Strategy_4.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Strategy-4",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# 4. 하락장 삼성전자 금투 수급 매매\n",
        "금투 수급이 기관 수급의 30% 이상일 때,\n",
        "\n",
        "*하락장 기준\n",
        ": 3개월 이상 고점 대비 25% 이상 하락한 기간\n",
        "- 2007/11 ~ 2008/11\n",
        "- 2011/05 ~ 2011/09\n",
        "- 2018/02 ~ 2020/03/19\n",
        "- 2021/07 ~ 현재"
      ],
      "metadata": {
        "id": "tHYS9fVcTrpz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Google Drive Mount\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tv1_pHE-gPvD",
        "outputId": "c6dcb7a0-4f19-4bb2-8015-e7ea6a44ebac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import csv\n",
        "\n",
        "# Load Data\n",
        "file_path = './drive/Shareddrives/CS360/madcamp-3-week/data/'\n",
        "file_path = file_path + '삼성전자_일별데이터.csv'\n",
        "\n",
        "# Save File\n",
        "_file = open(file_path, 'r', encoding = 'cp949')\n",
        "file_rdr = csv.reader(_file)\n",
        "\n",
        "date_lst = []\n",
        "\n",
        "\n",
        "\n",
        "file_dict = dict()\n",
        "for line in file_rdr:\n",
        "  if line[0] == '일자':\n",
        "    continue\n",
        "\n",
        "\n",
        "  if line[0][2:-3] in ['07-11', '07-12', '08-01', '08-02', '08-03', '08-04', '08-05', '08-06', '08-07', \n",
        "                       '08-08', '08-09', '08-10', '08-11', '11-05', '11-06', '11-07', '11-08', '11-09']:\n",
        "    file_dict[line[0]] = {\n",
        "        '시가' : int(line[1]),\n",
        "        '종가' : int(line[2]),\n",
        "        '기관계' : int(line[3]),\n",
        "        '금융투자' : int(line[4])\n",
        "    }\n",
        "    date_lst.append(line[0])\n",
        "  \n",
        "  elif line[0][2:4] == '18':\n",
        "    if line[0][5:7] != '01':\n",
        "      file_dict[line[0]] = {\n",
        "          '시가' : int(line[1]),\n",
        "          '종가' : int(line[2]),\n",
        "          '기관계' : int(line[3]),\n",
        "          '금융투자' : int(line[4])\n",
        "      }\n",
        "      date_lst.append(line[0])\n",
        "  \n",
        "  elif line[0][2:4] == '19':\n",
        "    file_dict[line[0]] = {\n",
        "        '시가' : int(line[1]),\n",
        "        '종가' : int(line[2]),\n",
        "        '기관계' : int(line[3]),\n",
        "        '금융투자' : int(line[4])\n",
        "    }\n",
        "    date_lst.append(line[0])\n",
        "  \n",
        "  elif line[0][2:-3] in ['20-01', '20-02', '20-03']:\n",
        "    if line[0][-2] == '2' or '3':\n",
        "      file_dict[line[0]] = {\n",
        "        '시가' : int(line[1]),\n",
        "        '종가' : int(line[2]),\n",
        "        '기관계' : int(line[3]),\n",
        "        '금융투자' : int(line[4])\n",
        "      }\n",
        "      date_lst.append(line[0])\n",
        "  \n",
        "  elif line[0][2:-3] in ['21-07', '21-08', '21-09', '21-10', '21-11', '21-12']:\n",
        "    file_dict[line[0]] = {\n",
        "      '시가' : int(line[1]),\n",
        "      '종가' : int(line[2]),\n",
        "      '기관계' : int(line[3]),\n",
        "      '금융투자' : int(line[4])\n",
        "    }\n",
        "    date_lst.append(line[0])\n",
        "  \n",
        "  elif line[0][2:4] == '22':\n",
        "    file_dict[line[0]] = {\n",
        "      '시가' : int(line[1]),\n",
        "      '종가' : int(line[2]),\n",
        "      '기관계' : int(line[3]),\n",
        "      '금융투자' : int(line[4])\n",
        "    }\n",
        "    date_lst.append(line[0])\n",
        "\n",
        "date_lst.reverse()"
      ],
      "metadata": {
        "id": "RKo0-a3dkKyl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tgt_cnt = 0\n",
        "tgt_date_lst = []\n",
