StocksV1.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rushikeshnakhate/A2DataTech/blob/master/StocksV1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uXUpBBnTyqyk",
        "outputId": "9a2dd7fa-547b-4e90-a147-72ebf29c366e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: jugaad_data in /usr/local/lib/python3.10/dist-packages (0.26)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from jugaad_data) (2.31.0)\n",
            "Requirement already satisfied: click==7.1.2 in /usr/local/lib/python3.10/dist-packages (from jugaad_data) (7.1.2)\n",
            "Requirement already satisfied: appdirs==1.4.4 in /usr/local/lib/python3.10/dist-packages (from jugaad_data) (1.4.4)\n",
            "Requirement already satisfied: beautifulsoup4==4.9.3 in /usr/local/lib/python3.10/dist-packages (from jugaad_data) (4.9.3)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4==4.9.3->jugaad_data) (2.5)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->jugaad_data) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->jugaad_data) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->jugaad_data) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->jugaad_data) (2023.11.17)\n"
          ]
        }
      ],
      "source": [
        "pip install jugaad_data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {
        "id": "EC6c_AJ-ytj1"
      },
      "outputs": [],
      "source": [
        "from pathlib import Path\n",
        "from datetime import date\n",
        "from jugaad_data.nse import NSELive\n",
        "from jugaad_data.nse import bhavcopy_save\n",
        "import pandas as pd\n",
        "output_dir = Path(\"/content/sample_data\")\n",
        "import os"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "metadata": {
        "id": "0YOwgLpkUzP_"
      },
      "outputs": [],
      "source": [
        "def validate_required_args(kwargs, *required_args):\n",
        "    for arg in required_args:\n",
        "        if arg not in kwargs:\n",
        "            raise ValueError(f\"Error: '{arg}' argument not provided, actual received: {kwargs}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "metadata": {
        "id": "nkmusvtt0g48"
      },
      "outputs": [],
      "source": [
        "import pickle\n",
        "\n",
        "def load_or_download_and_cache_data(download_function:callable,**kwargs):\n",
        "  validate_required_args(kwargs, 'cache_file')\n",
        "  cache_file : str = kwargs.get(\"cache_file\")\n",
        "\n",
        "  if os.path.exists(cache_file):\n",
        "    with open(cache_file,'rb') as file:\n",
        "      return pickle.load(file)\n",
        "\n",
        "  data_df = download_function(**kwargs)\n",
        "  # if not data_df.empty:\n",
        "  with open(cache_file,'wb') as file:\n",
        "    pickle.dump(data_df,file)\n",
        "  return data_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "metadata": {
        "id": "7_QFgxMO2H3F"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "def download_bhavcopy(**kwargs):\n",
        "  \"\"\"\n",
        "  # bhavcopy_save: Generates a CSV file with a random name.\n",
        "  # The expected name for the downloaded Bhavcopy file is \"bhavcopy_${start_date}.csv\".\n",
        "  # The cache file is named as \"bhavcopy_${start_date}.pkl\". A renaming process is required.\n",
        "  \"\"\"\n",
        "  validate_required_args(kwargs, 'cache_file','start_date')\n",
        "  cache_file: str = kwargs.get(\"cache_file\")\n",
        "  start_date : date= kwargs.get(\"start_date\")\n",
        "\n",
        "  generated_csv_filename = bhavcopy_save(start_date, output_dir)\n",
        "  cache_file_to_csv_name = cache_file.with_suffix(\".csv\")\n",
        "  os.rename(generated_csv_filename,cache_file_to_csv_name)\n",
        "  return pd.read_csv(cache_file_to_csv_name)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "metadata": {
        "id": "H6qU7vuFyx58"
      },
      "outputs": [],
      "source": [
        "def fetch_or_genenate_stocks(start_date: date):\n",
        "  output_file  = Path(output_dir)/(\"NseData_\" + str(start_date) +\".pkl\")\n",
        "  return load_or_download_and_cache_data(download_bhavcopy,start_date= start_date,cache_file=output_file)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "metadata": {
        "id": "2kVqnLN-6roX"
      },
      "outputs": [],
      "source": [
        "import yfinance as yf\n",
        "import concurrent.futures\n",
        "import threading\n",
        "\n",
        "def populate_sector(tick: str):\n",
        "  tick_ = tick + \".NS\"\n",
        "  try:\n",
        "    ticker = yf.Ticker(tick_)\n",
        "    # print(\"populate_sector sector for sym={}\".format(tick))\n",
        "    return ticker.info['sector']\n",
        "  except Exception as e:\n",
        "    return \"NOT_FOUND_ON_YAHOO\"\n",
        "\n",
        "\n",
        "def download_sectors(**kwargs):\n",
        "  validate_required_args(kwargs, 'stocks')\n",
        "  stocks_df : pd.Dataframe = kwargs.get('stocks')\n",
        "  new_data = []\n",
        "  for symbol in stocks_df['SYMBOL']:\n",
        "      sector = populate_sector(symbol)\n",
        "      new_data.append((symbol, sector))\n",
        "  return pd.DataFrame(new_data, columns=['SYMBOL', 'SECTOR'])\n",
        "\n",
        "\n",
        "# lock = threading.Lock()  # Create a lock for thread safety\n",
        "# results = {}  # Use a dictionary to store results with symbol as key\n",
        "# def process_stock(symbol):\n",
        "#   # Acquire the lock to prevent race conditions\n",
        "#   with lock:\n",
        "#     sector = populate_sector(symbol)\n",
        "#     results[symbol] = sector\n",
        "\n",
        "# def download_sectors_concurrently(**kwargs):\n",
        "#   validate_required_args(kwargs, 'stocks')\n",
        "#   stocks_df : pd.Dataframe = kwargs.get('stocks')\n",
        "#   with concurrent.futures.ThreadPoolExecutor() as executor:\n",
        "#       executor.map(process_stock, stocks_df['SYMBOL'].tolist())\n",
        "#   dd1 = pd.DataFrame(results)\n",
        "#   print(\"00000000000000000\")\n",
        "#   display(dd1)\n",
        "#   print(\"00000000000000000\")\n",
        "#   return dd1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "metadata": {
        "id": "Vle8c-Wx6GkI"
      },
      "outputs": [],
      "source": [
        "# def fetch_or_generate_sector_to_stocks(stocks : pd.DataFrame):\n",
        "#   output_file  = Path(output_dir)/(\"Sectors.pkl\")\n",
        "#   stocks_to_sector_map_df = load_or_download_and_cache_data(download_sectors,cache_file=output_file,stocks=stocks)\n",
        "#   dd =  pd.merge(stocks, stocks_to_sector_map_df, on='SYMBOL', how='inner',suffixes=('', ''))\n",
        "#   if dd.empty:\n",
        "#     raise ValueError(\"Error: The DataFrame is empty.\")\n",
        "#   return dd\n",
        "\n",
        "\n",
        "def fetch_or_generate_sector_to_stocks(stocks : pd.DataFrame):\n",
        "  output_file  = Path(output_dir)/(\"Sectors.pkl\")\n",
        "  stocks_to_sector_map_df = load_or_download_and_cache_data(download_sectors,cache_file=output_file,stocks=stocks)\n",
        "  # display(stocks_to_sector_map_df)\n",
        "  try:\n",
        "   return pd.merge(stocks, stocks_to_sector_map_df, on='SYMBOL', how='inner',suffixes=('', ''))\n",
        "  except pd.errors.MergeError as e:\n",
        "    print(f\"Merge failed: {e}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "metadata": {
        "id": "IOVvS3Qlc5uP"
      },
      "outputs": [],
