CP_positions_D30.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOZHO2XQCneiVTA6/TUCtVJ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/abhisekde96/fii-pro-analysis/blob/main/CP_positions_D30.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "import pandas as pd\n",
        "from datetime import datetime, timedelta\n",
        "import matplotlib.pyplot as plt\n",
        "import pytz\n",
        "import os\n",
        "from multiprocessing import Pool\n",
        "import time\n",
        "\n",
        "start_time = time.time()\n",
        "\n",
        "# Function to load or cache the CSV\n",
        "def load_or_cache_csv(date):\n",
        "    local_path = f'./cache/fao_participant_oi_{date}.csv'\n",
        "    if os.path.exists(local_path):\n",
        "        print(f\"Loading from cache: {date}\")\n",
        "        df = pd.read_csv(local_path)\n",
        "    else:\n",
        "        try:\n",
        "            #print(f\"Downloading for: {date}\")\n",
        "            df = pd.read_csv(f'http://archives.nseindia.com/content/nsccl/fao_participant_oi_{date}.csv', header=1)\n",
        "            os.makedirs('./cache', exist_ok=True)  # Create cache directory if it doesn't exist\n",
        "            df.to_csv(local_path, index=False)\n",
        "        except Exception as e:\n",
        "            print(f\"Failed to load data for date: {date} - {str(e)}\")\n",
        "            return None\n",
        "    return df\n",
        "\n",
        "# Get current time in IST timezone\n",
        "ist_timezone = pytz.timezone('Asia/Kolkata')\n",
        "current_time = datetime.now(ist_timezone)\n",
        "\n",
        "# Check if current time has crossed 9 PM\n",
        "if current_time.hour >= 21:  # 21 is 9 PM in 24-hour format\n",
        "    # If it has crossed 9 PM, today's date is considered\n",
        "    today = current_time.date()\n",
        "else:\n",
        "    # If it hasn't crossed 9 PM, consider yesterday's date as today's date\n",
        "    today = current_time.date() - timedelta(days=1)\n",
        "\n",
        "# Collect the last 30 weekdays (excluding weekends)\n",
        "dates_list = []\n",
        "date_count = 0\n",
        "while date_count < 33:\n",
        "    # Check if the current date is a weekday\n",
        "    if today.weekday() < 5:  # Monday is 0, Sunday is 6\n",
        "        # Format and append the date to the list\n",
        "        dates_list.append(today.strftime('%d%m%Y'))\n",
        "        date_count += 1\n",
        "    # Move to the previous day\n",
        "    today -= timedelta(days=1)\n",
        "\n",
        "# Load CSV files in parallel using multiprocessing\n",
        "with Pool() as pool:\n",
        "    results = pool.map(load_or_cache_csv, dates_list)\n",
        "\n",
        "# Filter out unsuccessful loads and create dataframes dict\n",
        "dataframes = {date: df for date, df in zip(dates_list, results) if df is not None}\n",
        "\n",
        "# Reverse the list for proper date order\n",
        "successful_dates = [date for date, df in zip(dates_list, results) if df is not None]\n",
        "dates = pd.DataFrame(successful_dates, columns=['Date'])\n",
        "dates = dates.iloc[::-1]\n",
        "\n",
        "# Convert the dictionary values to a list of DataFrames\n",
        "dataframes_list = list(dataframes.values())\n",
        "\n",
        "# Dynamically create and process variables t0, t1, t2, etc.\n",
        "for i in range(len(dataframes_list)):\n",
        "    df = dataframes_list[i]\n",
        "    df = df.iloc[2:4, [0, 5, 6, 7, 8]]\n",
        "    df.set_index('Client Type', inplace=True)\n",
        "    df[f'c{i}'] = df['Option Index Call Long'] - df['Option Index Call Short']  # Compute call difference\n",
        "    df[f'p{i}'] = df['Option Index Put Long'] - df['Option Index Put Short']  # Compute put difference\n",
        "    df = df.iloc[:, [4, 5]]  # Keep only the relevant columns (c and p columns)\n",
        "    globals()[f't{i}'] = df\n",
        "\n",
        "# Collect all processed DataFrames into a list\n",
        "df_list = [globals()[f't{i}'] for i in range(len(dataframes_list))]\n",
        "\n",
        "# Concatenate all DataFrames along columns (axis=1)\n",
        "t_all = pd.concat(df_list, axis=1)\n",
        "\n",
        "# Separate call and put columns\n",
        "c_columns = [f'c{i}' for i in range(len(dataframes_list))]\n",
        "calls = pd.concat([t_all[col] for col in c_columns], axis=1)\n",
        "\n",
        "p_columns = [f'p{i}' for i in range(len(dataframes_list))]\n",
        "puts = pd.concat([t_all[col] for col in p_columns], axis=1)\n",
        "\n",
        "# Calculate aggregated call and put positions\n",
        "agg_dict1 = {col: 'sum' for col in c_columns}\n",
        "tc = calls.agg(agg_dict1)\n",
        "rename_dict = {f'c{i}': i for i in range(len(dataframes_list))}\n",
