YFinance.ipynb

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   "source": "### Yahoo Finance API - Historical Data",
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     "text": "Collecting yfinance==0.1.68\n  Downloading yfinance-0.1.68-py2.py3-none-any.whl (26 kB)\nRequirement already satisfied: requests>=2.26 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from yfinance==0.1.68) (2.26.0)\nCollecting multitasking>=0.0.7\n  Downloading multitasking-0.0.10.tar.gz (8.2 kB)\nRequirement already satisfied: pandas>=0.24 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from yfinance==0.1.68) (1.2.5)\nRequirement already satisfied: lxml>=4.5.1 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from yfinance==0.1.68) (4.7.1)\nRequirement already satisfied: numpy>=1.15 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from yfinance==0.1.68) (1.21.4)\nRequirement already satisfied: pytz>=2017.3 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from pandas>=0.24->yfinance==0.1.68) (2021.3)\nRequirement already satisfied: python-dateutil>=2.7.3 in /shared-libs/python3.9/py-core/lib/python3.9/site-packages (from pandas>=0.24->yfinance==0.1.68) (2.8.2)\nRequirement already satisfied: six>=1.5 in /shared-libs/python3.9/py-core/lib/python3.9/site-packages (from python-dateutil>=2.7.3->pandas>=0.24->yfinance==0.1.68) (1.16.0)\nRequirement already satisfied: charset-normalizer~=2.0.0 in /shared-libs/python3.9/py-core/lib/python3.9/site-packages (from requests>=2.26->yfinance==0.1.68) (2.0.9)\nRequirement already satisfied: urllib3<1.27,>=1.21.1 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from requests>=2.26->yfinance==0.1.68) (1.26.7)\nRequirement already satisfied: idna<4,>=2.5 in /shared-libs/python3.9/py-core/lib/python3.9/site-packages (from requests>=2.26->yfinance==0.1.68) (3.3)\nRequirement already satisfied: certifi>=2017.4.17 in /shared-libs/python3.9/py/lib/python3.9/site-packages (from requests>=2.26->yfinance==0.1.68) (2021.10.8)\nBuilding wheels for collected packages: multitasking\n  Building wheel for multitasking (setup.py) ... \u001b[?25ldone\n\u001b[?25h  Created wheel for multitasking: filename=multitasking-0.0.10-py3-none-any.whl size=8500 sha256=2d5703f067b87ce67ef1d6597f7e2e7379fcfe3c6abc737e99f36253eccb5713\n  Stored in directory: /root/.cache/pip/wheels/f2/b5/2c/59ba95dcf854e542944c75fe3da584e4e3833b319735a0546c\nSuccessfully built multitasking\nInstalling collected packages: multitasking, yfinance\nSuccessfully installed multitasking-0.0.10 yfinance-0.1.68\n\u001b[33mWARNING: You are using pip version 21.2.3; however, version 21.3.1 is available.\nYou should consider upgrading via the '/root/venv/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
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    "execution_start": 1641144543823,
    "execution_millis": 8,
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   "source": "import yfinance as yf",
   "outputs": [],
   "execution_count": null
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    "execution_start": 1641144555550,
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   },
   "source": "df = yf.download(tickers=\"MSFT GS JPM MS AMZN\", start = \"2021-12-01\", end = \"2021-12-31\", group_by='ticker')",
   "outputs": [
    {
     "name": "stdout",
     "text": "[*********************100%***********************]  5 of 5 completed\n",
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   "source": "df['MSFT'].head(2)",
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      "text/plain": "                  Open        High         Low       Close   Adj Close  \\\nDate                                                                     \n2021-12-01  335.130005  339.279999  329.390015  330.079987  330.079987   \n2021-12-02  330.299988  333.489990  327.799988  329.489990  329.489990   \n\n              Volume  \nDate                  \n2021-12-01  33337600  \n2021-12-02  30766000  ",
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    "execution_start": 1641144580400,