      "source": [
        "def calculate_performace(stocks_df : pd.DataFrame, start_date: date):\n",
        "    # Calculate daily returns\n",
        "  print(\"calculate_performace for date={}\".format(start_date))\n",
        "  stocks_df['DAILY_RETURN'] =(stocks_df['CLOSE'] - stocks_df['OPEN'])/ stocks_df['OPEN']\n",
        "\n",
        "  # Group by 'SECTOR' and calculate average daily return and volatility\n",
        "  sector_performance_df = stocks_df.groupby('SECTOR').agg({\n",
        "      # stocks_list=('STOCK', lambda x: list(x))\n",
        "      'DAILY_RETURN': ['std','mean','count']\n",
        "  }).reset_index()\n",
        "\n",
        "  sector_performance_df[\"TRADEDATE\"] = start_date\n",
        "\n",
        "  # Flatten the column names, but only for columns where the second part is not an empty string\n",
        "  sector_performance_df.columns = [\n",
        "      f\"{col[0]}_{col[1]}\" if col[1] else col[0] for col in sector_performance_df.columns\n",
        "  ]\n",
        "  return sector_performance_df\n",
        "\n",
        "\n",
        "def prepare_stocks_data_and_calculate_performance(**kwargs):\n",
        "  try:\n",
        "    validate_required_args(kwargs, 'start_date')\n",
        "    start_date : date = kwargs.get('start_date')\n",
        "    stocks_df = fetch_or_genenate_stocks(start_date)\n",
        "    stocks_df_with_sector = fetch_or_generate_sector_to_stocks(stocks_df)\n",
        "    return calculate_performace(stocks_df_with_sector,start_date)\n",
        "  except ValueError as e:\n",
        "    print(e)\n",
        "\n",
        "def fetch_or_generate_performance_for_stocks(start_date:date):\n",
        "  sector_performance_output_file = Path(output_dir)/(\"SectorPeformance_\" + str(start_date) +\".pkl\")\n",
        "  return load_or_download_and_cache_data(prepare_stocks_data_and_calculate_performance,start_date=start_date,cache_file=sector_performance_output_file)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1842
        },
        "id": "LRgLRW2ky0WU",
        "outputId": "5f40506e-fb0d-41de-cb25-86bac3fc4248"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                    SECTOR  DAILY_RETURN_std  DAILY_RETURN_mean  \\\n",
              "0          Basic Materials          0.022636           0.000140   \n",
              "1   Communication Services          0.030817          -0.000281   \n",
              "2        Consumer Cyclical          0.025206           0.001927   \n",
              "3       Consumer Defensive          0.020967          -0.002440   \n",
              "4                   Energy          0.019827           0.003527   \n",
              "5       Financial Services          0.014939          -0.001455   \n",
              "6               Healthcare          0.019838           0.002678   \n",
              "7              Industrials          0.023680           0.001736   \n",
              "8       NOT_FOUND_ON_YAHOO          0.024667           0.001650   \n",
              "9              Real Estate          0.031887           0.009497   \n",
              "10              Technology          0.028230           0.001053   \n",
              "11               Utilities          0.017422          -0.002500   \n",
              "\n",
              "    DAILY_RETURN_count   TRADEDATE  \n",
              "0                  330  2024-01-18  \n",
              "1                   73  2024-01-18  \n",
              "2                  373  2024-01-18  \n",
              "3                  142  2024-01-18  \n",
              "4                   35  2024-01-18  \n",
              "5                 1024  2024-01-18  \n",
              "6                  129  2024-01-18  \n",
              "7                  388  2024-01-18  \n",
              "8                  821  2024-01-18  \n",
              "9                   64  2024-01-18  \n",
              "10                 144  2024-01-18  \n",
              "11                  64  2024-01-18  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9d67076b-aa1c-4e92-9491-25812fa7d657\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SECTOR</th>\n",
              "      <th>DAILY_RETURN_std</th>\n",
              "      <th>DAILY_RETURN_mean</th>\n",
              "      <th>DAILY_RETURN_count</th>\n",
              "      <th>TRADEDATE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Basic Materials</td>\n",
              "      <td>0.022636</td>\n",
              "      <td>0.000140</td>\n",
              "      <td>330</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Communication Services</td>\n",
              "      <td>0.030817</td>\n",
              "      <td>-0.000281</td>\n",
              "      <td>73</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Consumer Cyclical</td>\n",
              "      <td>0.025206</td>\n",
              "      <td>0.001927</td>\n",
              "      <td>373</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Consumer Defensive</td>\n",
              "      <td>0.020967</td>\n",
              "      <td>-0.002440</td>\n",
              "      <td>142</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Energy</td>\n",
              "      <td>0.019827</td>\n",
              "      <td>0.003527</td>\n",
              "      <td>35</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Financial Services</td>\n",
              "      <td>0.014939</td>\n",
              "      <td>-0.001455</td>\n",
              "      <td>1024</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Healthcare</td>\n",
              "      <td>0.019838</td>\n",
              "      <td>0.002678</td>\n",
              "      <td>129</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Industrials</td>\n",
              "      <td>0.023680</td>\n",
              "      <td>0.001736</td>\n",
              "      <td>388</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>NOT_FOUND_ON_YAHOO</td>\n",
              "      <td>0.024667</td>\n",
              "      <td>0.001650</td>\n",
              "      <td>821</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Real Estate</td>\n",
              "      <td>0.031887</td>\n",
              "      <td>0.009497</td>\n",
              "      <td>64</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Technology</td>\n",
              "      <td>0.028230</td>\n",
              "      <td>0.001053</td>\n",
              "      <td>144</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Utilities</td>\n",
              "      <td>0.017422</td>\n",
              "      <td>-0.002500</td>\n",
              "      <td>64</td>\n",
