
        "\n",
        "# 그래프에서 한글깨짐방지를 위한 한글폰트(나눔폰트) 설치 및 설정과정\n",
        "\n",
        "!apt-get update -qq                    # 나눔폰트(한글) 설치\n",
        "!apt-get install fonts-nanum* -qq\n",
        "\n",
        "path = '/usr/share/fonts/truetype/nanum/NanumGothicEco.ttf'  # 설치된 나눔글꼴중 원하는 녀석의 전체 경로를 가져오자\n",
        "font_name = fm.FontProperties(fname=path, size=10).get_name()\n",
        "print(font_name)\n",
        "plt.rc('font', family=font_name)\n",
        "\n",
        "fm._rebuild()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Python 3.6.9\n",
            "설정 폰트 글꼴: ['sans-serif'], 설정 폰트 사이즈: 10.0\n",
            "Selecting previously unselected package fonts-nanum.\n",
            "(Reading database ... 144676 files and directories currently installed.)\n",
            "Preparing to unpack .../fonts-nanum_20170925-1_all.deb ...\n",
            "Unpacking fonts-nanum (20170925-1) ...\n",
            "Selecting previously unselected package fonts-nanum-eco.\n",
            "Preparing to unpack .../fonts-nanum-eco_1.000-6_all.deb ...\n",
            "Unpacking fonts-nanum-eco (1.000-6) ...\n",
            "Selecting previously unselected package fonts-nanum-extra.\n",
            "Preparing to unpack .../fonts-nanum-extra_20170925-1_all.deb ...\n",
            "Unpacking fonts-nanum-extra (20170925-1) ...\n",
            "Selecting previously unselected package fonts-nanum-coding.\n",
            "Preparing to unpack .../fonts-nanum-coding_2.5-1_all.deb ...\n",
            "Unpacking fonts-nanum-coding (2.5-1) ...\n",
            "Setting up fonts-nanum-extra (20170925-1) ...\n",
            "Setting up fonts-nanum (20170925-1) ...\n",
            "Setting up fonts-nanum-coding (2.5-1) ...\n",
            "Setting up fonts-nanum-eco (1.000-6) ...\n",
            "Processing triggers for fontconfig (2.12.6-0ubuntu2) ...\n",
            "NanumGothic Eco\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DlWfGHooRzVp",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "outputId": "e5b13f8f-08d1-43ab-c7a9-47f7ec5f671a"
      },
      "source": [
        "!pip install -U pykrx  # KRX데이터를 크롤링하기 위한 라이브러리설치"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pykrx\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/c9/12/70cc31494c9e727fa216103b674d231124fabdac6ee8a4d8f43059afbc36/pykrx-0.1.41-py3-none-any.whl (40kB)\n",
            "\u001b[K     |████████████████████████████████| 40kB 1.9MB/s \n",
            "\u001b[?25hRequirement already satisfied, skipping upgrade: numpy in /usr/local/lib/python3.6/dist-packages (from pykrx) (1.18.5)\n",
            "Collecting datetime\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/73/22/a5297f3a1f92468cc737f8ce7ba6e5f245fcfafeae810ba37bd1039ea01c/DateTime-4.3-py2.py3-none-any.whl (60kB)\n",
            "\u001b[K     |████████████████████████████████| 61kB 3.5MB/s \n",
            "\u001b[?25hRequirement already satisfied, skipping upgrade: xlrd in /usr/local/lib/python3.6/dist-packages (from pykrx) (1.1.0)\n",
            "Requirement already satisfied, skipping upgrade: pandas in /usr/local/lib/python3.6/dist-packages (from pykrx) (1.0.5)\n",
            "Requirement already satisfied, skipping upgrade: requests in /usr/local/lib/python3.6/dist-packages (from pykrx) (2.23.0)\n",
            "Requirement already satisfied, skipping upgrade: pytz in /usr/local/lib/python3.6/dist-packages (from datetime->pykrx) (2018.9)\n",
            "Collecting zope.interface\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/57/33/565274c28a11af60b7cfc0519d46bde4125fcd7d32ebc0a81b480d0e8da6/zope.interface-5.1.0-cp36-cp36m-manylinux2010_x86_64.whl (234kB)\n",
            "\u001b[K     |████████████████████████████████| 235kB 11.6MB/s \n",
            "\u001b[?25hRequirement already satisfied, skipping upgrade: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas->pykrx) (2.8.1)\n",
            "Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->pykrx) (2.10)\n",
            "Requirement already satisfied, skipping upgrade: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->pykrx) (2020.6.20)\n",
            "Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->pykrx) (3.0.4)\n",
            "Requirement already satisfied, skipping upgrade: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->pykrx) (1.24.3)\n",
            "Requirement already satisfied, skipping upgrade: setuptools in /usr/local/lib/python3.6/dist-packages (from zope.interface->datetime->pykrx) (50.3.0)\n",
            "Requirement already satisfied, skipping upgrade: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.6.1->pandas->pykrx) (1.15.0)\n",
            "Installing collected packages: zope.interface, datetime, pykrx\n",
            "Successfully installed datetime-4.3 pykrx-0.1.41 zope.interface-5.1.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zQ-f3EMDTtN1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "abf20247-007b-4da2-a326-2dd666a51cf2"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UyJ_jzvIRtEX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "outputId": "52253433-2ef2-4343-d13d-bbad1f128454"
      },
      "source": [
        "# 주가 크롤링\n",
        "\n",
        "from pykrx import stock\n",
        "df = stock.get_market_ohlcv_by_date(\"20180701\", \"20200831\", \"122870\") # DataFrame, (시작날짜,종료날짜,종목번호)\n",
        "df"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>와이지엔터테인먼트</th>\n",
              "      <th>시가</th>\n",
              "      <th>고가</th>\n",
              "      <th>저가</th>\n",
              "      <th>종가</th>\n",
              "      <th>거래량</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>날짜</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>2018-07-02</th>\n",
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              "      <td>38050</td>\n",
              "      <td>38700</td>\n",
              "      <td>37350</td>\n",
              "      <td>37800</td>\n",
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              "    <tr>\n",
              "      <th>2018-07-05</th>\n",
              "      <td>37800</td>\n",
              "      <td>38000</td>\n",
              "      <td>36200</td>\n",
              "      <td>36850</td>\n",
              "      <td>267248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-06</th>\n",
              "      <td>36650</td>\n",
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              "      <td>36350</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2020-08-25</th>\n",
              "      <td>47200</td>\n",
              "      <td>49350</td>\n",
              "      <td>47000</td>\n",
              "      <td>48700</td>\n",
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              "      <th>2020-08-28</th>\n",
              "      <td>50900</td>\n",
              "      <td>52500</td>\n",
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              "      <td>49000</td>\n",
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              "      <th>2020-08-31</th>\n",
              "      <td>48950</td>\n",
              "      <td>49000</td>\n",
              "      <td>46000</td>\n",
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              "<p>535 rows × 5 columns</p>\n",
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            "text/plain": [
              "와이지엔터테인먼트      시가     고가     저가     종가      거래량\n",
              "날짜                                             \n",
              "2018-07-02  36200  37450  35550  35950   416807\n",
              "2018-07-03  36850  38200  36200  38100   689792\n",
              "2018-07-04  38050  38700  37350  37800   305088\n",
              "2018-07-05  37800  38000  36200  36850   267248\n",
              "2018-07-06  36650  37500  36350  37450   261478\n",
              "...           ...    ...    ...    ...      ...\n",
              "2020-08-25  47200  49350  47000  48700   397671\n",
              "2020-08-26  48750  50800  48100  50400   586564\n",
              "2020-08-27  49950  51400  49450  50900   528784\n",
              "2020-08-28  50900  52500  47600  49000  1298643\n",
              "2020-08-31  48950  49000  46000  46650   748647\n",
