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@firmai
Last active October 16, 2023 11:36
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tricks-of-the-trade.ipynb
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"%%capture\n",
"!pip install yfinance"
],
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"id": "X_Fk9-1OYkkm"
},
"execution_count": 1,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"With the following piece of code, we have a good looking panel dataset."
],
"metadata": {
"id": "dlkN8DfoaST7"
}
},
{
"cell_type": "code",
"source": [
"import pandas as pd\n",
"import warnings\n",
"\n",
"pd.set_option('display.max_columns', None)\n",
"warnings.simplefilter(action='ignore', category=FutureWarning)\n",
"\n",
"# convert time to timestamp\n",
"time_start = '2015-09-21'\n",
"time_end = '2022-01-22'\n",
"time_start = int(pd.to_datetime(time_start).timestamp())\n",
"time_end = int(pd.to_datetime(time_end).timestamp())\n",
"\n",
"yahoo_url = f'https://query1.finance.yahoo.com/v7/finance/download/{{}}?period1{time_start}=&period2={time_end}&interval=1d&events=history&includeAdjustedClose=true'\n",
"\n",
"tickers = ['AAPL','TSLA', 'JPM', 'MSFT']\n",
"\n",
"df_pricing = pd.DataFrame()\n",
"for ticker in tickers:\n",
" url = yahoo_url.format(ticker)\n",
" df_tmp = pd.read_csv(url)\n",
" df_tmp['Ticker'] = ticker\n",
" df_pricing = pd.concat([df_pricing, df_tmp])"
],
"metadata": {
"id": "RpBgtq2rZxJZ"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_pricing.head()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "QxaFZbEuaKnk",
"outputId": "86d4e9bd-06d6-49a8-dc60-f4fd025a9900"
},
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Open High Low Close Adj Close \\\n",
"0 2020-11-12 119.620003 120.529999 118.570000 119.209999 117.295494 \n",
"1 2020-11-13 119.440002 119.669998 117.870003 119.260002 117.344711 \n",
"2 2020-11-16 118.919998 120.989998 118.150002 120.300003 118.367989 \n",
"3 2020-11-17 119.550003 120.669998 118.959999 119.389999 117.472618 \n",
"4 2020-11-18 118.610001 119.820000 118.000000 118.029999 116.134445 \n",
"\n",
" Volume Ticker \n",
"0 103162300 AAPL \n",
"1 81581900 AAPL \n",
"2 91183000 AAPL \n",
"3 74271000 AAPL \n",
"4 76322100 AAPL "
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" <th>1</th>\n",
" <td>2020-11-13</td>\n",
" <td>119.440002</td>\n",
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" <td>117.870003</td>\n",
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" <td>AAPL</td>\n",
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" <th>2</th>\n",
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" <td>118.919998</td>\n",
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" <td>AAPL</td>\n",
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},
"metadata": {},
"execution_count": 3
}
]
},
{
"cell_type": "markdown",
"source": [
"Unfortunately the following piece of code produces a badly formatted dataset, even though the frame contains the same data."