              "      <td>2024-01-18</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9d67076b-aa1c-4e92-9491-25812fa7d657')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-9d67076b-aa1c-4e92-9491-25812fa7d657 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-9d67076b-aa1c-4e92-9491-25812fa7d657');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-6326c9c9-bf4b-473b-af6e-60996573c8ea\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6326c9c9-bf4b-473b-af6e-60996573c8ea')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6326c9c9-bf4b-473b-af6e-60996573c8ea button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_9ea067c3-60a0-4418-94ce-14609ba796f0\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_9ea067c3-60a0-4418-94ce-14609ba796f0 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[{\n            'v': 0,\n            'f': \"0\",\n        },\n\"Basic Materials\",\n{\n            'v': 0.022636032390057077,\n            'f': \"0.022636032390057077\",\n        },\n{\n            'v': 0.00013964600683210224,\n            'f': \"0.00013964600683210224\",\n        },\n{\n            'v': 330,\n            'f': \"330\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 1,\n            'f': \"1\",\n        },\n\"Communication Services\",\n{\n            'v': 0.030817476064185192,\n            'f': \"0.030817476064185192\",\n        },\n{\n            'v': -0.0002813483331722399,\n            'f': \"-0.0002813483331722399\",\n        },\n{\n            'v': 73,\n            'f': \"73\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 2,\n            'f': \"2\",\n        },\n\"Consumer Cyclical\",\n{\n            'v': 0.025205901993810186,\n            'f': \"0.025205901993810186\",\n        },\n{\n            'v': 0.0019273681474257108,\n            'f': \"0.0019273681474257108\",\n        },\n{\n            'v': 373,\n            'f': \"373\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 3,\n            'f': \"3\",\n        },\n\"Consumer Defensive\",\n{\n            'v': 0.020966522564835142,\n            'f': \"0.020966522564835142\",\n        },\n{\n            'v': -0.00244000285232926,\n            'f': \"-0.00244000285232926\",\n        },\n{\n            'v': 142,\n            'f': \"142\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 4,\n            'f': \"4\",\n        },\n\"Energy\",\n{\n            'v': 0.0198269228203616,\n            'f': \"0.0198269228203616\",\n        },\n{\n            'v': 0.0035268138665766123,\n            'f': \"0.0035268138665766123\",\n        },\n{\n            'v': 35,\n            'f': \"35\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 5,\n            'f': \"5\",\n        },\n\"Financial Services\",\n{\n            'v': 0.014939490476532221,\n            'f': \"0.014939490476532221\",\n        },\n{\n            'v': -0.00145507000096097,\n            'f': \"-0.00145507000096097\",\n        },\n{\n            'v': 1024,\n            'f': \"1024\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 6,\n            'f': \"6\",\n        },\n\"Healthcare\",\n{\n            'v': 0.019838057542222887,\n            'f': \"0.019838057542222887\",\n        },\n{\n            'v': 0.0026776970348916613,\n            'f': \"0.0026776970348916613\",\n        },\n{\n            'v': 129,\n            'f': \"129\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 7,\n            'f': \"7\",\n        },\n\"Industrials\",\n{\n            'v': 0.023680293902252018,\n            'f': \"0.023680293902252018\",\n        },\n{\n            'v': 0.0017357383720426971,\n            'f': \"0.0017357383720426971\",\n        },\n{\n            'v': 388,\n            'f': \"388\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 8,\n            'f': \"8\",\n        },\n\"NOT_FOUND_ON_YAHOO\",\n{\n            'v': 0.024666981898649357,\n            'f': \"0.024666981898649357\",\n        },\n{\n            'v': 0.0016501138812062674,\n            'f': \"0.0016501138812062674\",\n        },\n{\n            'v': 821,\n            'f': \"821\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 9,\n            'f': \"9\",\n        },\n\"Real Estate\",\n{\n            'v': 0.03188709836975684,\n            'f': \"0.03188709836975684\",\n        },\n{\n            'v': 0.009496821349253148,\n            'f': \"0.009496821349253148\",\n        },\n{\n            'v': 64,\n            'f': \"64\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 10,\n            'f': \"10\",\n        },\n\"Technology\",\n{\n            'v': 0.028230143835524826,\n            'f': \"0.028230143835524826\",\n        },\n{\n            'v': 0.0010532019843950983,\n            'f': \"0.0010532019843950983\",\n        },\n{\n            'v': 144,\n            'f': \"144\",\n        },\n\"2024-01-18\"],\n [{\n            'v': 11,\n            'f': \"11\",\n        },\n\"Utilities\",\n{\n            'v': 0.017422155316419493,\n            'f': \"0.017422155316419493\",\n        },\n{\n            'v': -0.002500017808693627,\n            'f': \"-0.002500017808693627\",\n        },\n{\n            'v': 64,\n            'f': \"64\",\n        },\n\"2024-01-18\"]],\n        columns: [[\"number\", \"index\"], [\"string\", \"SECTOR\"], [\"number\", \"DAILY_RETURN_std\"], [\"number\", \"DAILY_RETURN_mean\"], [\"number\", \"DAILY_RETURN_count\"], [\"string\", \"TRADEDATE\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n        quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-12c53299-8312-4f2d-a9d5-a9bfc35baf5a\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-12c53299-8312-4f2d-a9d5-a9bfc35baf5a')\"\n            title=\"Suggest charts\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-12c53299-8312-4f2d-a9d5-a9bfc35baf5a button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                    SECTOR  DAILY_RETURN_std  DAILY_RETURN_mean  \\\n",
              "0          Basic Materials          0.022535          -0.005132   \n",
              "1   Communication Services          0.038691           0.005711   \n",
              "2        Consumer Cyclical          0.022766          -0.004004   \n",
              "3       Consumer Defensive          0.026868          -0.000433   \n",
              "4                   Energy          0.014955           0.000888   \n",
              "5       Financial Services          0.016230          -0.000103   \n",
              "6               Healthcare          0.016931          -0.004468   \n",
              "7              Industrials          0.023632           0.001193   \n",
              "8       NOT_FOUND_ON_YAHOO          0.021942          -0.001196   \n",
              "9              Real Estate          0.030142           0.003197   \n",
              "10              Technology          0.024115           0.005173   \n",
              "11               Utilities          0.020562           0.002418   \n",
              "\n",
              "    DAILY_RETURN_count   TRADEDATE  \n",
              "0                  334  2024-01-17  \n",
              "1                   73  2024-01-17  \n",
              "2                  375  2024-01-17  \n",
              "3                  142  2024-01-17  \n",
              "4                   35  2024-01-17  \n",
              "5                 1082  2024-01-17  \n",
              "6                  129  2024-01-17  \n",
              "7                  388  2024-01-17  \n",
              "8                  867  2024-01-17  \n",
              "9                   64  2024-01-17  \n",
              "10                 142  2024-01-17  \n",
              "11                  62  2024-01-17  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e78cfc23-ecfe-48fb-bfeb-63406e221c7e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SECTOR</th>\n",
              "      <th>DAILY_RETURN_std</th>\n",
              "      <th>DAILY_RETURN_mean</th>\n",
              "      <th>DAILY_RETURN_count</th>\n",
              "      <th>TRADEDATE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Basic Materials</td>\n",
              "      <td>0.022535</td>\n",
              "      <td>-0.005132</td>\n",
              "      <td>334</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Communication Services</td>\n",
              "      <td>0.038691</td>\n",
              "      <td>0.005711</td>\n",
              "      <td>73</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Consumer Cyclical</td>\n",
              "      <td>0.022766</td>\n",
              "      <td>-0.004004</td>\n",