              "\n",
              "[535 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UzCK2M5iUIcV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# train,test 데이터 나누기\n",
        "\n",
        "train = df[:'2019-07-01']                   # 2018-07-02 ~ 2019-07-01 (약 1년) \n",
        "#test=df['2019-07-01':]                      # 2020-08-01 ~ 2020-08-31 (약 1개월)  \n",
        "\n",
        "\n",
        "# column들 중, 종가만 고려한다\n",
        "train.drop(['시가', '고가','저가','거래량'], axis='columns', inplace=True)\n",
        "#test.drop(['시가', '고가','저가','거래량'], axis='columns', inplace=True)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VdhaS0bnpbj2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "\n",
        "\n",
        "# 각 데이터의 column=['시가', '고가', '저가', '종가', '거래량']\n",
        "\n",
        "# Prophet모델에 input되기 위해서는 ['ds','y']로 column형식을 맞춰야 함\n",
        "\n",
        "train['날짜']=train.index\n",
        "#train=pd.DataFrame({'ds':train['날짜'],'y':train['종가']})\n",
        "train=pd.DataFrame({'y':train['종가']})\n",
        "#train=train.reset_index(drop=True)\n",
        "train   # "
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g1SiS4Gwj0my",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "outputId": "92fc5c39-3e20-4018-b461-fb29758fb0a9"
      },
      "source": [
        "train"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>날짜</th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-07-02</th>\n",
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              "    <tr>\n",
              "      <th>2018-07-03</th>\n",
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              "      <th>2018-07-04</th>\n",
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              "      <th>2018-07-05</th>\n",
              "      <td>36850</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2019-06-25</th>\n",
              "      <td>28750</td>\n",
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              "    <tr>\n",
              "      <th>2019-06-26</th>\n",
              "      <td>28400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-27</th>\n",
              "      <td>29150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-28</th>\n",
              "      <td>28950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01</th>\n",
              "      <td>28500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>245 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                y\n",
              "날짜               \n",
              "2018-07-02  35950\n",
              "2018-07-03  38100\n",
              "2018-07-04  37800\n",
              "2018-07-05  36850\n",
              "2018-07-06  37450\n",
              "...           ...\n",
              "2019-06-25  28750\n",
              "2019-06-26  28400\n",
              "2019-06-27  29150\n",
              "2019-06-28  28950\n",
              "2019-07-01  28500\n",
              "\n",
              "[245 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ztJFaXhwjrFh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "test1 = df['2019-07-02':'2019-08-30']            \n",
        "test2 = df['2019-09-02':'2019-10-31']          \n",
        "test3 = df['2019-11-01':'2019-12-31']          \n",
        "test4 = df['2020-01-02':'2020-02-29']           \n",
        "test5 = df['2020-03-02':'2020-04-30']  \n",
        "test_all=df['2019-07-02':'2020-04-30'] \n",
        "\n",
        "\n",
        "test1['날짜']=test1.index\n",
        "test1_n=pd.DataFrame({'y':test1['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test2['날짜']=test2.index\n",
        "test2_n=pd.DataFrame({'y':test2['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test3['날짜']=test3.index\n",
        "test3_n=pd.DataFrame({'y':test3['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test4['날짜']=test4.index\n",
        "test4_n=pd.DataFrame({'y':test4['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test5['날짜']=test5.index\n",
        "test5_n=pd.DataFrame({'y':test5['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test_all['날짜']=test_all.index\n",
        "test_all_n=pd.DataFrame({'y':test_all['종가']})\n",
        "#test=test.reset_index(drop=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BfX6OQiSV5uT",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "plt.rcParams[\"figure.figsize\"] = (10,5)\n",
        "plt.rcParams['lines.linewidth'] = 2\n",
        "plt.rcParams['lines.color'] = 'r'\n",
        "plt.rcParams['axes.grid'] = True "
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JSamBg1wUe4K",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "outputId": "d5be05f4-9b03-4b55-fe1a-569df82d74c8"
      },
      "source": [
        "# 시계열분해\n",
        "\n",
        "# 시계열데이터는 순서를 갖는 데이터, 즉 시간의 흐름에 따라 값이 변하는 데이터\n",
        "# 시계열에는 경향(trend), 계절성(seasonality), 주기(cycle), 불규칙성(irregular) 성분이 있음.\n",
        "\n",
        "result = seasonal_decompose(train.dropna(), model='additive',freq=10)   # freq = 10 (2-WEEKS )\n",
        "result.plot()\n",
        "plt.show()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "findfont: Font family ['NanumGothic Eco'] not found. Falling back to DejaVu Sans.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6y4-lyZ8WCLj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        },
        "outputId": "d526dcbb-a7f7-48a1-f651-cf8bd84bcf60"
      },
      "source": [
        "result = seasonal_decompose(train.dropna(), model='additive',freq=20)   # freq=20 (1-MONTH)\n",
        "result.plot()\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tN0iEGxthyHT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        },
        "outputId": "1eab37ee-74a4-4ac3-be0a-e907b66a74fc"
      },
      "source": [
        "result = seasonal_decompose(train.dropna(), model='additive',freq=60)   # freq=60 (3-MONTH)    # 추세(trend)가 어느정도 보이고, 계절성(seasonal)도 뚜렷한 것을 볼수 있음.\n",
        "result.plot()\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nVCJDgftWRO6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "outputId": "c055ef61-0096-4a57-ec04-c2e9f793d67a"
      },
      "source": [
        "# 잔차분포 확인\n",
        "\n",
        "residual=result.resid\n",
        "residual=residual.dropna()\n",
        "\n",
        "# 잔차 분포\n",
        "plt.scatter(x=residual.index,y=residual)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7f62e50da4a8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jp2Z0rBcWcO4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 686
        },
        "outputId": "00e26fbe-f78a-430e-9b6e-ce26e663e2e2"
      },
      "source": [
        "plt.hist(x=residual,bins=50)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([[0., 0., 0., ..., 0., 0., 0.],\n",
              "        [0., 0., 0., ..., 0., 0., 0.],\n",
              "        [0., 0., 0., ..., 0., 0., 0.],\n",
              "        ...,\n",
              "        [0., 0., 0., ..., 0., 0., 0.],\n",
              "        [0., 0., 0., ..., 0., 0., 0.],\n",
              "        [0., 0., 0., ..., 0., 0., 0.]]),\n",
              " array([-4590.85648148, -4395.94259259, -4201.0287037 , -4006.11481481,\n",
              "        -3811.20092593, -3616.28703704, -3421.37314815, -3226.45925926,\n",
              "        -3031.54537037, -2836.63148148, -2641.71759259, -2446.8037037 ,\n",
              "        -2251.88981481, -2056.97592593, -1862.06203704, -1667.14814815,\n",
              "        -1472.23425926, -1277.32037037, -1082.40648148,  -887.49259259,\n",
              "         -692.5787037 ,  -497.66481481,  -302.75092593,  -107.83703704,\n",
              "           87.07685185,   281.99074074,   476.90462963,   671.81851852,\n",
              "          866.73240741,  1061.6462963 ,  1256.56018519,  1451.47407407,\n",
              "         1646.38796296,  1841.30185185,  2036.21574074,  2231.12962963,\n",
              "         2426.04351852,  2620.95740741,  2815.8712963 ,  3010.78518519,\n",
              "         3205.69907407,  3400.61296296,  3595.52685185,  3790.44074074,\n",
              "         3985.35462963,  4180.26851852,  4375.18240741,  4570.0962963 ,\n",