        "open_open_win, open_open_lose = [], []\n",
        "open_close_win, open_close_lose = [], []\n",
        "close_open_win, close_open_lose = [], []\n",
        "close_close_win, close_close_lose = [], []\n",
        "for i in range(len(date_lst)):\n",
        "  if i == len(date_lst) - 1:\n",
        "    break\n",
        "  \n",
        "  curr = date_lst[i]\n",
        "  next = date_lst[i + 1]\n",
        "\n",
        "  curr_open = file_dict[curr]['시가']\n",
        "  curr_close = file_dict[curr]['종가']\n",
        "  curr_vol = file_dict[curr]['기관계']\n",
        "  curr_tgt = file_dict[curr]['금융투자']\n",
        "\n",
        "  next_open = file_dict[next]['시가']\n",
        "  next_close = file_dict[next]['종가']\n",
        "\n",
        "  if curr_tgt < 0 or curr_vol < 0:\n",
        "    continue\n",
        "  \n",
        "  if curr_tgt / curr_vol >= 0.3:\n",
        "    tgt_cnt += 1\n",
        "    tgt_date_lst.append(curr)\n",
        "\n",
        "    open_open_gap = next_open - curr_open\n",
        "    open_open_per = (open_open_gap / curr_open) * 100\n",
        "    if open_open_per > 0 :\n",
        "      open_open_win.append(open_open_per)\n",
        "    else:\n",
        "      open_open_lose.append(open_open_per)\n",
        "\n",
        "    open_close_gap = next_open - curr_close\n",
        "    open_close_per = (open_close_gap / curr_close) * 100\n",
        "    if open_close_per > 0:\n",
        "      open_close_win.append(open_close_per)\n",
        "    else:\n",
        "      open_close_lose.append(open_close_per)\n",
        "\n",
        "    close_open_gap = next_close - curr_open\n",
        "    close_open_per = (close_open_gap / curr_open) * 100\n",
        "    if close_open_per > 0:\n",
        "      close_open_win.append(close_open_per)\n",
        "    else:\n",
        "      close_open_lose.append(close_open_per)\n",
        "\n",
        "    close_close_gap = next_close - curr_close\n",
        "    close_close_per = (close_close_gap / curr_close) * 100\n",
        "    if close_close_per > 0:\n",
        "      close_close_win.append(close_close_per)\n",
        "    else:\n",
        "      close_close_lose.append(close_close_per)\n",
        "\n",
        "print(tgt_date_lst)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yua6_5mEThsX",
        "outputId": "757bfcd7-4aa7-4281-d220-c22f9488715b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['2007-11-08', '2007-11-19', '2007-11-20', '2007-11-27', '2007-12-13', '2007-12-14', '2007-12-17', '2007-12-27', '2008-01-07', '2008-01-08', '2008-01-21', '2008-01-22', '2008-01-28', '2008-02-11', '2008-02-13', '2008-02-18', '2008-03-13', '2008-03-31', '2008-04-04', '2008-04-11', '2008-04-22', '2008-04-23', '2008-04-30', '2008-05-06', '2008-05-07', '2008-05-08', '2008-05-20', '2008-06-10', '2008-06-12', '2008-06-24', '2008-07-04', '2008-07-07', '2008-07-08', '2008-07-14', '2008-07-15', '2008-07-16', '2008-07-22', '2008-07-23', '2008-08-01', '2008-08-06', '2008-08-19', '2008-08-20', '2008-08-22', '2008-08-26', '2008-08-27', '2008-09-17', '2008-09-18', '2008-09-24', '2008-09-25', '2008-09-26', '2008-10-02', '2008-10-22', '2008-11-07', '2008-11-10', '2008-11-13', '2008-11-28', '2011-05-06', '2011-05-16', '2011-06-13', '2011-06-20', '2011-06-21', '2011-06-27', '2011-07-15', '2011-07-22', '2011-07-26', '2011-08-05', '2011-08-09', '2011-09-16', '2018-02-19', '2018-02-21', '2018-02-23', '2018-02-26', '2018-02-27', '2018-03-09', '2018-03-19', '2018-03-20', '2018-03-21', '2018-03-22', '2018-03-30', '2018-04-05', '2018-04-06', '2018-04-09', '2018-04-10', '2018-04-18', '2018-04-20', '2018-04-23', '2018-05-10', '2018-05-17', '2018-05-18', '2018-05-21', '2018-05-28', '2018-06-11', '2018-06-14', '2018-06-15', '2018-06-18', '2018-06-19', '