              "      <td>375</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Consumer Defensive</td>\n",
              "      <td>0.026868</td>\n",
              "      <td>-0.000433</td>\n",
              "      <td>142</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Energy</td>\n",
              "      <td>0.014955</td>\n",
              "      <td>0.000888</td>\n",
              "      <td>35</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Financial Services</td>\n",
              "      <td>0.016230</td>\n",
              "      <td>-0.000103</td>\n",
              "      <td>1082</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Healthcare</td>\n",
              "      <td>0.016931</td>\n",
              "      <td>-0.004468</td>\n",
              "      <td>129</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Industrials</td>\n",
              "      <td>0.023632</td>\n",
              "      <td>0.001193</td>\n",
              "      <td>388</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>NOT_FOUND_ON_YAHOO</td>\n",
              "      <td>0.021942</td>\n",
              "      <td>-0.001196</td>\n",
              "      <td>867</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Real Estate</td>\n",
              "      <td>0.030142</td>\n",
              "      <td>0.003197</td>\n",
              "      <td>64</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Technology</td>\n",
              "      <td>0.024115</td>\n",
              "      <td>0.005173</td>\n",
              "      <td>142</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Utilities</td>\n",
              "      <td>0.020562</td>\n",
              "      <td>0.002418</td>\n",
              "      <td>62</td>\n",
              "      <td>2024-01-17</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e78cfc23-ecfe-48fb-bfeb-63406e221c7e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e78cfc23-ecfe-48fb-bfeb-63406e221c7e 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-e78cfc23-ecfe-48fb-bfeb-63406e221c7e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-93ea916e-ea34-4ae9-8647-03ee8ebfe676\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-93ea916e-ea34-4ae9-8647-03ee8ebfe676')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-93ea916e-ea34-4ae9-8647-03ee8ebfe676 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_7d8b8211-ea3e-4714-9709-fd6b7b67fdaf\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_7d8b8211-ea3e-4714-9709-fd6b7b67fdaf button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[{\n            'v': 0,\n            'f': \"0\",\n        },\n\"Basic Materials\",\n{\n            'v': 0.022534529867294262,\n            'f': \"0.022534529867294262\",\n        },\n{\n            'v': -0.005132089130245453,\n            'f': \"-0.005132089130245453\",\n        },\n{\n            'v': 334,\n            'f': \"334\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 1,\n            'f': \"1\",\n        },\n\"Communication Services\",\n{\n            'v': 0.03869067660173679,\n            'f': \"0.03869067660173679\",\n        },\n{\n            'v': 0.005711245225627298,\n            'f': \"0.005711245225627298\",\n        },\n{\n            'v': 73,\n            'f': \"73\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 2,\n            'f': \"2\",\n        },\n\"Consumer Cyclical\",\n{\n            'v': 0.022765598222102036,\n            'f': \"0.022765598222102036\",\n        },\n{\n            'v': -0.004004455676731022,\n            'f': \"-0.004004455676731022\",\n        },\n{\n            'v': 375,\n            'f': \"375\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 3,\n            'f': \"3\",\n        },\n\"Consumer Defensive\",\n{\n            'v': 0.026868401798357342,\n            'f': \"0.026868401798357342\",\n        },\n{\n            'v': -0.0004332522285571249,\n            'f': \"-0.0004332522285571249\",\n        },\n{\n            'v': 142,\n            'f': \"142\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 4,\n            'f': \"4\",\n        },\n\"Energy\",\n{\n            'v': 0.014955394929569075,\n            'f': \"0.014955394929569075\",\n        },\n{\n            'v': 0.0008882613099329646,\n            'f': \"0.0008882613099329646\",\n        },\n{\n            'v': 35,\n            'f': \"35\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 5,\n            'f': \"5\",\n        },\n\"Financial Services\",\n{\n            'v': 0.016230411776075516,\n            'f': \"0.016230411776075516\",\n        },\n{\n            'v': -0.00010325353468154068,\n            'f': \"-0.00010325353468154068\",\n        },\n{\n            'v': 1082,\n            'f': \"1082\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 6,\n            'f': \"6\",\n        },\n\"Healthcare\",\n{\n            'v': 0.016930958858714942,\n            'f': \"0.016930958858714942\",\n        },\n{\n            'v': -0.00446779191710382,\n            'f': \"-0.00446779191710382\",\n        },\n{\n            'v': 129,\n            'f': \"129\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 7,\n            'f': \"7\",\n        },\n\"Industrials\",\n{\n            'v': 0.02363246399427875,\n            'f': \"0.02363246399427875\",\n        },\n{\n            'v': 0.0011927739454980976,\n            'f': \"0.0011927739454980976\",\n        },\n{\n            'v': 388,\n            'f': \"388\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 8,\n            'f': \"8\",\n        },\n\"NOT_FOUND_ON_YAHOO\",\n{\n            'v': 0.02194244144486302,\n            'f': \"0.02194244144486302\",\n        },\n{\n            'v': -0.0011958777130973194,\n            'f': \"-0.0011958777130973194\",\n        },\n{\n            'v': 867,\n            'f': \"867\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 9,\n            'f': \"9\",\n        },\n\"Real Estate\",\n{\n            'v': 0.03014174782645929,\n            'f': \"0.03014174782645929\",\n        },\n{\n            'v': 0.0031965228764806123,\n            'f': \"0.0031965228764806123\",\n        },\n{\n            'v': 64,\n            'f': \"64\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 10,\n            'f': \"10\",\n        },\n\"Technology\",\n{\n            'v': 0.024115049042760132,\n            'f': \"0.024115049042760132\",\n        },\n{\n            'v': 0.005172750396340807,\n            'f': \"0.005172750396340807\",\n        },\n{\n            'v': 142,\n            'f': \"142\",\n        },\n\"2024-01-17\"],\n [{\n            'v': 11,\n            'f': \"11\",\n        },\n\"Utilities\",\n{\n            'v': 0.020562185401572706,\n            'f': \"0.020562185401572706\",\n        },\n{\n            'v': 0.0024176709314246416,\n            'f': \"0.0024176709314246416\",\n        },\n{\n            'v': 62,\n            'f': \"62\",\n        },\n\"2024-01-17\"]],\n        columns: [[\"number\", \"index\"], [\"string\", \"SECTOR\"], [\"number\", \"DAILY_RETURN_std\"], [\"number\", \"DAILY_RETURN_mean\"], [\"number\", \"DAILY_RETURN_count\"], [\"string\", \"TRADEDATE\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n        quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-2257aa33-29f6-4af0-a185-44abc93243c5\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2257aa33-29f6-4af0-a185-44abc93243c5')\"\n            title=\"Suggest charts\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-2257aa33-29f6-4af0-a185-44abc93243c5 button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                    SECTOR  DAILY_RETURN_std  DAILY_RETURN_mean  \\\n",