              "         4765.01018519,  4959.92407407,  5154.83796296]),\n",
              " <a list of 185 Lists of Patches objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlMAAAEvCAYAAABhSUTPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAVqUlEQVR4nO3db6xkZ30f8O8va1NXrLETO6xWa2ob1YWu121hXQziRbwNTda0slvVjWylhkTAIgVHVKTt2lXljaAvSqs2KcKkiSByqNpsaJrSlbupA5u1/CIyxS4p9i5yujUJtrMtYKizC3LA5dcXd2iHy/0z5pl7d+7m85FGmnPOc8955vzOnPu958ydp7o7AAB8b77vXHcAAGArE6YAAAYIUwAAA4QpAIABwhQAwABhCgBgwAXnasOXX355X3XVVedq8xvqa1/7Wl760pee626wBjVabOqz+NRosanP/D366KNf7u4fXGnZOQtTV111VR555JFztfkN9eCDD+bGG288191gDWq02NRn8anRYlOf+auqP1htmdt8AAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAxYN0xV1S9X1Rer6vFVlldVfaCqTlXVZ6vqtfPvJgDAYprlytR9SfavsfymJNdMHgeS/MJ4twAAtoZ1w1R3P5TkK2s0uSXJR3vJw0kuraqd8+ogAMAim8dnpnYleWpq+unJPACA896mjs1XVQeydCswO3bsyIMPPriZm980Z8+eXfW1nT59Ojt3unB3rq1Vo0X1zWfO5sJd2zd8O8+fOJGLrr12Q9Z98tmT2X3Z7nXbzbs+jz3zXK7bdcnc1pckX/rCmVy6reZSk1n3+Zkzj+fii/cMb2/Wvqy137bae2j62NuI42HRbLX6bHndve4jyVVJHl9l2S8muX1q+okkO9db5969e/t8dfz48VWXHTp0aNP6werWqtGieurgQ5uynZOvevWGrXvPfXtmajfv+lx58P65rq+7+4PvPDa3msy6zz957JVz2d5apvuy1n7bau+h6WNvI46HRbPV6rMVJHmkV8k087jNdyTJWyb/1ff6JM919+k5rBcAYOGte5uvqn41yY1JLq+qp5McSnJhknT3v0pyNMmbk5xK8vUkP7lRnQUAWDTrhqnuvn2d5Z3kXXPrEQDAFuIb0AEABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAEzhamq2l9VT1TVqaq6a4Xlf6aqjlfVZ6rqs1X15vl3FQBg8awbpqpqW5J7k9yUZHeS26tq97Jm/yjJx7r7NUluS/KheXcUAGARzXJl6nVJTnX3k939jSSHk9yyrE0nednk+SVJ/nB+XQQAWFwXzNBmV5KnpqafTnLDsjY/m+S3quqnk7w0yZvm0jsAgAVX3b12g6pbk+zv7rdPpu9IckN33znV5j2Tdf3zqnpDko8k2dPd31q2rgNJDiTJjh079h4+fHiuL2ZRnD17Ntu3b19x2enTp7Nz585N7hHLrVWjRfXNZ87mwl0b3+fnT5zIRddeuyHrPvnsyey+bPmnBL7bvOvz2DPP5bpdl8xtfUnypS+cyaXbai41mXWfnznzeC6+eM/w9mbty1r7bau9h6aPvY04HhbNVqvPVrBv375Hu/v6FRd295qPJG9I8sDU9N1J7l7W5kSSV0xNP5nk5Wutd+/evX2+On78+KrLDh06tGn9YHVr1WhRPXXwoU3ZzslXvXrD1r3nvj0ztZt3fa48eP9c19fd/cF3HptbTWbd55889sq5bG8t031Za79ttffQ9LG3EcfDotlq9dkKkjzSq2SaWT4z9ekk11TV1VX1kix9wPzIsjZfSPLDSVJVfz7JRUm+9GISHwDAVrRumOruF5LcmeSBJJ/L0n/tnaiq91bVzZNmP5PkHVX135L8apKfmKQ4AIDz2iwfQE93H01ydNm8e6aen0zyxvl2DQBg8fkGdACAAcIUAMAAYQoAYIAwBQAwQJgCABggTAEADBCmAAAGCFMAAAOEKQCAAcIUAMAAYQoAYIAwBQAwQJgCABggTAEADBCmAAAGCFMAAAOEKQCAAcIUAMAAYQoAYIAwBQAwQJgCABggTAEADBCmAAAGCFMAAAOEKQCAAcIUAMAAYQoAYIAwBQAwQJgCABggTAEADBCmAAAGCFMAAAOEKQCAAcIUAMAAYQoAYIAwBQAwQJgCABggTAEADBCmAAAGCFMAAAOEKQCAAcIUAMAAYQoAYMBMYaqq9lfVE1V1qqruWqXNj1XVyao6UVX/dr7dBABYTBes16CqtiW5N8lfTfJ0kk9X1ZHuPjnV5pokdyd5Y3d/tapevlEdBgBYJLNcmXpdklPd/WR3fyPJ4SS3LGvzjiT3dvdXk6S7vzjfbgIALKbq7rUbVN2aZH93v30yfUeSG7r7zqk2H0/ye0nemGRbkp/t7v+8wroOJDmQJDt27Nh7+PDheb2OhXL27Nls3759xWWnT5/Ozp07N7lHLLdWjRbVN585mwt3bXyfnz9xIhdde+2GrPvksyez+7Ld67abd30ee+a5XLfrkrmtL0m+9IUzuXRbzaUms+7zM2cez8UX7xne3qx9WWu/bbX30PSxtxHHw6LZavXZCvbt2/dod1+/4sLuXvOR5NYkH56aviPJB5e1uT/Jf0hyYZKrkzyV5NK11rt3794+Xx0/fnzVZYcOHdq0frC6tWq0qJ46+NCmbOfkq169Yevec9+emdrNuz5XHrx/ruvr7v7gO4/NrSaz7vNPHnvlXLa3lum+rLXfttp7aPrY24jjYdFstfpsBUke6VUyzSy3+Z5J8oqp6Ssm86Y9neRId3+zuz+fpatU18wU9QAAtrBZwtSnk1xTVVdX1UuS3JbkyLI2H09yY5JU1eVJ/lySJ+fYTwCAhbRumOruF5LcmeSBJJ9L8rHuPlFV762qmyfNHkjybFWdTHI8yd/v7mc3qtMAAIti3a9GSJLuPprk6LJ590w97yTvmTwAAP7E8A3oAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAEzhamq2l9VT1TVqaq6a412f6uquqqun18XAQAW17phqqq2Jbk3yU1Jdie5vap2r9Du4iTvTvKpeXcSAGBRzXJl6nVJTnX3k939jSSHk9yyQrv3JXl/kufn2D8AgIU2S5jaleSpqemnJ/P+n6p6bZJXdPd/mmPfAAAWXnX32g2qbk2yv7vfPpm+I8kN3X3nZPr7kvx2kp/o7t+vqgeT/L3ufmSFdR1IciBJduzYsffw4cPzfC0L4+zZs9m+ffuKy06fPp2dO3duco9Ybq0aLapvPnM2F+7a+D4/f+JELrr22g1Z98lnT2b3Zd/1KYHvMu/6PPbMc7lu1yVzW1+SfOkLZ3LptppLTWbd52fOPJ6LL94zvL1Z+7LWfttq76HpY28jjodFs9XqsxXs27fv0e5e+TPh3b3mI8kbkjwwNX13krunpi9J8uUkvz95PJ/kD5Ncv9Z69+7d2+er48ePr7rs0KFDm9YPVrdWjRbVUwcf2pTtnHzVqzds3Xvu2zNTu3nX58qD9891fd3dH3znsbnVZNZ9/sljr5zL9tYy3Ze19ttWew9NH3sbcTwsmq1Wn60gySO9SqaZ5Tbfp5NcU1VXV9VLktyW5MhUGHuuuy/v7qu6+6okDye5uVe4MgUAcL5ZN0x19wtJ7kzyQJLPJflYd5+oqvdW1c0b3UEAgEV2wSyNuvtokqPL5t2zStsbx7sFALA1+AZ0AIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBgwExhqqr2V9UTVXWqqu5aYfl7qupkVX22qo5V1ZXz7yoAwOJZN0xV1bYk9ya5KcnuJLdX1e5lzT6T5Pru/gtJfj3JP513RwEAFtEsV6Zel+RUdz/Z3d9IcjjJLdMNuvt4d399Mvlwkivm200AgMU0S5jaleSpqemnJ/NW87YkvznSKQCAraK6e+0GVbcm2d/db59M35Hkhu6+c4W2fyfJnUl+qLv/eIXlB5IcSJIdO3bsPXz48PgrWEBnz57N9u3bV1x2+vTp7Ny5c5N7xHJr1WhRffOZs7lw18b3+fkTJ3LRtdduyLpPPnsyuy9b/imB7zbv+jz2zHO5btclc1tfknzpC2dy6baaS01m3ednzjyeiy/eM7y9Wfuy1n7bau+h6WNvI46HRbPV6rMV7Nu379Huvn7Fhd295iPJG5I8MDV9d5K7V2j3piSfS/Ly9dbZ3dm7d2+fr44fP77qskOHDm1aP1jdWjVaVE8dfGhTtnPyVa/esHXvuW/PTO3mXZ8rD94/1/V1d3/wncfmVpNZ9/knj71yLttby3Rf1tpvW+09NH3sbcTxsGi2Wn22giSP9CqZZpbbfJ9Ock1VXV1VL0lyW5Ij0w2q6jVJfjHJzd39xe8l8QEAbEXrhqnufiFLt+4eyNKVp49194mqem9V3Txp9s+SbE/y76rqd6vqyCqrAwA4r1wwS6PuPprk6LJ590w9f9Oc+wUAsCX4BnQAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGDATGGqqvZX1RNVdaqq7lph+Z+qql+bLP9UVV01744CACyidcNUVW1Lcm+Sm5LsTnJ7Ve1e1uxtSb7a3X82yc8lef+8OwoAsIhmuTL1uiSnuvvJ7v5GksNJblnW5pYkvzJ5/utJfriqan7dBABYTLOEqV1Jnpqafnoyb8U23f1CkueSXDaPDgIALLLq7rUbVN2aZH93v30yfUeSG7r7zqk2j0/aPD2Z/h+TNl9etq4DSQ5MJl+V5Il5vZAFc3mSL6/binNJjRab+iw+NVps6jN/V3b3D6604IIZfviZJK+Ymr5iMm+lNk9X1QVJLkny7PIVdfcvJfmlWXq8lVXVI919/bnuB6tTo8WmPotPjRab+myuWW7zfTrJNVV1dVW9JMltSY4sa3MkyVsnz29N8tu93iUvAIDzwLpXprr7haq6M8kDSbYl+eXuPlFV703ySHcfSfKRJP+6qk4l+UqWAhcAwHlvltt86e6jSY4um3fP1PPnk/zt+XZtSzvvb2WeB9RosanP4lOjxaY+m2jdD6ADALA6w8kAAAwQpl6kqvrLVfXC5Csjvj3vrVX13yePt07N31tVj02G2fnAt7/ItKp+oKo+MWn/iar6/nPxWs43VfXjVfXZyT7/nar6i1PLVhwSafKPFZ+azP+1yT9ZGCLpHFpv+Co2RlW9oqqOV9XJqjpRVe+ezF/xfFVLPjCp02er6rVT61rxnMi4qtpWVZ+pqvsn0y/6HFZVd0/mP1FVP3puXsn5RZh6ESZD67w/yW9NzfuBJIeS3JClb4s/NBWOfiHJO5JcM3nsn8y/K8mx7r4mybHJNOM+n+SHuvu6JO/L5DMD6wyJ9P4kPzcZCumrWRoaKTFE0jkx4/BVbIwXkvxMd+9O8vok75rs+9XOVzfl/5/bDmTpfLfeOZFx707yuanpF3UOm9T0tiTXZul30ocm7zsGCFMvzk8n+fdJvjg170eTfKK7v9LdX03yiST7q2pnkpd198OTr4n4aJK/MfmZ6eF3fmVqPgO6+3cmNUiSh7P0nWjJKkMiTa4U/pUsDYGUfGctDJF0bswyfBUboLtPd/d/nTw/k6Vf2Luy+vnqliQf7SUPJ7l0ct5b8Zy4iS/lvFVVVyT5a0k+PJn+Xs5htyQ53N1/3N2fT3IqS+87BghTM6qqXUn+ZiZ/fU1ZbbidXZPny+cnyY7uPj15/j+T7Jh7h3lbkt+cPF+tRpcl+d+TIZCm53/HzxgiaVPNMnwVG2xyS+g1ST6V1c9Xa5371HBj/HySf5DkW5Pp7+Ucpj4bQJia3c8nOdjd31q35YswuWrlXyrnqKr2ZSlMHTzXfYGtpqq2Z+kK/N/t7j+aXuZ8de5U1V9P8sXufvRc94XvNtP3TP1JVVXvytJnnpKlIXIOT+70XJ7kzVX1QpaG0rlx6seuSPLgZP4Vy+Z/exie/1VVO7v79OSy+PRtQ16EZTV6c5Zq8+EkN3X3t4c0Wm1IpGezdGvigslfbtM1mmmIJOZuluGr2CBVdWGWgtS/6e7fmMxe7Xy1Wq1WOycy5o1Jbq6qNye5KMnLkvzLvPhzmPfYBnBlag3dfW93/6XJ4+ruvqq7r8rS/eef6u6PZ+mb4X+kqr5/8iHLH0nywOSy+B9V1esn96nfkuQ/TlY9PfzOW6fm8yJN1yhLfxz8RpI7uvv3ppqtOCTS5K/s41kaAin5zloYIuncmGX4KjbA5Dz1kSSf6+5/MbVotfPVkSRvmfxX3+uTPDc57614TtyUF3Ee6+67u/uKye+g27J0TvrxvPhz2JEkt03+2+/qLP0DwX/ZpJdx3nJlalB3f6Wq3pelXwJJ8t7u/srk+U8luS/Jn87S53e+/Rmef5LkY1X1tiR/kOTHNq/H57V7svSZgA9NriC+0N3XrzYk0uRnDmbpiuM/TvKZLP0ySQyRdE6sUys21huT3JHksar63cm8f5jVz1dHs3Q1+FSSryf5yWTdcyLz96LOYZPh4D6W5GSW/oPzXd39fza/2+cX34AOADDAbT4AgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAAD/i+aeiUdj+B+wQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C8kTAqLRWgVM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# 정상성 확인함수 \n",
        "\n",
        "# p-value가 0.05이하여야 정상성을 만족함  \n",
        "# 그래프는 rollin_mean : 이동평균, rolling_std : 이동표준편차  \n",
        "# 이동평균, 이동표준편차 : 정상성을 만족한다는 것은, 데이터의 평균과 분산이 일정하다는 의미이다. \n",
        "# 이동평균,이동표준편차 그래프를 통해서 평균과 표준편차가 x축과 평행인 선을 그리는지 알수 있기 때문에 그래프를 만들었음 \n",
        " \n",
        "def get_stationarity(timeseries,wind_date):\n",
        "    \n",
        "    # rolling statistics\n",
        "    rolling_mean = timeseries.rolling(window=wind_date).mean()\n",
        "    rolling_std = timeseries.rolling(window=wind_date).std()\n",
        "    \n",
        "    # rolling statistics plot\n",
        "    original = plt.plot(timeseries, color='blue', label='Original')\n",
        "    mean = plt.plot(rolling_mean, color='red', label='Rolling Mean')\n",
        "    std = plt.plot(rolling_std, color='black', label='Rolling Std')\n",
        "    plt.legend(loc='best')\n",
        "    plt.title('Rolling Mean & Standard Deviation')\n",
        "    plt.show(block=False)\n",
        "    \n",
        "    # Dickey–Fuller test:\n",
        "    result = adfuller(timeseries['y'])\n",
        "    print('ADF Statistic: {}'.format(result[0]))\n",
        "    print('p-value: {}'.format(result[1]))\n",
        "    print('Critical Values:')\n",
        "    for key, value in result[4].items():\n",