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   },
   "source": "df_msft = df['MSFT']\ndf_gs = df['GS']\ndf_jpm = df['JPM']\ndf_ms = df['MS']\ndf_amzn = df['AMZN']",
   "outputs": [],
   "execution_count": null
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    "execution_start": 1641144582923,
    "execution_millis": 5,
    "deepnote_cell_type": "code"
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   "source": "df_msft['Stock_Code'] = 'MSFT'",
   "outputs": [
    {
     "name": "stderr",
     "text": "<ipython-input-8-8d01a5e378d5>:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  df_msft['Stock_Code'] = 'MSFT'\n",
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    "execution_start": 1641144584752,
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   "source": "df_ms['Stock_Code'] = 'MS'",
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    {
     "name": "stderr",
     "text": "<ipython-input-9-0bdc997650fd>:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  df_ms['Stock_Code'] = 'MS'\n",
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    "execution_start": 1641144587178,
    "execution_millis": 1,
    "deepnote_cell_type": "code"
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   "source": "df_gs['Stock_Code'] = 'GS'",
   "outputs": [
    {
     "name": "stderr",
     "text": "<ipython-input-10-b5168951a71f>:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  df_gs['Stock_Code'] = 'GS'\n",
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   "source": "df_jpm['Stock_Code'] = 'JPM'",
   "outputs": [
    {
     "name": "stderr",
     "text": "<ipython-input-11-67566d5852ba>:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  df_jpm['Stock_Code'] = 'JPM'\n",
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   "source": "df_amzn['Stock_Code'] = 'AMZN'",
   "outputs": [
    {
     "name": "stderr",
     "text": "<ipython-input-12-0b53570c51d9>:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  df_amzn['Stock_Code'] = 'AMZN'\n",
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   "execution_count": null
  },
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   "source": "data_stocks = pd.concat([df_msft,df_gs,df_jpm,df_ms,df_amzn],axis=0)",
   "execution_count": null,
   "outputs": []
  },
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      "text/plain": "                  Open        High         Low       Close   Adj Close  \\\nDate                                                                     \n2021-01-04  267.000000  267.579987  260.160004  265.000000  260.428192   \n2021-01-05  263.880005  273.500000  262.570007  270.929993  266.255920   \n2021-01-06  276.290009  288.380005  273.100006  285.549988  280.623657   \n2021-01-07  287.769989  295.890015  286.679993  291.649994  286.618469   \n2021-01-08  292.000000  292.279999  285.059998  290.079987  285.075500   \n...                ...         ...         ...         ...         ...   \n2021-11-22  393.160004  402.489990  390.179993  396.160004  394.080353   \n2021-11-23  400.250000  406.959991  397.510010  406.339996  404.206909   \n2021-11-24  405.000000  407.480011  398.299988  399.190002  397.094452   \n2021-11-26  384.480011  391.709991  382.720001  389.390015  387.345917   \n2021-11-29  394.000000  396.369995  382.450012  386.540009  384.510864   \n\n             Volume Stock_Code  \nDate                            \n2021-01-04  3572000         GS  \n2021-01-05  4207100         GS  \n2021-01-06  6383500         GS  \n2021-01-07  4009700         GS  \n2021-01-08  2800800         GS  \n...             ...        ...  \n2021-11-22  3058700         GS  \n2021-11-23  2402300         GS  \n2021-11-24  2186300         GS  \n2021-11-26  2687900         GS  \n2021-11-29  2883400         GS  \n\n[229 rows x 7 columns]",