        "tc = tc.rename(rename_dict)\n",
        "tc = pd.DataFrame(tc)\n",
        "\n",
        "agg_dict2 = {col: 'sum' for col in p_columns}\n",
        "tp = puts.agg(agg_dict2)\n",
        "rename_dict = {f'p{i}': i for i in range(len(dataframes_list))}\n",
        "tp = tp.rename(rename_dict)\n",
        "tp = pd.DataFrame(tp)\n",
        "\n",
        "# Reverse order and add date columns\n",
        "tc = tc.iloc[::-1]\n",
        "tp = tp.iloc[::-1]\n",
        "tc['Date'] = dates['Date']\n",
        "tp['Date'] = dates['Date']\n",
        "tc['Date'] = pd.to_datetime(tc['Date'], format='%d%m%Y').dt.strftime('%d/%m/%Y')\n",
        "tp['Date'] = pd.to_datetime(tp['Date'], format='%d%m%Y').dt.strftime('%d/%m/%Y')\n",
        "\n",
        "tc.set_index('Date', inplace=True)\n",
        "tp.set_index('Date', inplace=True)\n",
        "tc.rename(columns={0: 'call_positions'}, inplace=True)\n",
        "tp.rename(columns={0: 'put_positions'}, inplace=True)\n",
        "\n",
        "# Final DataFrame\n",
        "all_data = pd.merge(tc, tp, left_index=True, right_index=True, how='inner').reset_index()\n",
        "all_data = all_data.iloc[::-1]\n",
        "all_data['Date'] = pd.to_datetime(all_data['Date'], format='%d/%m/%Y')\n",
        "\n",
        "# Calculate Call/Put Changes and Direction\n",
        "all_data['Day'] = all_data['Date'].dt.day_name()\n",
        "all_data['direction'] = all_data.apply(lambda row: 'CALLS>>' if row['call_positions'] > row['put_positions'] else 'PUTS>>', axis=1)\n",
        "all_data['c1'] = all_data['call_positions'].shift(-1)\n",
        "all_data['p1'] = all_data['put_positions'].shift(-1)\n",
        "all_data['cd'] = (all_data['call_positions'] - all_data['c1']) / all_data['c1'] * 100\n",
        "all_data['pd'] = (all_data['put_positions'] - all_data['p1']) / all_data['p1'] * 100\n",
        "all_data['cd'] = round(all_data['cd'].abs(), 2).astype(str) + '%'\n",
        "all_data['pd'] = round(all_data['pd'].abs(), 2).astype(str) + '%'\n",
        "all_data['CALLS'] = all_data['call_positions'] - all_data['c1']\n",
        "all_data['PUTS'] = all_data['put_positions'] - all_data['p1']\n",
        "all_data['CALLS'] = all_data['CALLS'].apply(lambda x: 'ADDED' if x > 0 else 'DUMPED') + ' ' + all_data['cd']\n",
        "all_data['PUTS'] = all_data['PUTS'].apply(lambda x: 'ADDED' if x > 0 else 'DUMPED') + ' ' + all_data['pd']\n",
        "\n",
        "final_df = all_data[['Date', 'Day', 'call_positions', 'put_positions', 'CALLS', 'PUTS']]\n",
        "\n",
        "end_time = time.time()\n",
        "\n",
        "total_time = end_time - start_time\n",
        "print(f\"Total time taken: {total_time:.2f} seconds\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AXnYN3SghogB",
        "outputId": "e788e53c-8e8a-4c8b-e175-76c8ab2e6a9d"
      },
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Failed to load data for date: 02102024 - HTTP Error 404: Not Found\n",
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            "Total time taken: 1.85 seconds\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "adPITF-4hxKi",
        "outputId": "fcd77fe9-7929-4b4a-f54d-ac0506579964"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Date        Day  call_positions  put_positions           CALLS  \\\n",
              "31 2024-10-04     Friday          458066        1061905   ADDED 224.98%   \n",
              "30 2024-10-03   Thursday          140954         678329   DUMPED 68.01%   \n",
              "29 2024-10-01    Tuesday          440563         602264    ADDED 448.3%   \n",
              "28 2024-09-30     Monday           80350         500145   DUMPED 87.42%   \n",
              "27 2024-09-27     Friday          638634         494317    DUMPED 2.41%   \n",
              "26 2024-09-26   Thursday          654379         160546    DUMPED 21.5%   \n",
              "25 2024-09-25  Wednesday          833552         299270    ADDED 57.68%   \n",
              "24 2024-09-24    Tuesday          528620          43440   DUMPED 34.66%   \n",
              "23 2024-09-23     Monday          808992          -6021    DUMPED 21.5%   \n",
              "22 2024-09-20     Friday         1030622         226214   ADDED 109.53%   \n",
              "21 2024-09-19   Thursday          491879         365955    ADDED 69.71%   \n",
              "20 2024-09-18  Wednesday          289831         182195     ADDED 13.8%   \n",
              "19 2024-09-17    Tuesday          254686        -126020    DUMPED 13.9%   \n",
              "18 2024-09-16     Monday          295793        -101409    DUMPED 26.9%   \n",
              "17 2024-09-13     Friday          404616         103952   DUMPED 42.26%   \n",
              "16 2024-09-12   Thursday          700764         182198   ADDED 189.12%   \n",
              "15 2024-09-11  Wednesday          242382         635258   DUMPED 49.67%   \n",
              "14 2024-09-10    Tuesday          481551         392585    ADDED 14.75%   \n",