              "0          Basic Materials          0.022732          -0.010494   \n",
              "1   Communication Services          0.023743          -0.015012   \n",
              "2        Consumer Cyclical          0.024568          -0.014766   \n",
              "3       Consumer Defensive          0.024344          -0.009650   \n",
              "4                   Energy          0.021318          -0.006440   \n",
              "5       Financial Services          0.014802          -0.003482   \n",
              "6               Healthcare          0.023780          -0.009749   \n",
              "7              Industrials          0.024232          -0.012569   \n",
              "8       NOT_FOUND_ON_YAHOO          0.020521          -0.006008   \n",
              "9              Real Estate          0.026426          -0.019248   \n",
              "10              Technology          0.030656          -0.015790   \n",
              "11               Utilities          0.017191          -0.009494   \n",
              "\n",
              "    DAILY_RETURN_count   TRADEDATE  \n",
              "0                  330  2024-01-16  \n",
              "1                   73  2024-01-16  \n",
              "2                  373  2024-01-16  \n",
              "3                  142  2024-01-16  \n",
              "4                   36  2024-01-16  \n",
              "5                  978  2024-01-16  \n",
              "6                  129  2024-01-16  \n",
              "7                  388  2024-01-16  \n",
              "8                  829  2024-01-16  \n",
              "9                   64  2024-01-16  \n",
              "10                 142  2024-01-16  \n",
              "11                  69  2024-01-16  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9c4715a2-3e89-4071-9d2a-c0c961b1fa7c\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SECTOR</th>\n",
              "      <th>DAILY_RETURN_std</th>\n",
              "      <th>DAILY_RETURN_mean</th>\n",
              "      <th>DAILY_RETURN_count</th>\n",
              "      <th>TRADEDATE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Basic Materials</td>\n",
              "      <td>0.022732</td>\n",
              "      <td>-0.010494</td>\n",
              "      <td>330</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Communication Services</td>\n",
              "      <td>0.023743</td>\n",
              "      <td>-0.015012</td>\n",
              "      <td>73</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Consumer Cyclical</td>\n",
              "      <td>0.024568</td>\n",
              "      <td>-0.014766</td>\n",
              "      <td>373</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Consumer Defensive</td>\n",
              "      <td>0.024344</td>\n",
              "      <td>-0.009650</td>\n",
              "      <td>142</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Energy</td>\n",
              "      <td>0.021318</td>\n",
              "      <td>-0.006440</td>\n",
              "      <td>36</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Financial Services</td>\n",
              "      <td>0.014802</td>\n",
              "      <td>-0.003482</td>\n",
              "      <td>978</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Healthcare</td>\n",
              "      <td>0.023780</td>\n",
              "      <td>-0.009749</td>\n",
              "      <td>129</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Industrials</td>\n",
              "      <td>0.024232</td>\n",
              "      <td>-0.012569</td>\n",
              "      <td>388</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>NOT_FOUND_ON_YAHOO</td>\n",
              "      <td>0.020521</td>\n",
              "      <td>-0.006008</td>\n",
              "      <td>829</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Real Estate</td>\n",
              "      <td>0.026426</td>\n",
              "      <td>-0.019248</td>\n",
              "      <td>64</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Technology</td>\n",
              "      <td>0.030656</td>\n",
              "      <td>-0.015790</td>\n",
              "      <td>142</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Utilities</td>\n",
              "      <td>0.017191</td>\n",
              "      <td>-0.009494</td>\n",
              "      <td>69</td>\n",
              "      <td>2024-01-16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9c4715a2-3e89-4071-9d2a-c0c961b1fa7c')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-9c4715a2-3e89-4071-9d2a-c0c961b1fa7c 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-9c4715a2-3e89-4071-9d2a-c0c961b1fa7c');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-76f31d70-1fe3-45d4-a56c-db478078f906\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-76f31d70-1fe3-45d4-a56c-db478078f906')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-76f31d70-1fe3-45d4-a56c-db478078f906 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_abeecefc-c3b7-4381-ba49-1741fafae24c\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_abeecefc-c3b7-4381-ba49-1741fafae24c button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[{\n            'v': 0,\n            'f': \"0\",\n        },\n\"Basic Materials\",\n{\n            'v': 0.022731936122686584,\n            'f': \"0.022731936122686584\",\n        },\n{\n            'v': -0.010493654228210457,\n            'f': \"-0.010493654228210457\",\n        },\n{\n            'v': 330,\n            'f': \"330\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 1,\n            'f': \"1\",\n        },\n\"Communication Services\",\n{\n            'v': 0.023743167676940242,\n            'f': \"0.023743167676940242\",\n        },\n{\n            'v': -0.01501188763589642,\n            'f': \"-0.01501188763589642\",\n        },\n{\n            'v': 73,\n            'f': \"73\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 2,\n            'f': \"2\",\n        },\n\"Consumer Cyclical\",\n{\n            'v': 0.0245679296353221,\n            'f': \"0.0245679296353221\",\n        },\n{\n            'v': -0.014766440820542544,\n            'f': \"-0.014766440820542544\",\n        },\n{\n            'v': 373,\n            'f': \"373\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 3,\n            'f': \"3\",\n        },\n\"Consumer Defensive\",\n{\n            'v': 0.02434390242890724,\n            'f': \"0.02434390242890724\",\n        },\n{\n            'v': -0.009650340823441149,\n            'f': \"-0.009650340823441149\",\n        },\n{\n            'v': 142,\n            'f': \"142\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 4,\n            'f': \"4\",\n        },\n\"Energy\",\n{\n            'v': 0.02131755943480883,\n            'f': \"0.02131755943480883\",\n        },\n{\n            'v': -0.006439683398316957,\n            'f': \"-0.006439683398316957\",\n        },\n{\n            'v': 36,\n            'f': \"36\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 5,\n            'f': \"5\",\n        },\n\"Financial Services\",\n{\n            'v': 0.014802167745341897,\n            'f': \"0.014802167745341897\",\n        },\n{\n            'v': -0.003481639718489421,\n            'f': \"-0.003481639718489421\",\n        },\n{\n            'v': 978,\n            'f': \"978\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 6,\n            'f': \"6\",\n        },\n\"Healthcare\",\n{\n            'v': 0.023780066478402685,\n            'f': \"0.023780066478402685\",\n        },\n{\n            'v': -0.009749271614557548,\n            'f': \"-0.009749271614557548\",\n        },\n{\n            'v': 129,\n            'f': \"129\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 7,\n            'f': \"7\",\n        },\n\"Industrials\",\n{\n            'v': 0.02423241230205779,\n            'f': \"0.02423241230205779\",\n        },\n{\n            'v': -0.012569028039340721,\n            'f': \"-0.012569028039340721\",\n        },\n{\n            'v': 388,\n            'f': \"388\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 8,\n            'f': \"8\",\n        },\n\"NOT_FOUND_ON_YAHOO\",\n{\n            'v': 0.020521135831704333,\n            'f': \"0.020521135831704333\",\n        },\n{\n            'v': -0.006007929131080313,\n            'f': \"-0.006007929131080313\",\n        },\n{\n            'v': 829,\n            'f': \"829\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 9,\n            'f': \"9\",\n        },\n\"Real Estate\",\n{\n            'v': 0.02642577361342912,\n            'f': \"0.02642577361342912\",\n        },\n{\n            'v': -0.019247518305410494,\n            'f': \"-0.019247518305410494\",\n        },\n{\n            'v': 64,\n            'f': \"64\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 10,\n            'f': \"10\",\n        },\n\"Technology\",\n{\n            'v': 0.030655708045966856,\n            'f': \"0.030655708045966856\",\n        },\n{\n            'v': -0.01579032198453339,\n            'f': \"-0.01579032198453339\",\n        },\n{\n            'v': 142,\n            'f': \"142\",\n        },\n\"2024-01-16\"],\n [{\n            'v': 11,\n            'f': \"11\",\n        },\n\"Utilities\",\n{\n            'v': 0.017190548723163106,\n            'f': \"0.017190548723163106\",\n        },\n{\n            'v': -0.009494143183326172,\n            'f': \"-0.009494143183326172\",\n        },\n{\n            'v': 69,\n            'f': \"69\",\n        },\n\"2024-01-16\"]],\n        columns: [[\"number\", \"index\"], [\"string\", \"SECTOR\"], [\"number\", \"DAILY_RETURN_std\"], [\"number\", \"DAILY_RETURN_mean\"], [\"number\", \"DAILY_RETURN_count\"], [\"string\", \"TRADEDATE\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n        quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-74cc89c7-659a-4bde-b177-2709fa6c7130\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-74cc89c7-659a-4bde-b177-2709fa6c7130')\"\n            title=\"Suggest charts\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-74cc89c7-659a-4bde-b177-2709fa6c7130 button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                    SECTOR  DAILY_RETURN_std  DAILY_RETURN_mean  \\\n",
              "0          Basic Materials          0.029695          -0.001037   \n",
              "1   Communication Services          0.029421          -0.009211   \n",
              "2        Consumer Cyclical          0.027972          -0.006130   \n",
              "3       Consumer Defensive          0.027551          -0.013983   \n",
              "4                   Energy          0.020202           0.000117   \n",
              "5       Financial Services          0.041982           0.003275   \n",
              "6               Healthcare          0.021771          -0.006409   \n",
              "7              Industrials          0.029880          -0.004145   \n",
              "8       NOT_FOUND_ON_YAHOO          0.021959          -0.001395   \n",
              "9              Real Estate          0.032541           0.002002   \n",
              "10              Technology          0.030162          -0.004683   \n",
              "11               Utilities          0.018176          -0.001370   \n",
              "\n",
              "    DAILY_RETURN_count   TRADEDATE  \n",
              "0                  332  2024-01-15  \n",
              "1                   73  2024-01-15  \n",
              "2                  374  2024-01-15  \n",
              "3                  142  2024-01-15  \n",
              "4                   35  2024-01-15  \n",
              "5                 1113  2024-01-15  \n",
              "6                  129  2024-01-15  \n",
              "7                  387  2024-01-15  \n",
              "8                  830  2024-01-15  \n",
              "9                   64  2024-01-15  \n",
              "10                 143  2024-01-15  \n",
              "11                  66  2024-01-15  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-11b64b7c-5d34-4368-bba2-35a93a8405c0\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SECTOR</th>\n",
              "      <th>DAILY_RETURN_std</th>\n",
              "      <th>DAILY_RETURN_mean</th>\n",
              "      <th>DAILY_RETURN_count</th>\n",
              "      <th>TRADEDATE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Basic Materials</td>\n",
              "      <td>0.029695</td>\n",
              "      <td>-0.001037</td>\n",
              "      <td>332</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Communication Services</td>\n",
              "      <td>0.029421</td>\n",
              "      <td>-0.009211</td>\n",
              "      <td>73</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Consumer Cyclical</td>\n",
              "      <td>0.027972</td>\n",
              "      <td>-0.006130</td>\n",
              "      <td>374</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Consumer Defensive</td>\n",
              "      <td>0.027551</td>\n",
              "      <td>-0.013983</td>\n",
              "      <td>142</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Energy</td>\n",
              "      <td>0.020202</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>35</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Financial Services</td>\n",
              "      <td>0.041982</td>\n",
              "      <td>0.003275</td>\n",
              "      <td>1113</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Healthcare</td>\n",
              "      <td>0.021771</td>\n",
              "      <td>-0.006409</td>\n",
              "      <td>129</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Industrials</td>\n",
              "      <td>0.029880</td>\n",
              "      <td>-0.004145</td>\n",
              "      <td>387</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>NOT_FOUND_ON_YAHOO</td>\n",
              "      <td>0.021959</td>\n",
              "      <td>-0.001395</td>\n",
              "      <td>830</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Real Estate</td>\n",
              "      <td>0.032541</td>\n",
              "      <td>0.002002</td>\n",
              "      <td>64</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Technology</td>\n",
              "      <td>0.030162</td>\n",
              "      <td>-0.004683</td>\n",
              "      <td>143</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Utilities</td>\n",
              "      <td>0.018176</td>\n",
              "      <td>-0.001370</td>\n",
              "      <td>66</td>\n",