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      "text/plain": "                   Open         High          Low        Close    Volume  \\\nDate                                                                       \n2021-01-04   222.529999   223.000000   214.809998   217.690002  37130100   \n2021-01-05   217.259995   218.520004   215.699997   217.899994  23823000   \n2021-01-06   212.169998   216.490005   211.940002   212.250000  35930700   \n2021-01-07   214.039993   219.339996   213.710007   218.289993  27694500   \n2021-01-08   218.679993   220.580002   217.029999   219.619995  22956200   \n...                 ...          ...          ...          ...       ...   \n2021-11-22  3676.379883  3713.459961  3567.500000  3572.570068   4842200   \n2021-11-23  3585.040039  3621.050049  3527.709961  3580.040039   3690200   \n2021-11-24  3562.669922  3613.639893  3536.850098  3580.409912   2328000   \n2021-11-26  3602.100098  3633.500000  3504.149902  3504.560059   2991300   \n2021-11-29  3547.639893  3596.000000  3531.500000  3561.570068   3265600   \n\n           Stock_Code  \nDate                   \n2021-01-04       MSFT  \n2021-01-05       MSFT  \n2021-01-06       MSFT  \n2021-01-07       MSFT  \n2021-01-08       MSFT  \n...               ...  \n2021-11-22       AMZN  \n2021-11-23       AMZN  \n2021-11-24       AMZN  \n2021-11-26       AMZN  \n2021-11-29       AMZN  \n\n[1145 rows x 6 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Volume</th>\n      <th>Stock_Code</th>\n    </tr>\n    <tr>\n      <th>Date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-01-04</th>\n      <td>222.529999</td>\n      <td>223.000000</td>\n      <td>214.809998</td>\n      <td>217.690002</td>\n      <td>37130100</td>\n      <td>MSFT</td>\n    </tr>\n    <tr>\n      <th>2021-01-05</th>\n      <td>217.259995</td>\n      <td>218.520004</td>\n      <td>215.699997</td>\n      <td>217.899994</td>\n      <td>23823000</td>\n      <td>MSFT</td>\n    </tr>\n    <tr>\n      <th>2021-01-06</th>\n      <td>212.169998</td>\n      <td>216.490005</td>\n      <td>211.940002</td>\n      <td>212.250000</td>\n      <td>35930700</td>\n      <td>MSFT</td>\n    </tr>\n    <tr>\n      <th>2021-01-07</th>\n      <td>214.039993</td>\n      <td>219.339996</td>\n      <td>213.710007</td>\n      <td>218.289993</td>\n      <td>27694500</td>\n      <td>MSFT</td>\n    </tr>\n    <tr>\n      <th>2021-01-08</th>\n      <td>218.679993</td>\n      <td>220.580002</td>\n      <td>217.029999</td>\n      <td>219.619995</td>\n      <td>22956200</td>\n      <td>MSFT</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>2021-11-22</th>\n      <td>3676.379883</td>\n      <td>3713.459961</td>\n      <td>3567.500000</td>\n      <td>3572.570068</td>\n      <td>4842200</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-11-23</th>\n      <td>3585.040039</td>\n      <td>3621.050049</td>\n      <td>3527.709961</td>\n      <td>3580.040039</td>\n      <td>3690200</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-11-24</th>\n      <td>3562.669922</td>\n      <td>3613.639893</td>\n      <td>3536.850098</td>\n      <td>3580.409912</td>\n      <td>2328000</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-11-26</th>\n      <td>3602.100098</td>\n      <td>3633.500000</td>\n      <td>3504.149902</td>\n      <td>3504.560059</td>\n      <td>2991300</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-11-29</th>\n      <td>3547.639893</td>\n      <td>3596.000000</td>\n      <td>3531.500000</td>\n      <td>3561.570068</td>\n      <td>3265600</td>\n      <td>AMZN</td>\n    </tr>\n  </tbody>\n</table>\n<p>1145 rows × 6 columns</p>\n</div>"
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00020-9c5f7cc0-69f6-4758-b7e3-77b83cc7a683",
    "deepnote_to_be_reexecuted": false,
    "source_hash": "2f3a4c39",
    "execution_start": 1640200138111,
    "execution_millis": 1,
    "deepnote_cell_type": "code"
   },
   "source": "# calculating index!!\n# for every stock? separately?",
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00018-a6063c1f-ea0e-455c-9af5-99d37ed8a929",
    "deepnote_to_be_reexecuted": false,
    "source_hash": "3aea781f",
    "execution_start": 1640256997808,
    "execution_millis": 27,
    "deepnote_cell_type": "code"