        "        print('\\t{}: {}'.format(key, value))"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FYVVe4H1dfV3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "outputId": "c437ed94-ea4f-4ca0-e898-a80798969d4b"
      },
      "source": [
        "get_stationarity(train,60) # p-value : 0.60.. > 0.05 => Non-Stationary"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "ADF Statistic: -1.1859293191590858\n",
            "p-value: 0.679619087484661\n",
            "Critical Values:\n",
            "\t1%: -3.4575505077947746\n",
            "\t5%: -2.8735087323013526\n",
            "\t10%: -2.573148434859185\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_8s2i2R6WtcV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "train_diff=train.diff()\n",
        "train_diff=train_diff.dropna()                # 종가를 1차차분한 값들 -> train_diff "
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xFEZfGmJdmzB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "outputId": "b0815122-dcb9-44e9-f750-235b4234655b"
      },
      "source": [
        "get_stationarity(train_diff,60) # p-value : 0.00.. < 0.05  / 이동평균선과 이동표준편차가 x축과 평행 => Stationary (p,d,q중, d = 1 / s=60)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "ADF Statistic: -17.20699429927333\n",
            "p-value: 6.405149576186949e-30\n",
            "Critical Values:\n",
            "\t1%: -3.4575505077947746\n",
            "\t5%: -2.8735087323013526\n",
            "\t10%: -2.573148434859185\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K88JmRPReHDS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        },
        "outputId": "70a8ee43-c84b-4c5e-d466-5b2c5f68ecbf"
      },
      "source": [
        "# ACF그래프 (자기상관함수) : \n",
        "#자기상관은 시점 t 와 (t - n) 간의 상관 관계를 의미하며 한동안(일정 기간) 증가하거나 감소하는 경우 양의 자기상관이 존재한다고 하고 시점마다 증감이 반복되는 경우 이를 음의 자기상관이라 한다\n",
        "\n",
        "# PACF그래프 (부분자기상관함수) : \n",
        "# 부분자기상관은 시점 (t-1) ~ (t-n+1)의 영향을 배제한, 시점 t와 (t - n)과의 상관관계를 의미한다.   \n",
        "\n",
        "# ACF, PACF그래프의 x축은 lag,지연값,시점 (t-n)에서 n의 값이다.\n",
        "\n",
        "# train 원데이터의 ACF, PACF그래프 그리기\n",
        "fig = plt.figure(figsize=(12,8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "fig = sm.graphics.tsa.plot_acf(train, lags=30, ax=ax1, alpha=0.01)\n",
        "ax2 = fig.add_subplot(212)\n",
        "fig = sm.graphics.tsa.plot_pacf(train,lags=30,ax=ax2,alpha=0.01)\n",
        "plt.tight_layout()\n",
        "plt.show\n",
        "\n",
        "\n",
        "# => Random Walk (Non-Stationary)의 특징을 보임 (Acf그래프에서는 천천히 감소, Pacf에서는 급격하게 감소(lag=1에서 절단점 발생))"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ASvPm1vpkneO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        },
        "outputId": "d625a5b9-89a1-48d2-f545-ca7fbe549665"
      },
      "source": [
        "# train데이터를 1차차분한 값의 ACF,PACF그래프 그리기\n",
        "fig = plt.figure(figsize=(12,8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "fig = sm.graphics.tsa.plot_acf(train_diff, lags=60, ax=ax1, alpha=0.01)\n",
        "ax2 = fig.add_subplot(212)\n",
        "fig = sm.graphics.tsa.plot_pacf(train_diff,lags=60,ax=ax2,alpha=0.01)\n",
        "plt.tight_layout()\n",
        "plt.show\n",
        "\n",
        "# => White noise(Stationary)데이터의 acf,pacf그래프 양상을 보임 , ARIMA(p,d,q)에서 p=0, q=0 \n",
        "\n",
        "\n",
        "# 따라서, 1차차분한 값의 p=0,q=0이라고 판단됨 => (p,d,q) = (0,1,0)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PwL79Z0inowq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "d4032879-4530-4563-ff11-78d42b890228"
      },
      "source": [
        "# 그래프등을 통해 판단된 값으로 ARIMA모델실행, Fitting\n",
        "'''\n",
        "#from statsmodels.tsa.arima_model import ARIMA\n",
        "#from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
        "#model = SARIMAX(train, order=(0,1,0),seasonal_order=(0,1,1,60))\n",
        "#model_fit = model.fit(trend='c',full_output=True, disp=1) \n",
        "#print(model_fit.summary()) \n",
        "\n",
        "#  P > |z| 값이 일반적으로 학습의 적정성을 위해 확인되는 t-test값\n",
        "\n",
        "#model_fit.plot_diagnostics()\n",
        "#plt.tight_layout()\n",
        "#plt.show()\n",
        "\n",
        "\n",
        "forecast_test1 = model_fit.get_prediction(period=43)\n",
        "#forecast_test1=pd.DataFrame(forecast_test1)\n",
        "pred1 = forecast_test1.conf_int(alpha=0.05)\n",
        "pred1_mean=forecast_test1.predicted_mean\n",
        "#print(forecast_test1)\n",
        "pred1_mean.plot()\n",
        "'''"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "\"\\n#from statsmodels.tsa.arima_model import ARIMA\\n#from statsmodels.tsa.statespace.sarimax import SARIMAX\\n#model = SARIMAX(train, order=(0,1,0),seasonal_order=(0,1,1,60))\\n#model_fit = model.fit(trend='c',full_output=True, disp=1) \\n#print(model_fit.summary()) \\n\\n#  P > |z| 값이 일반적으로 학습의 적정성을 위해 확인되는 t-test값\\n\\n#model_fit.plot_diagnostics()\\n#plt.tight_layout()\\n#plt.show()\\n\\n\\nforecast_test1 = model_fit.get_prediction(period=43)\\n#forecast_test1=pd.DataFrame(forecast_test1)\\npred1 = forecast_test1.conf_int(alpha=0.05)\\npred1_mean=forecast_test1.predicted_mean\\n#print(forecast_test1)\\npred1_mean.plot()\\n\""
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EIfjRyX8v_mH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Auto_Arima모델 "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ckACj26rwc8Z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 720
        },
        "outputId": "3670c054-ff65-428f-98c9-83b82d7738b7"
      },
      "source": [
        "!pip install pmdarima"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pmdarima\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/be/62/725b3b6ae0e56c77534de5a8139322e7b863ca53fd5bd6bd3b7de87d0c20/pmdarima-1.7.1-cp36-cp36m-manylinux1_x86_64.whl (1.5MB)\n",
            "\u001b[K     |████████████████████████████████| 1.5MB 3.0MB/s \n",
            "\u001b[?25hRequirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.4.1)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.18.5)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (0.16.0)\n",
            "Requirement already satisfied: pandas>=0.19 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.0.5)\n",
            "Collecting setuptools<50.0.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/c3/a9/5dc32465951cf4812e9e93b4ad2d314893c2fa6d5f66ce5c057af6e76d85/setuptools-49.6.0-py3-none-any.whl (803kB)\n",
            "\u001b[K     |████████████████████████████████| 808kB 16.5MB/s \n",
            "\u001b[?25hCollecting Cython<0.29.18,>=0.29\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/e7/d7/510ddef0248f3e1e91f9cc7e31c0f35f8954d0af92c5c3fd4c853e859ebe/Cython-0.29.17-cp36-cp36m-manylinux1_x86_64.whl (2.1MB)\n",
            "\u001b[K     |████████████████████████████████| 2.1MB 16.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: urllib3 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.24.3)\n",
            "Collecting statsmodels<0.12,>=0.11\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/cb/83/540fd83238a18abe6c2d280fa8e489ac5fcefa1f370f0ca1acd16ae1b860/statsmodels-0.11.1-cp36-cp36m-manylinux1_x86_64.whl (8.7MB)\n",
            "\u001b[K     |████████████████████████████████| 8.7MB 25.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: scikit-learn>=0.22 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (0.22.2.post1)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.19->pmdarima) (2.8.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.19->pmdarima) (2018.9)\n",
            "Requirement already satisfied: patsy>=0.5 in /usr/local/lib/python3.6/dist-packages (from statsmodels<0.12,>=0.11->pmdarima) (0.5.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.6.1->pandas>=0.19->pmdarima) (1.15.0)\n",
            "\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Installing collected packages: setuptools, Cython, statsmodels, pmdarima\n",
            "  Found existing installation: setuptools 50.3.0\n",
            "    Uninstalling setuptools-50.3.0:\n",
            "      Successfully uninstalled setuptools-50.3.0\n",
            "  Found existing installation: Cython 0.29.21\n",
            "    Uninstalling Cython-0.29.21:\n",