2018-06-26', '2018-06-28', '2018-07-05', '2018-07-09', '2018-07-17', '2018-07-20', '2018-07-23', '2018-07-24', '2018-07-25', '2018-07-26', '2018-07-27', '2018-07-31', '2018-08-09', '2018-08-13', '2018-08-14', '2018-08-16', '2018-08-20', '2018-09-03', '2018-09-06', '2018-09-07', '2018-09-12', '2018-09-13', '2018-09-28', '2018-10-04', '2018-10-05', '2018-10-08', '2018-10-10', '2018-10-11', '2018-10-19', '2018-10-24', '2018-10-25', '2018-10-26', '2018-10-29', '2018-11-13', '2018-11-14', '2018-11-15', '2018-11-19', '2018-11-20', '2018-11-21', '2018-11-22', '2018-11-26', '2018-12-05', '2018-12-06', '2018-12-10', '2018-12-12', '2018-12-17', '2018-12-18', '2018-12-19', '2018-12-20', '2018-12-21', '2018-12-24', '2018-12-26', '2019-01-04', '2019-01-15', '2019-01-18', '2019-01-22', '2019-01-23', '2019-02-08', '2019-02-13', '2019-02-14', '2019-02-18', '2019-02-19', '2019-02-22', '2019-02-28', '2019-03-04', '2019-03-05', '2019-03-07', '2019-03-11', '2019-03-12', '2019-03-14', '2019-03-15', '2019-03-18', '2019-03-20', '2019-03-29', '2019-04-03', '2019-04-04', '2019-04-05', '2019-04-10', '2019-04-17', '2019-04-18', '2019-04-19', '2019-04-25', '2019-04-29', '2019-05-14', '2019-05-24', '2019-05-27', '2019-05-28', '2019-05-29', '2019-06-11', '2019-06-17', '2019-06-18', '2019-06-19', '2019-06-20', '2019-06-24', '2019-06-25', '2019-06-26', '2019-07-02', '2019-07-03', '2019-07-17', '2019-07-19', '2019-07-29', '2019-07-31', '2019-08-05', '2019-08-06', '2019-08-27', '2019-08-30', '2019-09-03', '2019-09-04', '2019-09-10', '2019-09-11', '2019-09-24', '2019-09-25', '2019-09-26', '2019-10-01', '2019-10-07', '2019-10-08', '2019-10-11', '2019-10-14', '2019-10-15', '2019-10-16', '2019-10-17', '2019-10-21', '2019-10-22', '2019-10-24', '2019-10-25', '2019-10-28', '2019-10-29', '2019-11-04', '2019-11-07', '2019-11-08', '2019-11-12', '2019-11-14', '2019-11-15', '2019-11-18', '2019-11-21', '2019-11-22', '2019-11-25', '2019-11-26', '2019-11-27', '2019-11-28', '2019-12-02', '2019-12-03', '2019-12-09', '2019-12-10', '2019-12-11', '2019-12-12', '2019-12-13', '2019-12-16', '2019-12-23', '2019-12-24', '2019-12-26', '2019-12-30', '2020-01-07', '2020-01-20', '2020-01-22', '2020-01-28', '2020-02-06', '2020-02-11', '2020-02-12', '2020-02-28', '2020-03-10', '2020-03-17', '2020-03-19', '2021-07-05', '2021-07-06', '2021-07-13', '2021-07-15', '2021-07-20', '2021-07-22', '2021-07-23', '2021-07-27', '2021-07-28', '2021-07-29', '2021-08-02', '2021-08-03', '2021-08-04', '2021-08-05', '2021-08-12', '2021-08-18', '2021-08-20', '2021-08-23', '2021-08-24', '2021-08-27', '2021-08-30', '2021-09-10', '2021-09-13', '2021-09-14', '2021-10-05', '2021-10-07', '2021-10-13', '2021-10-14', '2021-10-15', '2021-10-19', '2021-10-22', '2021-10-25', '2021-10-26', '2021-11-01', '2021-11-02', '2021-11-04', '2021-11-09', '2021-11-12', '2021-11-15', '2021-11-19', '2021-11-22', '2021-11-29', '2021-12-08', '2021-12-13', '2021-12-21', '2021-12-23', '2021-12-24', '2021-12-27', '2021-12-28', '2022-01-12', '2022-01-20', '2022-01-24', '2022-01-28', '2022-02-09', '2022-02-14', '2022-02-15', '2022-02-16', '2022-02-25', '2022-03-03', '2022-03-10', '2022-03-16', '2022-03-17', '2022-03-22', '2022-03-23', '2022-03-29', '2022-03-31', '2022-04-13', '2022-04-19', '2022-04-21', '2022-04-26', '2022-05-10', '2022-05-13', '2022-05-17', '2022-05-20', '2022-05-25', '2022-05-27', '2022-05-30', '2022-06-03', '2022-06-09', '2022-06-14', '2022-06-15', '2022-06-17', '2022-06-20', '2022-06-21', '2022-06-23', '2022-06-24', '2022-07-01', '2022-07-04', '2022-07-05', '2022-07-07', '2022-07-13']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"total case : {tgt_cnt}\\n\")\n",
        "\n",
        "column = ['매수/매도', '승리', '패배', '승률(%)', '패율(%)', '평균수익률(%)', '평균손실률(%)', '기대수익률(%)']\n",
        "\n",
        "print(\"시가 매수 시가 매도\")\n",