   },
   "source": "data_stocks.to_csv('Stocks_HistData.csv')",
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": "df_amzn",
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    "cell_id": "00021-fa5174a1-df76-46fc-a332-3a52334d1c17",
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    "source_hash": "25def6bb",
    "execution_start": 1641144634914,
    "execution_millis": 35,
    "deepnote_cell_type": "code"
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      "text/plain": "                   Open         High          Low        Close    Adj Close  \\\nDate                                                                          \n2021-12-01  3545.000000  3559.879883  3441.600098  3443.719971  3443.719971   \n2021-12-02  3460.000000  3492.699951  3423.750000  3437.360107  3437.360107   \n2021-12-03  3455.000000  3469.870117  3338.600098  3389.790039  3389.790039   \n2021-12-06  3393.000000  3473.909912  3338.689941  3427.370117  3427.370117   \n2021-12-07  3492.000000  3549.989990  3466.689941  3523.290039  3523.290039   \n2021-12-08  3523.010010  3543.600098  3495.010010  3523.159912  3523.159912   \n2021-12-09  3515.000000  3539.389893  3482.790039  3483.419922  3483.419922   \n2021-12-10  3508.340088  3518.540039  3410.000000  3444.239990  3444.239990   \n2021-12-13  3440.000000  3442.000000  3382.600098  3391.350098  3391.350098   \n2021-12-14  3351.000000  3389.979980  3328.800049  3381.830078  3381.830078   \n2021-12-15  3371.959961  3472.000000  3303.899902  3466.300049  3466.300049   \n2021-12-16  3467.370117  3483.320068  3363.209961  3377.419922  3377.419922   \n2021-12-17  3354.209961  3417.969971  3312.270020  3400.350098  3400.350098   \n2021-12-20  3337.000000  3357.489990  3312.000000  3341.580078  3341.580078   \n2021-12-21  3357.010010  3414.330078  3312.949951  3408.340088  3408.340088   \n2021-12-22  3385.399902  3441.000000  3370.010010  3420.739990  3420.739990   \n2021-12-23  3408.560059  3439.500000  3403.000000  3421.370117  3421.370117   \n2021-12-27  3420.739990  3458.860107  3384.310059  3393.389893  3393.389893   \n2021-12-28  3403.649902  3443.520020  3382.709961  3413.219971  3413.219971   \n2021-12-29  3416.800049  3424.239990  3372.010010  3384.020020  3384.020020   \n2021-12-30  3394.000000  3417.760010  3370.479980  3372.889893  3372.889893   \n\n             Volume Stock_Code  \nDate                            \n2021-12-01  3745800       AMZN  \n2021-12-02  3236300       AMZN  \n2021-12-03  4032600       AMZN  \n2021-12-06  3443000       AMZN  \n2021-12-07  3320500       AMZN  \n2021-12-08  2262700       AMZN  \n2021-12-09  2303100       AMZN  \n2021-12-10  3031400       AMZN  \n2021-12-13  3108500       AMZN  \n2021-12-14  2798800       AMZN  \n2021-12-15  3789700       AMZN  \n2021-12-16  3043800       AMZN  \n2021-12-17  4277100       AMZN  \n2021-12-20  2868600       AMZN  \n2021-12-21  2797800       AMZN  \n2021-12-22  2751800       AMZN  \n2021-12-23  1839400       AMZN  \n2021-12-27  2934400       AMZN  \n2021-12-28  2731900       AMZN  \n2021-12-29  1787700       AMZN  \n2021-12-30  1879200       AMZN  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Adj Close</th>\n      <th>Volume</th>\n      <th>Stock_Code</th>\n    </tr>\n    <tr>\n      <th>Date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-12-01</th>\n      <td>3545.000000</td>\n      <td>3559.879883</td>\n      <td>3441.600098</td>\n      <td>3443.719971</td>\n      <td>3443.719971</td>\n      <td>3745800</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-02</th>\n      <td>3460.000000</td>\n      <td>3492.699951</td>\n      <td>3423.750000</td>\n      <td>3437.360107</td>\n      <td>3437.360107</td>\n      <td>3236300</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-03</th>\n      <td>3455.000000</td>\n      <td>3469.870117</td>\n      <td>3338.600098</td>\n      <td>3389.790039</td>\n      <td>3389.790039</td>\n      <td>4032600</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-06</th>\n      <td>3393.000000</td>\n      <td>3473.909912</td>\n      <td>3338.689941</td>\n      <td>3427.370117</td>\n      <td>3427.370117</td>\n      <td>3443000</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-07</th>\n      <td>3492.000000</td>\n      <td>3549.989990</td>\n      <td>3466.689941</td>\n      <td>3523.290039</td>\n      <td>3523.290039</td>\n      <td>3320500</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-08</th>\n      <td>3523.010010</td>\n      <td>3543.600098</td>\n      <td>3495.010010</td>\n      <td>3523.159912</td>\n      <td>3523.159912</td>\n      <td>2262700</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-09</th>\n      <td>3515.000000</td>\n      <td>3539.389893</td>\n      <td>3482.790039</td>\n      <td>3483.419922</td>\n      <td>3483.419922</td>\n      <td>2303100</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-10</th>\n      <td>3508.340088</td>\n      <td>3518.540039</td>\n      <td>3410.000000</td>\n      <td>3444.239990</td>\n      <td>3444.239990</td>\n      <td>3031400</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-13</th>\n      <td>3440.000000</td>\n      <td>3442.000000</td>\n      <td>3382.600098</td>\n      <td>3391.350098</td>\n      <td>3391.350098</td>\n      <td>3108500</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-14</th>\n      <td>3351.000000</td>\n      <td>3389.979980</td>\n      <td>3328.800049</td>\n      <td>3381.830078</td>\n      <td>3381.830078</td>\n      <td>2798800</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-15</th>\n      <td>3371.959961</td>\n      <td>3472.000000</td>\n      <td>3303.899902</td>\n      <td>3466.300049</td>\n      <td>3466.300049</td>\n      <td>3789700</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-16</th>\n      <td>3467.370117</td>\n      <td>3483.320068</td>\n      <td>3363.209961</td>\n      <td>3377.419922</td>\n      <td>3377.419922</td>\n      <td>3043800</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-17</th>\n      <td>3354.209961</td>\n      <td>3417.969971</td>\n      <td>3312.270020</td>\n      <td>3400.350098</td>\n      <td>3400.350098</td>\n      <td>4277100</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-20</th>\n      <td>3337.000000</td>\n      <td>3357.489990</td>\n      <td>3312.000000</td>\n      <td>3341.580078</td>\n      <td>3341.580078</td>\n      <td>2868600</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-21</th>\n      <td>3357.010010</td>\n      <td>3414.330078</td>\n      <td>3312.949951</td>\n      <td>3408.340088</td>\n      <td>3408.340088</td>\n      <td>2797800</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-22</th>\n      <td>3385.399902</td>\n      <td>3441.000000</td>\n      <td>3370.010010</td>\n      <td>3420.739990</td>\n      <td>3420.739990</td>\n      <td>2751800</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-23</th>\n      <td>3408.560059</td>\n      <td>3439.500000</td>\n      <td>3403.000000</td>\n      <td>3421.370117</td>\n      <td>3421.370117</td>\n      <td>1839400</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-27</th>\n      <td>3420.739990</td>\n      <td>3458.860107</td>\n      <td>3384.310059</td>\n      <td>3393.389893</td>\n      <td>3393.389893</td>\n      <td>2934400</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-28</th>\n      <td>3403.649902</td>\n      <td>3443.520020</td>\n      <td>3382.709961</td>\n      <td>3413.219971</td>\n      <td>3413.219971</td>\n      <td>2731900</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-29</th>\n      <td>3416.800049</td>\n      <td>3424.239990</td>\n      <td>3372.010010</td>\n      <td>3384.020020</td>\n      <td>3384.020020</td>\n      <td>1787700</td>\n      <td>AMZN</td>\n    </tr>\n    <tr>\n      <th>2021-12-30</th>\n      <td>3394.000000</td>\n      <td>3417.760010</td>\n      <td>3370.479980</td>\n      <td>3372.889893</td>\n      <td>3372.889893</td>\n      <td>1879200</td>\n      <td>AMZN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
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