            "      Successfully uninstalled Cython-0.29.21\n",
            "  Found existing installation: statsmodels 0.10.2\n",
            "    Uninstalling statsmodels-0.10.2:\n",
            "      Successfully uninstalled statsmodels-0.10.2\n",
            "Successfully installed Cython-0.29.17 pmdarima-1.7.1 setuptools-49.6.0 statsmodels-0.11.1\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "pkg_resources",
                  "statsmodels"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0VIDKgUjoZwn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "outputId": "9d4c69aa-a36e-4c63-af28-c90400b7546a"
      },
      "source": [
        "train"
      ],
      "execution_count": 34,
      "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>y</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>날짜</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-07-02</th>\n",
              "      <td>35950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-03</th>\n",
              "      <td>38100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-04</th>\n",
              "      <td>37800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-05</th>\n",
              "      <td>36850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-07-06</th>\n",
              "      <td>37450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-25</th>\n",
              "      <td>28750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-26</th>\n",
              "      <td>28400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-27</th>\n",
              "      <td>29150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-28</th>\n",
              "      <td>28950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-01</th>\n",
              "      <td>28500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>245 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                y\n",
              "날짜               \n",
              "2018-07-02  35950\n",
              "2018-07-03  38100\n",
              "2018-07-04  37800\n",
              "2018-07-05  36850\n",
              "2018-07-06  37450\n",
              "...           ...\n",
              "2019-06-25  28750\n",
              "2019-06-26  28400\n",
              "2019-06-27  29150\n",
              "2019-06-28  28950\n",
              "2019-07-01  28500\n",
              "\n",
              "[245 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w4wJl-_po0S3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 610
        },
        "outputId": "5cc8aaa4-a743-490d-d3f7-e1b069a3ab47"
      },
      "source": [
        "from pmdarima import auto_arima\n",
        "stepwise_model = auto_arima(train, start_p=1, start_q=1,\n",
        "                           max_p=3, max_q=3, m=60,\n",
        "                           seasonal=True,\n",
        "                           d=1, D=1, trace=True,\n",
        "                           error_action=\n",
        "                            'ignore',  \n",
        "                           suppress_warnings=True,\n",
        "                           stepwise=True)\n",
        "\n",
        "\n",
        "# AIC값이 최소값이 나오는 파라미터를 선정한다.\n",
        "# AIC는 Akaike Information Criterion이다. AIC는 얼마나 모델이 데이터를 잘 피팅하는지를 측정함. \n",
        "# AIC(Akaike Information Criterion) value\n",
        "# The AIC measures how well a model fits the data while taking into account the overall complexity of the model.\n",
        "# A model that fits the data very well while using lots of features will be assigned a larger AIC score than a model that uses fewer features to achieve the same goodness-of-fit.\n"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Performing stepwise search to minimize aic\n",
            " ARIMA(1,1,1)(1,1,1)[60]             : AIC=inf, Time=86.01 sec\n",
            " ARIMA(0,1,0)(0,1,0)[60]             : AIC=3304.350, Time=1.75 sec\n",
            " ARIMA(1,1,0)(1,1,0)[60]             : AIC=3265.434, Time=25.00 sec\n",
            " ARIMA(0,1,1)(0,1,1)[60]             : AIC=3252.857, Time=32.51 sec\n",
            " ARIMA(0,1,1)(0,1,0)[60]             : AIC=3303.620, Time=1.46 sec\n",
            " ARIMA(0,1,1)(1,1,1)[60]             : AIC=inf, Time=42.14 sec\n",
            " ARIMA(0,1,1)(0,1,2)[60]             : AIC=inf, Time=nan sec\n",
            " ARIMA(0,1,1)(1,1,0)[60]             : AIC=3271.713, Time=9.57 sec\n",
            " ARIMA(0,1,1)(1,1,2)[60]             : AIC=inf, Time=nan sec\n",
            " ARIMA(0,1,0)(0,1,1)[60]             : AIC=inf, Time=24.19 sec\n",
            " ARIMA(1,1,1)(0,1,1)[60]             : AIC=3253.235, Time=69.65 sec\n",
            " ARIMA(0,1,2)(0,1,1)[60]             : AIC=3253.592, Time=37.56 sec\n",
            " ARIMA(1,1,0)(0,1,1)[60]             : AIC=3252.684, Time=30.75 sec\n",
            " ARIMA(1,1,0)(0,1,0)[60]             : AIC=3303.258, Time=0.95 sec\n",
            " ARIMA(1,1,0)(1,1,1)[60]             : AIC=inf, Time=65.67 sec\n",
            " ARIMA(1,1,0)(0,1,2)[60]             : AIC=inf, Time=nan sec\n",
            " ARIMA(1,1,0)(1,1,2)[60]             : AIC=inf, Time=nan sec\n",
            " ARIMA(2,1,0)(0,1,1)[60]             : AIC=3253.375, Time=37.20 sec\n",
            " ARIMA(2,1,1)(0,1,1)[60]             : AIC=3255.958, Time=94.32 sec\n",
            " ARIMA(1,1,0)(0,1,1)[60] intercept   : AIC=3250.965, Time=34.42 sec\n",
            " ARIMA(1,1,0)(0,1,0)[60] intercept   : AIC=3304.559, Time=1.23 sec\n",
            " ARIMA(1,1,0)(1,1,1)[60] intercept   : AIC=inf, Time=51.95 sec\n",
            " ARIMA(1,1,0)(0,1,2)[60] intercept   : AIC=inf, Time=nan sec\n",
            " ARIMA(1,1,0)(1,1,0)[60] intercept   : AIC=3265.332, Time=31.76 sec\n",
            " ARIMA(1,1,0)(1,1,2)[60] intercept   : AIC=inf, Time=nan sec\n",
            " ARIMA(0,1,0)(0,1,1)[60] intercept   : AIC=3251.065, Time=36.08 sec\n",
            " ARIMA(2,1,0)(0,1,1)[60] intercept   : AIC=3252.201, Time=45.06 sec\n",
            " ARIMA(1,1,1)(0,1,1)[60] intercept   : AIC=3251.879, Time=96.02 sec\n",
            " ARIMA(0,1,1)(0,1,1)[60] intercept   : AIC=3251.176, Time=40.85 sec\n",
            " ARIMA(2,1,1)(0,1,1)[60] intercept   : AIC=3253.766, Time=93.38 sec\n",
            "\n",
            "Best model:  ARIMA(1,1,0)(0,1,1)[60] intercept\n",
            "Total fit time: 989.590 seconds\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ue3oCmsE0OKh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# 잡음(불규칙요인)의 분포 살피기 (표준잔차, 잔차분포, Normal Q-Q (QQ-Plot), 상관성)\n",
        "\n",
        "# https://data.library.virginia.edu/diagnostic-plots/ 참고\n",
        "#https://www.digitalocean.com/community/tutorials/a-guide-to-time-series-forecasting-with-arima-in-python-3 참고\n",
        "\n",
        "# 표준잔차 : 추정 회귀식으로부터 관측치가 얼마나 떨어져 있는지, 절댓값 3이상이면 이상값이 확실, 연구자에 따라 2~3사이의 값을 이상값일 가능성이 달라짐.\n",
        "# 잔차분포 : \n",
        "# QQ-plot : 수집 데이터를 표준정규분포의 분위수와 비교하여 그리는 그래프 -> 데이터의 정규성 가정에 대한 검토를 가능하게 해줌 -> 집단이 정규성을 따른다면, 점들이 직선의 형태로 그려짐.\n",
        "# 상관성 : correlation확인\n",
        "\n",
        "result_seasonal=stepwise_model.fit(train)\n",
        "result_seasonal.plot_diagnostics(figsize=(12,10))          \n",
        "plt.show()                                                "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lA4t3FQftXKP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "result=pd.DataFrame() # 예측한 10개월을 concat해서  한번에 볼 데이터프레임"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NQxlgZWKkfbt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "'''\n",
        "test1 = df['2019-07-02':'2019-08-30']            \n",
        "test2 = df['2019-09-02':'2019-10-31']          \n",
        "test3 = df['2019-11-01':'2019-12-31']          \n",
        "test4 = df['2020-01-02':'2020-02-29']           \n",
        "test5 = df['2020-03-02':'2020-04-30']\n",
        "  \n",
        "test_all=df['2019-07-02':'2020-04-30'] \n",
        "\n",
        "\n",
        "test1['날짜']=test1.index\n",
        "test1_n=pd.DataFrame({'y':test1['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test2['날짜']=test2.index\n",
        "test2_n=pd.DataFrame({'y':test2['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test3['날짜']=test3.index\n",