],
"metadata": {
"id": "K4iIy6ljaXpX"
}
},
{
"cell_type": "code",
"source": [
"import numpy as np\n",
"import yfinance as yf\n",
"from pandas_datareader import data as pdr\n",
"\n",
"yf.pdr_override()\n",
"\n",
"df_pricing = pdr.get_data_yahoo(['AAPL','TSLA', 'JPM', 'MSFT'],\n",
" start='2015-09-21',\n",
" end='2022-02-28',\n",
" auto_adjust=False,) #import S&P data"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "SMry2WBnYS7q",
"outputId": "4c819c4a-8e44-4432-a020-b258ff2770d7"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[*********************100%%**********************] 4 of 4 completed\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"df_pricing.head()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 289
},
"id": "pkJhgYNUdO8r",
"outputId": "3aefc767-0919-418e-fa3b-02485b711db9"
},
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Adj Close Close \\\n",
" AAPL JPM MSFT TSLA AAPL JPM \n",
"Date \n",
"2015-09-21 26.144232 48.671604 39.015625 17.613333 28.8025 61.450001 \n",
"2015-09-22 25.733498 48.243889 38.829887 17.396000 28.3500 60.910000 \n",
"2015-09-23 25.942263 48.030037 38.803337 17.403999 28.5800 60.639999 \n",
"2015-09-24 26.096575 47.697388 38.838730 17.541332 28.7500 60.220001 \n",
"2015-09-25 26.030766 48.687431 38.865257 17.127333 28.6775 61.470001 \n",
"\n",
" High \\\n",
" MSFT TSLA AAPL JPM MSFT TSLA \n",
"Date \n",
"2015-09-21 44.110001 17.613333 28.842501 61.910000 44.470001 18.104668 \n",
"2015-09-22 43.900002 17.396000 28.545000 61.090000 44.049999 17.510000 \n",
"2015-09-23 43.869999 17.403999 28.680000 61.150002 44.169998 17.472000 \n",
"2015-09-24 43.910000 17.541332 28.875000 60.380001 44.130001 17.563334 \n",
"2015-09-25 43.939999 17.127333 29.172501 61.860001 44.730000 17.794001 \n",
"\n",
" Low Open \\\n",
" AAPL JPM MSFT TSLA AAPL JPM \n",
"Date \n",
"2015-09-21 28.415001 61.080002 43.599998 17.053333 28.417500 61.520000 \n",
"2015-09-22 28.129999 60.419998 43.310001 17.058001 28.344999 60.599998 \n",
"2015-09-23 28.325001 60.320000 43.509998 17.172001 28.407499 60.799999 \n",
"2015-09-24 28.092501 59.459999 43.270000 17.080667 28.312500 60.009998 \n",
"2015-09-25 28.504999 60.869999 43.759998 17.076668 29.110001 61.270000 \n",
"\n",
" Volume \n",
" MSFT TSLA AAPL JPM MSFT TSLA \n",
"Date \n",
"2015-09-21 43.619999 17.598667 200888000 13136400 26177200 91803000 \n",
"2015-09-22 43.380001 17.268667 201384800 14811900 28085900 54966000 \n",
"2015-09-23 43.930000 17.463333 143026800 11712200 17145200 39012000 \n",
"2015-09-24 43.450001 17.302000 200878000 17293400 27905600 51723000 \n",
"2015-09-25 44.480000 17.774000 224607600 18384300 29384600 56601000 "
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" <th>2015-09-21</th>\n",
" <td>26.144232</td>\n",
" <td>48.671604</td>\n",
" <td>39.015625</td>\n",
" <td>17.613333</td>\n",
" <td>28.8025</td>\n",
" <td>61.450001</td>\n",
" <td>44.110001</td>\n",
" <td>17.613333</td>\n",
" <td>28.842501</td>\n",
" <td>61.910000</td>\n",
" <td>44.470001</td>\n",
" <td>18.104668</td>\n",
" <td>28.415001</td>\n",
" <td>61.080002</td>\n",
" <td>43.599998</td>\n",
" <td>17.053333</td>\n",
" <td>28.417500</td>\n",
" <td>61.520000</td>\n",
" <td>43.619999</td>\n",
" <td>17.598667</td>\n",
" <td>200888000</td>\n",
" <td>13136400</td>\n",
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" <td>25.733498</td>\n",
" <td>48.243889</td>\n",
" <td>38.829887</td>\n",
" <td>17.396000</td>\n",
" <td>28.3500</td>\n",
" <td>60.910000</td>\n",
" <td>43.900002</td>\n",
" <td>17.396000</td>\n",
" <td>28.545000</td>\n",
" <td>61.090000</td>\n",
" <td>44.049999</td>\n",
" <td>17.510000</td>\n",
" <td>28.129999</td>\n",
" <td>60.419998</td>\n",
" <td>43.310001</td>\n",
" <td>17.058001</td>\n",