        "print(f\"win  : {len(open_open_win)} ({len(open_open_win) / tgt_cnt * 100:.2f}% / {sum(open_open_win)/len(open_open_win):.2f}%)\")\n",
        "print(f\"lose : {len(open_open_lose)} ({len(open_open_lose) / tgt_cnt * 100:.2f}% / {sum(open_open_lose)/len(open_open_lose):.2f}%)\")\n",
        "print(f\"=> {(len(open_open_win) / tgt_cnt) * (sum(open_open_win)/len(open_open_win)) + (len(open_open_lose) / tgt_cnt) * (sum(open_open_lose)/len(open_open_lose)):.2f}%\\n\")\n",
        "\n",
        "open_open = ['시가/시가', len(open_open_win), len(open_open_lose),\n",
        "             f'{len(open_open_win) / tgt_cnt * 100:.2f}', f'{len(open_open_lose) / tgt_cnt * 100:.2f}',\n",
        "             f'{sum(open_open_win)/len(open_open_win):.2f}', f'{sum(open_open_lose)/len(open_open_lose):.2f}',\n",
        "             f'{(len(open_open_win) / tgt_cnt) * (sum(open_open_win)/len(open_open_win)) + (len(open_open_lose) / tgt_cnt) * (sum(open_open_lose)/len(open_open_lose)):.2f}']\n",
        "\n",
        "print(\"시가 매수 종가 매도\")\n",
        "print(f\"win  : {len(open_close_win)} ({len(open_close_win) / tgt_cnt * 100:.2f}% / {sum(open_close_win)/len(open_close_win):.2f}%)\")\n",
        "print(f\"lose : {len(open_close_lose)} ({len(open_close_lose) / tgt_cnt * 100:.2f}% / {sum(open_close_lose)/len(open_close_lose):.2f}%)\")\n",
        "print(f\"=> {(len(open_close_win) / tgt_cnt) * (sum(open_close_win)/len(open_close_win)) + (len(open_close_lose) / tgt_cnt) * (sum(open_close_lose)/len(open_close_lose)):.2f}%\\n\")\n",
        "\n",
        "open_close = ['시가/종가', len(open_close_win), len(open_close_lose),\n",
        "              f'{len(open_close_win) / tgt_cnt * 100:.2f}', f'{len(open_close_lose) / tgt_cnt * 100:.2f}',\n",
        "              f'{sum(open_close_win)/len(open_close_win):.2f}', f'{sum(open_close_lose)/len(open_close_lose):.2f}',\n",
        "              f'{(len(open_close_win) / tgt_cnt) * (sum(open_close_win)/len(open_close_win)) + (len(open_close_lose) / tgt_cnt) * (sum(open_close_lose)/len(open_close_lose)):.2f}']\n",
        "\n",
        "print(\"종가 매수 시가 매도\")\n",
        "print(f\"win  : {len(close_open_win)} ({len(close_open_win) / tgt_cnt * 100:.2f}% / {sum(close_open_win)/len(close_open_win):.2f}%)\")\n",
        "print(f\"lose : {len(close_open_lose)} ({len(close_open_lose) / tgt_cnt * 100:.2f}% / {sum(close_open_lose)/len(close_open_lose):.2f}%)\")\n",
        "print(f\"=> {(len(close_open_win) / tgt_cnt) * (sum(close_open_win)/len(close_open_win)) + (len(close_open_lose) / tgt_cnt) * (sum(close_open_lose)/len(close_open_lose)):.2f}%\\n\")\n",
        "\n",
        "close_open = ['종가/시가', len(close_open_win), len(close_open_lose),\n",
        "              f'{len(close_open_win) / tgt_cnt * 100:.2f}', f'{len(close_open_lose) / tgt_cnt * 100:.2f}',\n",
        "              f'{sum(close_open_win)/len(close_open_win):.2f}', f'{sum(close_open_lose)/len(close_open_lose):.2f}',\n",
        "              f'{(len(close_open_win) / tgt_cnt) * (sum(close_open_win)/len(close_open_win)) + (len(close_open_lose) / tgt_cnt) * (sum(close_open_lose)/len(close_open_lose)):.2f}']\n",
        "\n",
        "print(\"종가 매수 종가 매도\")\n",
        "print(f\"win  : {len(close_close_win)} ({len(close_close_win) / tgt_cnt * 100:.2f}% / {sum(close_close_win)/len(close_close_win):.2f}%)\")\n",
        "print(f\"lose : {len(close_close_lose)} ({len(close_close_lose) / tgt_cnt * 100:.2f}% / {sum(close_close_lose)/len(close_close_lose):.2f}%)\")\n",
        "print(f\"=> {(len(close_close_win) / tgt_cnt) * (sum(close_close_win)/len(close_close_win)) + (len(close_close_lose) / tgt_cnt) * (sum(close_close_lose)/len(close_close_lose)):.2f}%\\n\")\n",
        "\n",
        "close_close = ['종가/시가', len(close_close_win), len(close_close_lose),\n",