        "test3_n=pd.DataFrame({'y':test3['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test4['날짜']=test4.index\n",
        "test4_n=pd.DataFrame({'y':test4['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test5['날짜']=test5.index\n",
        "test5_n=pd.DataFrame({'y':test5['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "test_all['날짜']=test_all.index\n",
        "test_all_n=pd.DataFrame({'y':test_all['종가']})\n",
        "#test=test.reset_index(drop=True)\n",
        "\n",
        "print(train.shape) # 245 x x2 \n",
        "print(test1.shape) # 43 x 8 (약 두달) \n",
        "print(test2.shape) # 40 x 6\n",
        "print(test3.shape) # 41 x 6\n",
        "print(test4.shape) # 40 x 6\n",
        "print(test5.shape) # 42 x 6\n",
        "print(test_all.shape) # 42 x 6\n",
        "\n",
        "print(test1.columns) # -> 종가만\n",
        "'''"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cD7GjFPLnAoR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1decd22a-0753-42cd-a800-debace1c4b72"
      },
      "source": [
        "# 10개월 예측 : \n",
        "# model에 train을 fit -> predict(2달) -> predict값을 train에 concat(합침) -> 다시 model에 train을 fit -> ... (반복)   \n",
        "\n",
        "start_date=['2019-07-02','2019-09-02','2019-11-01','2020-01-02','2020-03-02']\n",
        "end_date=['2019-08-30','2019-10-31','2019-12-31','2020-02-29','2020-04-30']\n",
        "\n",
        "test_all=df[start_date[0]:end_date[-1]]\n",
        "\n",
        "for i in range(0,5):\n",
        "  test=df[start_date[i]:end_date[i]]\n",
        "  print(test)\n",
        "  '''\n",
        "  result_seasonal=stepwise_model.fit(train)\n",
        "\n",
        "  pred_seasonal = result_seasonal.predict(n_periods=test.shape[0])\n",
        "  pred_seasonal = pd.DataFrame(pred_seasonal,index = test1.index,columns=['y'])\n",
        "  pred_seasonal['y']=round(pred_seasonal['y'])\n",
        "\n",
        "  train=pd.concat([train,pred_seasonal],axis=0)\n",
        "  '''"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "와이지엔터테인먼트      시가     고가     저가     종가     거래량\n",
            "날짜                                            \n",
            "2019-07-02  28250  29800  28200  29000  384554\n",
            "2019-07-03  29300  29300  28350  28550  264976\n",
            "2019-07-04  28550  29150  28500  28850  131863\n",
            "2019-07-05  29000  29200  28600  29050  126249\n",
            "2019-07-08  28800  29300  27600  27950  260711\n",
            "2019-07-09  27850  28700  27700  27700  184764\n",
            "2019-07-10  27750  29150  27750  28600  287805\n",
            "2019-07-11  28600  29850  28600  29850  290271\n",
            "2019-07-12  29500  29800  28350  28500  397232\n",
            "2019-07-15  28800  28800  28000  28150  188563\n",
            "2019-07-16  28150  28400  27900  28250  147086\n",
            "2019-07-17  28100  28150  27450  27550  166749\n",
            "2019-07-18  26950  27450  25750  27000  462908\n",
            "2019-07-19  27000  28300  27000  27800  216773\n",
            "2019-07-22  28000  28000  27200  27750   82836\n",
            "2019-07-23  27750  28200  27300  27350  137128\n",
            "2019-07-24  27350  27700  27150  27150  125235\n",
            "2019-07-25  26900  27100  26350  26550  136106\n",
            "2019-07-26  26000  26500  25150  25250  326307\n",
            "2019-07-29  25000  25500  24300  24350  283671\n",
            "2019-07-30  24300  25500  24300  25250  212539\n",
            "2019-07-31  24800  25350  24350  25000  148721\n",
            "2019-08-01  24600  25600  24450  24800  134212\n",
            "2019-08-02  24150  25350  24150  24800   99501\n",
            "2019-08-05  24500  24700  22300  22300  289040\n",
            "2019-08-06  21150  24000  21150  22500  427754\n",
            "2019-08-07  22500  23750  22500  23450  175381\n",
            "2019-08-08  23500  26000  23350  26000  232391\n",
            "2019-08-09  25000  25050  23050  23150  483862\n",
            "2019-08-12  22900  23400  22500  23050  127546\n",
            "2019-08-13  22100  22600  21200  22150  375401\n",
            "2019-08-14  22400  22600  21250  21400  302913\n",
            "2019-08-16  20950  21250  20400  21000  241257\n",
            "2019-08-19  20900  21650  20600  21400  217041\n",
            "2019-08-20  21150  21550  21100  21350  141306\n",
            "2019-08-21  21350  22500  21200  22450  230229\n",
            "2019-08-22  22450  22450  21400  21600  301137\n",
            "2019-08-23  21400  21650  21000  21250  143441\n",
            "2019-08-26  20600  20850  19300  19450  527359\n",
            "2019-08-27  19600  20300  19550  20000  223649\n",
            "2019-08-28  19950  20900  19900  20800  171287\n",
            "2019-08-29  20800  21150  20600  20750  134345\n",
            "2019-08-30  21150  21650  21000  21200  147455\n",
            "와이지엔터테인먼트      시가     고가     저가     종가      거래량\n",
            "날짜                                             \n",
            "2019-09-02  20850  22200  20850  21900   194960\n",
            "2019-09-03  21800  22450  21700  21750   140789\n",
            "2019-09-04  21950  22350  21550  22200   113154\n",
            "2019-09-05  22450  22550  21900  22300   106122\n",
            "2019-09-06  22400  22650  21850  21850    70760\n",
            "2019-09-09  22100  22350  21850  22150   108343\n",
            "2019-09-10  22150  22750  22100  22600   175239\n",
            "2019-09-11  22550  23500  22400  23500   230595\n",
            "2019-09-16  23050  23250  22500  23000   155178\n",
            "2019-09-17  23050  23200  22450  22750   119104\n",
            "2019-09-18  22800  23350  22600  22750   117321\n",
            "2019-09-19  22800  23100  22400  22550   107572\n",
            "2019-09-20  22600  27550  22250  24200  2022021\n",
            "2019-09-23  24400  24950  24150  24500   433756\n",
            "2019-09-24  24500  24700  23700  23750   249813\n",
            "2019-09-25  23500  23700  22550  22700   226677\n",
            "2019-09-26  22850  24300  22850  23700   327291\n",
            "2019-09-27  24000  24450  23750  23900   195906\n",
            "2019-09-30  24100  24200  22850  23050   236607\n",
            "2019-10-01  23200  24200  22800  24200   215461\n",
            "2019-10-02  23600  23850  23200  23200   235928\n",
            "2019-10-04  23250  23250  22450  22850   181631\n",
            "2019-10-07  23000  23700  22850  23400   194442\n",
            "2019-10-08  23400  23900  22900  23800   148848\n",
            "2019-10-10  23550  23700  23000  23550   150525\n",
            "2019-10-11  23800  25200  23650  23950   474910\n",
            "2019-10-14  24350  25850  24150  25650   558471\n",
            "2019-10-15  25600  26700  25350  26000   425303\n",
            "2019-10-16  26150  26500  25750  25800   169610\n",
            "2019-10-17  26150  26300  24800  25250   221089\n",
            "2019-10-18  25200  25200  24350  24750   218737\n",
            "2019-10-21  24850  25450  24400  24900   243871\n",
            "2019-10-22  25100  26550  24850  26400   513743\n",
            "2019-10-23  26700  26800  25850  26350   326506\n",
            "2019-10-24  26450  26750  25800  26400   203440\n",
            "2019-10-25  26450  26550  25550  25850   188961\n",
            "2019-10-28  26200  26700  25900  26000   302018\n",
            "2019-10-29  26000  26100  25500  25700   216804\n",
            "2019-10-30  25900  26900  25700  26750   491262\n",
            "2019-10-31  27000  27000  26400  26750   290557\n",
            "와이지엔터테인먼트      시가     고가     저가     종가     거래량\n",
            "날짜                                            \n",
            "2019-11-01  26900  27500  26650  26900  361597\n",
            "2019-11-04  26900  27300  26800  27050  166356\n",
            "2019-11-05  27150  27150  26500  26900  154367\n",
            "2019-11-06  26900  27050  26300  26500  193562\n",
            "2019-11-07  26200  26900  26150  26650  132801\n",
            "2019-11-08  26700  26800  24700  25400  499115\n",
            "2019-11-11  24900  26100  24850  26050  199545\n",