              "13 2024-09-09     Monday          419660         439011   ADDED 475.31%   \n",
              "12 2024-09-06     Friday         -111816         559560  DUMPED 123.99%   \n",
              "11 2024-09-05   Thursday          466153         410713    DUMPED 10.9%   \n",
              "10 2024-09-04  Wednesday          523156         430055    DUMPED 9.72%   \n",
              "9  2024-09-03    Tuesday          579461         199088    ADDED 56.74%   \n",
              "8  2024-09-02     Monday          369684         282420   DUMPED 38.45%   \n",
              "7  2024-08-30     Friday          600664         241621     ADDED 33.5%   \n",
              "6  2024-08-29   Thursday          449938         359815    ADDED 14.64%   \n",
              "5  2024-08-28  Wednesday          392486         418321    ADDED 10.43%   \n",
              "4  2024-08-27    Tuesday          355423         249180    DUMPED 26.9%   \n",
              "3  2024-08-26     Monday          486222         257594    ADDED 54.91%   \n",
              "2  2024-08-23     Friday          313875         388424    DUMPED 6.82%   \n",
              "1  2024-08-22   Thursday          336861         320465    DUMPED 3.34%   \n",
              "0  2024-08-21  Wednesday          348500         272610     DUMPED nan%   \n",
              "\n",
              "              PUTS  \n",
              "31    ADDED 56.55%  \n",
              "30    ADDED 12.63%  \n",
              "29    ADDED 20.42%  \n",
              "28     ADDED 1.18%  \n",
              "27    ADDED 207.9%  \n",
              "26   DUMPED 46.35%  \n",
              "25   ADDED 588.93%  \n",
              "24   ADDED 821.47%  \n",
              "23  DUMPED 102.66%  \n",
              "22   DUMPED 38.19%  \n",
              "21   ADDED 100.86%  \n",
              "20   ADDED 244.58%  \n",
              "19   DUMPED 24.27%  \n",
              "18  DUMPED 197.55%  \n",
              "17   DUMPED 42.95%  \n",
              "16   DUMPED 71.32%  \n",
              "15    ADDED 61.81%  \n",
              "14   DUMPED 10.58%  \n",
              "13   DUMPED 21.54%  \n",
              "12    ADDED 36.24%  \n",
              "11     DUMPED 4.5%  \n",
              "10   ADDED 116.01%  \n",
              "9    DUMPED 29.51%  \n",
              "8     ADDED 16.89%  \n",
              "7    DUMPED 32.85%  \n",
              "6    DUMPED 13.99%  \n",
              "5     ADDED 67.88%  \n",
              "4     DUMPED 3.27%  \n",
              "3    DUMPED 33.68%  \n",
              "2     ADDED 21.21%  \n",
              "1     ADDED 17.55%  \n",
              "0      DUMPED nan%  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-221b7734-ff7b-4858-b43f-e43e1b9e4508\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Day</th>\n",
              "      <th>call_positions</th>\n",
              "      <th>put_positions</th>\n",
              "      <th>CALLS</th>\n",
              "      <th>PUTS</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2024-10-04</td>\n",
              "      <td>Friday</td>\n",
              "      <td>458066</td>\n",
              "      <td>1061905</td>\n",
              "      <td>ADDED 224.98%</td>\n",
              "      <td>ADDED 56.55%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2024-10-03</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>140954</td>\n",
              "      <td>678329</td>\n",
              "      <td>DUMPED 68.01%</td>\n",
              "      <td>ADDED 12.63%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2024-10-01</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>440563</td>\n",
              "      <td>602264</td>\n",
              "      <td>ADDED 448.3%</td>\n",
              "      <td>ADDED 20.42%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2024-09-30</td>\n",
              "      <td>Monday</td>\n",
              "      <td>80350</td>\n",
              "      <td>500145</td>\n",
              "      <td>DUMPED 87.42%</td>\n",
              "      <td>ADDED 1.18%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2024-09-27</td>\n",
              "      <td>Friday</td>\n",
              "      <td>638634</td>\n",
              "      <td>494317</td>\n",
              "      <td>DUMPED 2.41%</td>\n",
              "      <td>ADDED 207.9%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2024-09-26</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>654379</td>\n",
              "      <td>160546</td>\n",
              "      <td>DUMPED 21.5%</td>\n",
              "      <td>DUMPED 46.35%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2024-09-25</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>833552</td>\n",
              "      <td>299270</td>\n",
              "      <td>ADDED 57.68%</td>\n",
              "      <td>ADDED 588.93%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2024-09-24</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>528620</td>\n",