              "      <td>2024-01-15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-11b64b7c-5d34-4368-bba2-35a93a8405c0')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-11b64b7c-5d34-4368-bba2-35a93a8405c0 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-11b64b7c-5d34-4368-bba2-35a93a8405c0');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-b60d1649-cf21-43fc-8a3a-2a3ba385b6c3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b60d1649-cf21-43fc-8a3a-2a3ba385b6c3')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b60d1649-cf21-43fc-8a3a-2a3ba385b6c3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_8903d059-23c5-42a5-acfa-0267ce3b8d45\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_8903d059-23c5-42a5-acfa-0267ce3b8d45 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[{\n            'v': 0,\n            'f': \"0\",\n        },\n\"Basic Materials\",\n{\n            'v': 0.029695357265710855,\n            'f': \"0.029695357265710855\",\n        },\n{\n            'v': -0.001036667605617851,\n            'f': \"-0.001036667605617851\",\n        },\n{\n            'v': 332,\n            'f': \"332\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 1,\n            'f': \"1\",\n        },\n\"Communication Services\",\n{\n            'v': 0.0294214461251539,\n            'f': \"0.0294214461251539\",\n        },\n{\n            'v': -0.009211159779816992,\n            'f': \"-0.009211159779816992\",\n        },\n{\n            'v': 73,\n            'f': \"73\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 2,\n            'f': \"2\",\n        },\n\"Consumer Cyclical\",\n{\n            'v': 0.027972126475184843,\n            'f': \"0.027972126475184843\",\n        },\n{\n            'v': -0.006129547558270805,\n            'f': \"-0.006129547558270805\",\n        },\n{\n            'v': 374,\n            'f': \"374\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 3,\n            'f': \"3\",\n        },\n\"Consumer Defensive\",\n{\n            'v': 0.027550780817081566,\n            'f': \"0.027550780817081566\",\n        },\n{\n            'v': -0.013982856639945682,\n            'f': \"-0.013982856639945682\",\n        },\n{\n            'v': 142,\n            'f': \"142\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 4,\n            'f': \"4\",\n        },\n\"Energy\",\n{\n            'v': 0.020202300049555758,\n            'f': \"0.020202300049555758\",\n        },\n{\n            'v': 0.00011673486716063803,\n            'f': \"0.00011673486716063803\",\n        },\n{\n            'v': 35,\n            'f': \"35\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 5,\n            'f': \"5\",\n        },\n\"Financial Services\",\n{\n            'v': 0.041982001708770485,\n            'f': \"0.041982001708770485\",\n        },\n{\n            'v': 0.003274884961541689,\n            'f': \"0.003274884961541689\",\n        },\n{\n            'v': 1113,\n            'f': \"1113\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 6,\n            'f': \"6\",\n        },\n\"Healthcare\",\n{\n            'v': 0.021770751223615686,\n            'f': \"0.021770751223615686\",\n        },\n{\n            'v': -0.006409169815557059,\n            'f': \"-0.006409169815557059\",\n        },\n{\n            'v': 129,\n            'f': \"129\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 7,\n            'f': \"7\",\n        },\n\"Industrials\",\n{\n            'v': 0.02988033933288875,\n            'f': \"0.02988033933288875\",\n        },\n{\n            'v': -0.00414523601979353,\n            'f': \"-0.00414523601979353\",\n        },\n{\n            'v': 387,\n            'f': \"387\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 8,\n            'f': \"8\",\n        },\n\"NOT_FOUND_ON_YAHOO\",\n{\n            'v': 0.021959254274750366,\n            'f': \"0.021959254274750366\",\n        },\n{\n            'v': -0.0013950864931823628,\n            'f': \"-0.0013950864931823628\",\n        },\n{\n            'v': 830,\n            'f': \"830\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 9,\n            'f': \"9\",\n        },\n\"Real Estate\",\n{\n            'v': 0.03254060254383588,\n            'f': \"0.03254060254383588\",\n        },\n{\n            'v': 0.0020019184793632974,\n            'f': \"0.0020019184793632974\",\n        },\n{\n            'v': 64,\n            'f': \"64\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 10,\n            'f': \"10\",\n        },\n\"Technology\",\n{\n            'v': 0.03016151614314009,\n            'f': \"0.03016151614314009\",\n        },\n{\n            'v': -0.004683075540827274,\n            'f': \"-0.004683075540827274\",\n        },\n{\n            'v': 143,\n            'f': \"143\",\n        },\n\"2024-01-15\"],\n [{\n            'v': 11,\n            'f': \"11\",\n        },\n\"Utilities\",\n{\n            'v': 0.018175772303911444,\n            'f': \"0.018175772303911444\",\n        },\n{\n            'v': -0.001369543242911358,\n            'f': \"-0.001369543242911358\",\n        },\n{\n            'v': 66,\n            'f': \"66\",\n        },\n\"2024-01-15\"]],\n        columns: [[\"number\", \"index\"], [\"string\", \"SECTOR\"], [\"number\", \"DAILY_RETURN_std\"], [\"number\", \"DAILY_RETURN_mean\"], [\"number\", \"DAILY_RETURN_count\"], [\"string\", \"TRADEDATE\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n        quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-9bc7595a-c770-4552-9803-8665c19e5004\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9bc7595a-c770-4552-9803-8665c19e5004')\"\n            title=\"Suggest charts\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-9bc7595a-c770-4552-9803-8665c19e5004 button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {}
        },
        {
          "output_type": "error",
          "ename": "BadZipFile",
          "evalue": "File is not a zip file",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mBadZipFile\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-85-78f2e32ef0fb>\u001b[0m in \u001b[0;36m<cell line: 6>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      9\u001b[0m   \u001b[0mdate_range\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mstart_date\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mtimedelta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdays\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_days\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m   \u001b[0;32mfor\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdate_range\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfetch_or_generate_performance_for_stocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m     \u001b[0mdisplay\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-84-ae6ef9dcc2cc>\u001b[0m in \u001b[0;36mfetch_or_generate_performance_for_stocks\u001b[0;34m(start_date)\u001b[0m\n\u001b[1;32m     31\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfetch_or_generate_performance_for_stocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m   \u001b[0msector_performance_output_file\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"SectorPeformance_\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m\u001b[0;34m\".pkl\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 33\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0mload_or_download_and_cache_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprepare_stocks_data_and_calculate_performance\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcache_file\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msector_performance_output_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-79-839e911d511c>\u001b[0m in \u001b[0;36mload_or_download_and_cache_data\u001b[0;34m(download_function, **kwargs)\u001b[0m\n\u001b[1;32m      9\u001b[0m       \u001b[0;32mreturn\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m   \u001b[0mdata_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdownload_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m   \u001b[0;31m# if not data_df.empty:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m   \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcache_file\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-84-ae6ef9dcc2cc>\u001b[0m in \u001b[0;36mprepare_stocks_data_and_calculate_performance\u001b[0;34m(**kwargs)\u001b[0m\n\u001b[1;32m     23\u001b[0m     \u001b[0mvalidate_required_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'start_date'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m     \u001b[0mstart_date\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mdate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'start_date'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m     \u001b[0mstocks_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfetch_or_genenate_stocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     26\u001b[0m     \u001b[0mstocks_df_with_sector\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfetch_or_generate_sector_to_stocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstocks_df\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mcalculate_performace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstocks_df_with_sector\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-81-c7adc48a9809>\u001b[0m in \u001b[0;36mfetch_or_genenate_stocks\u001b[0;34m(start_date)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfetch_or_genenate_stocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m   \u001b[0moutput_file\u001b[0m  \u001b[0;34m=\u001b[0m \u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"NseData_\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m\u001b[0;34m\".pkl\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0mload_or_download_and_cache_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdownload_bhavcopy\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mstart_date\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcache_file\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moutput_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-79-839e911d511c>\u001b[0m in \u001b[0;36mload_or_download_and_cache_data\u001b[0;34m(download_function, **kwargs)\u001b[0m\n\u001b[1;32m      9\u001b[0m       \u001b[0;32mreturn\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m   \u001b[0mdata_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdownload_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m   \u001b[0;31m# if not data_df.empty:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m   \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcache_file\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-80-a679965a0ead>\u001b[0m in \u001b[0;36mdownload_bhavcopy\u001b[0;34m(**kwargs)\u001b[0m\n\u001b[1;32m     10\u001b[0m   \u001b[0mstart_date\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"start_date\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m   \u001b[0mgenerated_csv_filename\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbhavcopy_save\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     13\u001b[0m   \u001b[0mcache_file_to_csv_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache_file\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_suffix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\".csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m   \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerated_csv_filename\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcache_file_to_csv_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/jugaad_data/nse/archives.py\u001b[0m in \u001b[0;36mbhavcopy_save\u001b[0;34m(self, dt, dest, skip_if_present)\u001b[0m\n\u001b[1;32m     72\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misfile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mskip_if_present\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mfname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 74\u001b[0;31m         \u001b[0mtext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbhavcopy_raw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     75\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'w'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     76\u001b[0m             \u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/jugaad_data/nse/archives.py\u001b[0m in \u001b[0;36munzipper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     15\u001b[0m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m         \u001b[0mfp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m         \u001b[0;32mwith\u001b[0m \u001b[0mzipfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mZipFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfp\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mzf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     18\u001b[0m             \u001b[0mfname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mzf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnamelist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mzf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfp_bh\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/zipfile.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, file, mode, compression, allowZip64, compresslevel, strict_timestamps)\u001b[0m\n\u001b[1;32m   1267\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1268\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'r'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1269\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_RealGetContents\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1270\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m'w'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'x'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1271\u001b[0m                 \u001b[0;31m# set the modified flag so central directory gets written\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/zipfile.py\u001b[0m in \u001b[0;36m_RealGetContents\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1334\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mBadZipFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"File is not a zip file\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1335\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mendrec\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1336\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mBadZipFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"File is not a zip file\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1337\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1338\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mendrec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mBadZipFile\u001b[0m: File is not a zip file"
          ]
        }
      ],
      "source": [
        "from google.colab import data_table\n",
        "from datetime import date, timedelta#\n",
        "\n",
        "data_table.enable_dataframe_formatter()\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "  start_date = date (2024,1,18)\n",
        "  num_days = 10\n",
        "  date_range = [start_date - timedelta(days=i) for i in range(num_days)]\n",
        "  for d in date_range:\n",
        "    df = fetch_or_generate_performance_for_stocks(d)\n",
        "    display(df)\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "98liOXHb3q3U"
      },
      "outputs": [],
      "source": [
        "# ! rm -rf /content/sample_data/*pkl\n",
        "# ! rm -rf /content/sample_data/*csv"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "P2ebqxXaI-lF"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNwmtTf/kaG0aKv2ou46gkH",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}