            "2019-11-12  25900  26200  25400  26150  142238\n",
            "2019-11-13  25900  26400  25500  25550  125815\n",
            "2019-11-14  25600  25700  24850  25400  156877\n",
            "2019-11-15  25400  25550  25000  25400   99995\n",
            "2019-11-18  25550  25850  25200  25450   97726\n",
            "2019-11-19  25400  25600  24750  24850  144043\n",
            "2019-11-20  25050  25100  23950  24300  161294\n",
            "2019-11-21  24150  24500  23350  23800  158884\n",
            "2019-11-22  23800  24450  23800  24050  101893\n",
            "2019-11-25  24400  25100  24200  24950  150776\n",
            "2019-11-26  25350  25350  24600  25150  101890\n",
            "2019-11-27  25300  25300  24650  24950   72173\n",
            "2019-11-28  24950  25100  24550  24600   67522\n",
            "2019-11-29  24600  27000  24300  24850  705130\n",
            "2019-12-02  24850  25500  24750  24800  116471\n",
            "2019-12-03  24650  24750  23750  24300  165865\n",
            "2019-12-04  24250  24800  24100  24400   89504\n",
            "2019-12-05  24200  24800  24200  24400   80400\n",
            "2019-12-06  24600  25750  24050  25500  200115\n",
            "2019-12-09  25700  26250  24800  25100  196271\n",
            "2019-12-10  25100  26000  25000  25550  156763\n",
            "2019-12-11  25500  26000  25350  25350   88349\n",
            "2019-12-12  25350  25900  25250  25450  144774\n",
            "2019-12-13  25700  26400  25700  26250  168192\n",
            "2019-12-16  26300  26300  25400  25900  127645\n",
            "2019-12-17  26100  26400  25800  26200   82943\n",
            "2019-12-18  26150  26450  25850  26200   99819\n",
            "2019-12-19  26200  26550  25800  26150   93434\n",
            "2019-12-20  26400  26400  25950  26100   55552\n",
            "2019-12-23  26300  26350  25850  26150   75549\n",
            "2019-12-24  26100  26400  25900  26000   87561\n",
            "2019-12-26  26000  26500  26000  26500  122516\n",
            "2019-12-27  26350  26800  26050  26750  108407\n",
            "2019-12-30  26200  27700  26200  27350  357012\n",
            "와이지엔터테인먼트      시가     고가     저가     종가      거래량\n",
            "날짜                                             \n",
            "2020-01-02  27250  27700  26500  27500   224040\n",
            "2020-01-03  27600  28800  26600  28400   563162\n",
            "2020-01-06  28400  30500  28000  30000  1141917\n",
            "2020-01-07  30500  31200  29500  30750   634303\n",
            "2020-01-08  30750  30950  29400  30550   457119\n",
            "2020-01-09  31200  32250  30800  32050   500618\n",
            "2020-01-10  32050  32050  31050  31750   219049\n",
            "2020-01-13  32350  34850  32200  34700  1145821\n",
            "2020-01-14  35100  36750  34450  35000   568891\n",
            "2020-01-15  35100  35950  34500  35800   288280\n",
            "2020-01-16  35750  35750  34600  35150   323680\n",
            "2020-01-17  35100  35300  34350  34950   241874\n",
            "2020-01-20  34950  35600  34300  34450   266582\n",
            "2020-01-21  34350  34550  33100  33300   359966\n",
            "2020-01-22  33200  34500  33100  33950   231387\n",
            "2020-01-23  33000  33950  32900  33300   235061\n",
            "2020-01-28  30500  32300  28000  31300   752471\n",
            "2020-01-29  31300  33150  31300  32750   300269\n",
            "2020-01-30  32750  33250  31900  32550   237379\n",
            "2020-01-31  33000  33350  31600  31600   242343\n",
            "2020-02-03  30400  34250  30400  33950   454352\n",
            "2020-02-04  33650  35050  33250  34200   261373\n",
            "2020-02-05  34250  34700  33400  33500   175969\n",
            "2020-02-06  33950  34350  33000  33650   193934\n",
            "2020-02-07  33800  34550  33250  33900   143567\n",
            "2020-02-10  33300  33300  32650  32650   164585\n",
            "2020-02-11  32650  33200  31850  32000   248802\n",
            "2020-02-12  32200  32900  32050  32700   160443\n",
            "2020-02-13  32850  33500  32400  33200   242917\n",
            "2020-02-14  33200  33250  32450  32650   114880\n",
            "2020-02-17  32650  34950  32000  34600   424372\n",
            "2020-02-18  34700  35350  33950  34050   259913\n",
            "2020-02-19  34100  34650  33150  33900   151941\n",
            "2020-02-20  33750  33750  32700  32900   195634\n",
            "2020-02-21  32500  32650  31050  31050   298120\n",
            "2020-02-24  30100  31400  29400  30050   402842\n",
            "2020-02-25  30050  31100  29800  30600   222417\n",
            "2020-02-26  30200  32450  29900  31750   277212\n",
            "2020-02-27  32000  33750  31500  32000   448357\n",
            "2020-02-28  31600  32050  30000  30300   295035\n",
            "와이지엔터테인먼트      시가     고가     저가     종가      거래량\n",
            "날짜                                             \n",
            "2020-03-02  30550  31300  29300  30900   307466\n",
            "2020-03-03  31450  31900  29650  29950   393072\n",
            "2020-03-04  29800  30300  29050  29700   416340\n",
            "2020-03-05  30000  30050  29000  29100   305440\n",
            "2020-03-06  28100  28850  25950  26450  1036503\n",
            "2020-03-09  25600  25750  24700  25100   542646\n",
            "2020-03-10  24600  25750  24400  25300   334610\n",
            "2020-03-11  25350  26550  24900  25150   571946\n",
            "2020-03-12  25050  25050  22700  23250   528861\n",
            "2020-03-13  21100  24000  20500  22700   482022\n",
            "2020-03-16  23000  23750  21750  22200   278885\n",
            "2020-03-17  20700  22850  20700  22400   254009\n",
            "2020-03-18  22450  23200  21000  21000   310288\n",
            "2020-03-19  21650  22300  18950  19550   442647\n",
            "2020-03-20  19650  21450  19350  21350   278436\n",
            "2020-03-23  19900  20100  19000  19450   263535\n",
            "2020-03-24  19900  21800  19450  21400   276303\n",
            "2020-03-25  22100  24650  21900  24650   443802\n",
            "2020-03-26  25350  26900  24300  24650   491865\n",
            "2020-03-27  25850  25900  23550  24400   324990\n",
            "2020-03-30  23300  24000  22650  23800   231466\n",
            "2020-03-31  24050  24300  23250  24050   300035\n",
            "2020-04-01  23900  24650  23100  23100   259274\n",
            "2020-04-02  23300  24100  22850  24100   143869\n",
            "2020-04-03  24100  24150  23250  23650   163565\n",
            "2020-04-06  23900  25000  23500  25000   249158\n",
            "2020-04-07  25650  26000  24700  25300   210131\n",
            "2020-04-08  25050  26900  24800  26250   387566\n",
            "2020-04-09  27000  27050  26100  26550   207071\n",
            "2020-04-10  26550  28900  26100  28900   708254\n",
            "2020-04-13  28900  29800  28000  28000   477031\n",
            "2020-04-14  28600  29100  27900  28900   245061\n",
            "2020-04-16  29550  30800  29300  30550   582642\n",
            "2020-04-17  31300  31400  29800  30850   430579\n",
            "2020-04-20  30950  30950  29600  29600   423534\n",
            "2020-04-21  29150  29150  27950  28700   491120\n",
            "2020-04-22  28000  29250  27800  29250   239240\n",
            "2020-04-23  29300  29450  28800  29150   138419\n",
            "2020-04-24  28900  28900  27750  28050   206180\n",
            "2020-04-27  28350  29100  28000  28850   194223\n",
            "2020-04-28  28850  30500  28450  29550   386562\n",
            "2020-04-29  29600  30000  29000  29650   201966\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mDam9TUGkz0Z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 942
        },
        "outputId": "3c9144d4-e0f9-46d9-9f71-4ff000653a4a"
      },
      "source": [
        "# 10개월 예측 : \n",
        "# model에 train을 fit -> predict(2달) -> predict값을 train에 concat(합침) -> 다시 model에 train을 fit -> ... (반복)   \n",
        "\n",
        "start_date=['2019-07-02','2019-09-02','2019-11-01','2020-01-02','2020-03-02']\n",