              "      <td>43440</td>\n",
              "      <td>DUMPED 34.66%</td>\n",
              "      <td>ADDED 821.47%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2024-09-23</td>\n",
              "      <td>Monday</td>\n",
              "      <td>808992</td>\n",
              "      <td>-6021</td>\n",
              "      <td>DUMPED 21.5%</td>\n",
              "      <td>DUMPED 102.66%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2024-09-20</td>\n",
              "      <td>Friday</td>\n",
              "      <td>1030622</td>\n",
              "      <td>226214</td>\n",
              "      <td>ADDED 109.53%</td>\n",
              "      <td>DUMPED 38.19%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2024-09-19</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>491879</td>\n",
              "      <td>365955</td>\n",
              "      <td>ADDED 69.71%</td>\n",
              "      <td>ADDED 100.86%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2024-09-18</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>289831</td>\n",
              "      <td>182195</td>\n",
              "      <td>ADDED 13.8%</td>\n",
              "      <td>ADDED 244.58%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2024-09-17</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>254686</td>\n",
              "      <td>-126020</td>\n",
              "      <td>DUMPED 13.9%</td>\n",
              "      <td>DUMPED 24.27%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2024-09-16</td>\n",
              "      <td>Monday</td>\n",
              "      <td>295793</td>\n",
              "      <td>-101409</td>\n",
              "      <td>DUMPED 26.9%</td>\n",
              "      <td>DUMPED 197.55%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2024-09-13</td>\n",
              "      <td>Friday</td>\n",
              "      <td>404616</td>\n",
              "      <td>103952</td>\n",
              "      <td>DUMPED 42.26%</td>\n",
              "      <td>DUMPED 42.95%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2024-09-12</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>700764</td>\n",
              "      <td>182198</td>\n",
              "      <td>ADDED 189.12%</td>\n",
              "      <td>DUMPED 71.32%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2024-09-11</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>242382</td>\n",
              "      <td>635258</td>\n",
              "      <td>DUMPED 49.67%</td>\n",
              "      <td>ADDED 61.81%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2024-09-10</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>481551</td>\n",
              "      <td>392585</td>\n",
              "      <td>ADDED 14.75%</td>\n",
              "      <td>DUMPED 10.58%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2024-09-09</td>\n",
              "      <td>Monday</td>\n",
              "      <td>419660</td>\n",
              "      <td>439011</td>\n",
              "      <td>ADDED 475.31%</td>\n",
              "      <td>DUMPED 21.54%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2024-09-06</td>\n",
              "      <td>Friday</td>\n",
              "      <td>-111816</td>\n",
              "      <td>559560</td>\n",
              "      <td>DUMPED 123.99%</td>\n",
              "      <td>ADDED 36.24%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2024-09-05</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>466153</td>\n",
              "      <td>410713</td>\n",
              "      <td>DUMPED 10.9%</td>\n",
              "      <td>DUMPED 4.5%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2024-09-04</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>523156</td>\n",
              "      <td>430055</td>\n",
              "      <td>DUMPED 9.72%</td>\n",
              "      <td>ADDED 116.01%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2024-09-03</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>579461</td>\n",
              "      <td>199088</td>\n",
              "      <td>ADDED 56.74%</td>\n",
              "      <td>DUMPED 29.51%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2024-09-02</td>\n",
              "      <td>Monday</td>\n",
              "      <td>369684</td>\n",
              "      <td>282420</td>\n",
              "      <td>DUMPED 38.45%</td>\n",
              "      <td>ADDED 16.89%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2024-08-30</td>\n",
              "      <td>Friday</td>\n",
              "      <td>600664</td>\n",
              "      <td>241621</td>\n",
              "      <td>ADDED 33.5%</td>\n",
              "      <td>DUMPED 32.85%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2024-08-29</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>449938</td>\n",
              "      <td>359815</td>\n",
              "      <td>ADDED 14.64%</td>\n",