        "               f'{len(close_close_win) / tgt_cnt * 100:.2f}', f'{len(close_close_lose) / tgt_cnt * 100:.2f}',\n",
        "               f'{sum(close_close_win)/len(close_close_win):.2f}', f'{sum(close_close_lose)/len(close_close_lose):.2f}',\n",
        "               f'{(len(close_close_win) / tgt_cnt) * (sum(close_close_win)/len(close_close_win)) + (len(close_close_lose) / tgt_cnt) * (sum(close_close_lose)/len(close_close_lose)):.2f}']\n",
        "\n",
        "\n",
        "import pandas as pd\n",
        "data = [open_open, open_close, close_open, close_close]\n",
        "DF = pd.DataFrame(data = data, columns=column)\n",
        "DF"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 635
        },
        "id": "Fgf5fz8IYpVi",
        "outputId": "0aa9cb15-bbc0-41e4-86ce-6f845755ed2d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total case : 350\n",
            "\n",
            "시가 매수 시가 매도\n",
            "win  : 173 (49.43% / 1.93%)\n",
            "lose : 177 (50.57% / -1.32%)\n",
            "=> 0.29%\n",
            "\n",
            "시가 매수 종가 매도\n",
            "win  : 166 (47.43% / 1.47%)\n",
            "lose : 184 (52.57% / -0.79%)\n",
            "=> 0.28%\n",
            "\n",
            "종가 매수 시가 매도\n",
            "win  : 162 (46.29% / 2.25%)\n",
            "lose : 188 (53.71% / -1.58%)\n",
            "=> 0.19%\n",
            "\n",
            "종가 매수 종가 매도\n",
            "win  : 154 (44.00% / 1.97%)\n",
            "lose : 196 (56.00% / -1.23%)\n",
            "=> 0.18%\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   매수/매도   승리   패배  승률(%)  패율(%) 평균수익률(%) 평균손실률(%) 기대수익률(%)\n",
              "0  시가/시가  173  177  49.43  50.57     1.93    -1.32     0.29\n",
              "1  시가/종가  166  184  47.43  52.57     1.47    -0.79     0.28\n",
              "2  종가/시가  162  188  46.29  53.71     2.25    -1.58     0.19\n",
              "3  종가/시가  154  196  44.00  56.00     1.97    -1.23     0.18"
            ],
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              "      <th></th>\n",
              "      <th>매수/매도</th>\n",
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              "      <td>시가/시가</td>\n",
              "      <td>173</td>\n",
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              "      <td>0.29</td>\n",
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              "      <td>52.57</td>\n",
              "      <td>1.47</td>\n",
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              "      <td>0.28</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>종가/시가</td>\n",
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              "      <td>0.19</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>종가/시가</td>\n",
              "      <td>154</td>\n",
              "      <td>196</td>\n",
              "      <td>44.00</td>\n",
              "      <td>56.00</td>\n",
              "      <td>1.97</td>\n",
              "      <td>-1.23</td>\n",
              "      <td>0.18</td>\n",
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              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ee65cbf9-aec5-4d6b-b937-61c8f6a0fdea')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
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              "\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      <script>\n",
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              "          document.querySelector('#df-ee65cbf9-aec5-4d6b-b937-61c8f6a0fdea button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ee65cbf9-aec5-4d6b-b937-61c8f6a0fdea');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "C-oDuM7djXu-"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}