        "end_date=['2019-08-30','2019-10-31','2019-12-31','2020-02-29','2020-04-30']\n",
        "\n",
        "test_all=df[start_date[0]:end_date[-1]]\n",
        "\n",
        "for i in range(0,5):\n",
        "  test=df[start_date[i]:end_date[i]]\n",
        "  \n",
        "  result_seasonal=stepwise_model.fit(train)\n",
        "\n",
        "  pred_seasonal = result_seasonal.predict(n_periods=test.shape[0])\n",
        "  print(pred_seasonal)\n",
        "  pred_seasonal = pd.DataFrame(pred_seasonal,index = test.index,columns=['y'])\n",
        "  pred_seasonal['y']=round(pred_seasonal['y'])\n",
        "\n",
        "  train=pd.concat([train,pred_seasonal],axis=0)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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            " 13779.08304989 13954.40306845 11947.26753144]\n",
            "[11649.6564902  11903.0022419  11953.25086831 10825.43693306\n",
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          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bEwrUsCyp0je",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "outputId": "0c85e006-e47d-4add-be64-d9b0af5c4236"
      },
      "source": [
        "pred=train[start_date[0]:]\n",
        "pred"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>y</th>\n",
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              "    <tr>\n",
              "      <th>날짜</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-07-02</th>\n",
              "      <td>29130.0</td>\n",
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              "    <tr>\n",
              "      <th>2019-07-03</th>\n",
              "      <td>28652.0</td>\n",
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              "      <th>2019-07-04</th>\n",
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              "      <th>2019-07-08</th>\n",
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              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2020-04-23</th>\n",
              "      <td>-77728.0</td>\n",
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              "      <th>2020-04-24</th>\n",
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              "      <th>2020-04-27</th>\n",
              "      <td>-79679.0</td>\n",
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              "    <tr>\n",
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              "      <td>-80114.0</td>\n",
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              "      <th>2020-04-29</th>\n",
              "      <td>-80914.0</td>\n",
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              "<p>206 rows × 1 columns</p>\n",
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              "                  y\n",
              "날짜                 \n",
              "2019-07-02  29130.0\n",
              "2019-07-03  28652.0\n",
              "2019-07-04  28450.0\n",
              "2019-07-05  27956.0\n",
              "2019-07-08  27650.0\n",
              "...             ...\n",
              "2020-04-23 -77728.0\n",
              "2020-04-24 -78308.0\n",
              "2020-04-27 -79679.0\n",
              "2020-04-28 -80114.0\n",
              "2020-04-29 -80914.0\n",
              "\n",
              "[206 rows x 1 columns]"
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          "metadata": {
            "tags": []
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          "execution_count": 39
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    {
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      "metadata": {
        "id": "Ky97Q_oCqod3",
        "colab_type": "code",
        "colab": {
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          "height": 434
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        "outputId": "cc6575a9-ea9a-44e6-b994-27b297ea73f9"
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      "source": [
        "test_all\n"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>와이지엔터테인먼트</th>\n",
              "      <th>시가</th>\n",
              "      <th>고가</th>\n",
              "      <th>저가</th>\n",
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              "      <th>2019-07-02</th>\n",
              "      <td>28250</td>\n",
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              "      <td>29000</td>\n",
              "      <td>29200</td>\n",
              "      <td>28600</td>\n",
              "      <td>29050</td>\n",
              "      <td>126249</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-07-08</th>\n",
              "      <td>28800</td>\n",
              "      <td>29300</td>\n",
              "      <td>27600</td>\n",
              "      <td>27950</td>\n",
              "      <td>260711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-04-23</th>\n",
              "      <td>29300</td>\n",
              "      <td>29450</td>\n",
              "      <td>28800</td>\n",
              "      <td>29150</td>\n",
              "      <td>138419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-04-24</th>\n",
              "      <td>28900</td>\n",
              "      <td>28900</td>\n",
              "      <td>27750</td>\n",
              "      <td>28050</td>\n",
              "      <td>206180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-04-27</th>\n",
              "      <td>28350</td>\n",
              "      <td>29100</td>\n",
              "      <td>28000</td>\n",
              "      <td>28850</td>\n",
              "      <td>194223</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-04-28</th>\n",
              "      <td>28850</td>\n",
              "      <td>30500</td>\n",
              "      <td>28450</td>\n",
              "      <td>29550</td>\n",
              "      <td>386562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-04-29</th>\n",
              "      <td>29600</td>\n",
              "      <td>30000</td>\n",
              "      <td>29000</td>\n",
              "      <td>29650</td>\n",
              "      <td>201966</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>206 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "와이지엔터테인먼트      시가     고가     저가     종가     거래량\n",
              "날짜                                            \n",
              "2019-07-02  28250  29800  28200  29000  384554\n",
              "2019-07-03  29300  29300  28350  28550  264976\n",
              "2019-07-04  28550  29150  28500  28850  131863\n",
              "2019-07-05  29000  29200  28600  29050  126249\n",
              "2019-07-08  28800  29300  27600  27950  260711\n",
              "...           ...    ...    ...    ...     ...\n",
              "2020-04-23  29300  29450  28800  29150  138419\n",
              "2020-04-24  28900  28900  27750  28050  206180\n",
              "2020-04-27  28350  29100  28000  28850  194223\n",
              "2020-04-28  28850  30500  28450  29550  386562\n",
              "2020-04-29  29600  30000  29000  29650  201966\n",
              "\n",
              "[206 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vS0QwYgumONm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377
        },
        "outputId": "04918b60-7806-4952-af8d-4fba65b247f2"
      },
      "source": [
        "# 10개월 예측값(pred)과 실제값(test_all)을 그래프로 비교 및 mape확인\n",
        "pred=train[start_date[0]:]\n",
        "\n",
        "fm._rebuild()\n",
        "fig = plt.figure(figsize=(15,12))\n",
        "ax1 = fig.add_subplot(211)\n",
        "ax1.plot(test_all['종가'],label='실제값' )                 ##\n",
        "ax1.plot(pred['y'],color='red',label='예측값')    ## \n",
        "ax1.set_xlabel('Date')\n",
        "ax1.set_ylabel('Y')\n",
        "ax1.legend(loc=1)\n",
        "plt.show\n",
        "\n",
        "# Compute the Mean of Absolute Percentage Errors\n",
        "\n",
        "#mape = ((abs( pred['y'] - test_all['종가'] ) / test_all['종가'])*100).mean()\n",
        "#print('The MAPE of our forecasts is {}%'.format( round(mape, 2))) "
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x864 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}