              "      <td>DUMPED 13.99%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2024-08-28</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>392486</td>\n",
              "      <td>418321</td>\n",
              "      <td>ADDED 10.43%</td>\n",
              "      <td>ADDED 67.88%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2024-08-27</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>355423</td>\n",
              "      <td>249180</td>\n",
              "      <td>DUMPED 26.9%</td>\n",
              "      <td>DUMPED 3.27%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2024-08-26</td>\n",
              "      <td>Monday</td>\n",
              "      <td>486222</td>\n",
              "      <td>257594</td>\n",
              "      <td>ADDED 54.91%</td>\n",
              "      <td>DUMPED 33.68%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2024-08-23</td>\n",
              "      <td>Friday</td>\n",
              "      <td>313875</td>\n",
              "      <td>388424</td>\n",
              "      <td>DUMPED 6.82%</td>\n",
              "      <td>ADDED 21.21%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2024-08-22</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>336861</td>\n",
              "      <td>320465</td>\n",
              "      <td>DUMPED 3.34%</td>\n",
              "      <td>ADDED 17.55%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2024-08-21</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>348500</td>\n",
              "      <td>272610</td>\n",
              "      <td>DUMPED nan%</td>\n",
              "      <td>DUMPED nan%</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-221b7734-ff7b-4858-b43f-e43e1b9e4508')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "    .colab-df-buttons div {\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-221b7734-ff7b-4858-b43f-e43e1b9e4508 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-221b7734-ff7b-4858-b43f-e43e1b9e4508');\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",
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              "\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\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",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    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",
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              "    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-b31220cf-0f7f-4bdd-b352-0577533812ce button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_4e9bc137-3dcb-42e5-9559-cdcd84419a76\">\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",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
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              "      }\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('final_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",
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              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_4e9bc137-3dcb-42e5-9559-cdcd84419a76 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('final_df');\n",
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              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "final_df",
              "summary": "{\n  \"name\": \"final_df\",\n  \"rows\": 32,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-08-21 00:00:00\",\n        \"max\": \"2024-10-04 00:00:00\",\n        \"num_unique_values\": 32,\n        \"samples\": [\n          \"2024-08-23 00:00:00\",\n          \"2024-09-12 00:00:00\",\n          \"2024-08-30 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Day\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Thursday\",\n          \"Wednesday\",\n          \"Tuesday\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"call_positions\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 223630,\n        \"min\": -111816,\n        \"max\": 1030622,\n        \"num_unique_values\": 32,\n        \"samples\": [\n          313875,\n          700764,\n          600664\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"put_positions\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 237279,\n        \"min\": -126020,\n        \"max\": 1061905,\n        \"num_unique_values\": 32,\n        \"samples\": [\n          388424,\n          182198,\n          241621\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CALLS\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 30,\n        \"samples\": [\n          \"DUMPED 6.82%\",\n          \"DUMPED 49.67%\",\n          \"ADDED 33.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PUTS\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 32,\n        \"samples\": [\n          \"ADDED 21.21%\",\n          \"DUMPED 71.32%\",\n          \"DUMPED 32.85%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "7EFmzdzMiBpk"
      },
      "execution_count": 86,
      "outputs": []
    }
  ]
}