" <td>28.344999</td>\n",
" <td>60.599998</td>\n",
" <td>43.380001</td>\n",
" <td>17.268667</td>\n",
" <td>201384800</td>\n",
" <td>14811900</td>\n",
" <td>28085900</td>\n",
" <td>54966000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-09-23</th>\n",
" <td>25.942263</td>\n",
" <td>48.030037</td>\n",
" <td>38.803337</td>\n",
" <td>17.403999</td>\n",
" <td>28.5800</td>\n",
" <td>60.639999</td>\n",
" <td>43.869999</td>\n",
" <td>17.403999</td>\n",
" <td>28.680000</td>\n",
" <td>61.150002</td>\n",
" <td>44.169998</td>\n",
" <td>17.472000</td>\n",
" <td>28.325001</td>\n",
" <td>60.320000</td>\n",
" <td>43.509998</td>\n",
" <td>17.172001</td>\n",
" <td>28.407499</td>\n",
" <td>60.799999</td>\n",
" <td>43.930000</td>\n",
" <td>17.463333</td>\n",
" <td>143026800</td>\n",
" <td>11712200</td>\n",
" <td>17145200</td>\n",
" <td>39012000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-09-24</th>\n",
" <td>26.096575</td>\n",
" <td>47.697388</td>\n",
" <td>38.838730</td>\n",
" <td>17.541332</td>\n",
" <td>28.7500</td>\n",
" <td>60.220001</td>\n",
" <td>43.910000</td>\n",
" <td>17.541332</td>\n",
" <td>28.875000</td>\n",
" <td>60.380001</td>\n",
" <td>44.130001</td>\n",
" <td>17.563334</td>\n",
" <td>28.092501</td>\n",
" <td>59.459999</td>\n",
" <td>43.270000</td>\n",
" <td>17.080667</td>\n",
" <td>28.312500</td>\n",
" <td>60.009998</td>\n",
" <td>43.450001</td>\n",
" <td>17.302000</td>\n",
" <td>200878000</td>\n",
" <td>17293400</td>\n",
" <td>27905600</td>\n",
" <td>51723000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-09-25</th>\n",
" <td>26.030766</td>\n",
" <td>48.687431</td>\n",
" <td>38.865257</td>\n",
" <td>17.127333</td>\n",
" <td>28.6775</td>\n",
" <td>61.470001</td>\n",
" <td>43.939999</td>\n",
" <td>17.127333</td>\n",
" <td>29.172501</td>\n",
" <td>61.860001</td>\n",
" <td>44.730000</td>\n",
" <td>17.794001</td>\n",
" <td>28.504999</td>\n",
" <td>60.869999</td>\n",
" <td>43.759998</td>\n",
" <td>17.076668</td>\n",
" <td>29.110001</td>\n",
" <td>61.270000</td>\n",
" <td>44.480000</td>\n",
" <td>17.774000</td>\n",
" <td>224607600</td>\n",
" <td>18384300</td>\n",
" <td>29384600</td>\n",
" <td>56601000</td>\n",
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" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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"</div>\n",
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]
},
"metadata": {},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"source": [
"df_pricing = df_pricing.stack().reset_index().rename(columns={\"level_1\":\"Ticker\"}).sort_values([\"Ticker\",\"Date\"]); df_pricing.head()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "Khwy-5b5dHeH",
"outputId": "cd576882-5302-4e10-9bf3-6567b55e9d4e"
},
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low Open \\\n",
"0 2015-09-21 AAPL 26.144232 28.8025 28.842501 28.415001 28.417500 \n",
"4 2015-09-22 AAPL 25.733498 28.3500 28.545000 28.129999 28.344999 \n",
"8 2015-09-23 AAPL 25.942263 28.5800 28.680000 28.325001 28.407499 \n",
"12 2015-09-24 AAPL 26.096575 28.7500 28.875000 28.092501 28.312500 \n",
"16 2015-09-25 AAPL 26.030766 28.6775 29.172501 28.504999 29.110001 \n",
"\n",
" Volume \n",
"0 200888000 \n",
"4 201384800 \n",
"8 143026800 \n",
"12 200878000 \n",
"16 224607600 "
],
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" <td>28.3500</td>\n",
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" <th>8</th>\n",
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" <td>AAPL</td>\n",
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},
"metadata": {},
"execution_count": 6
}
]
},
{
"cell_type": "markdown",
"source": [
"After `sort_values`, we can see the index looks kind-off funny now, its best to order it from 0 consecutively 0,1,2,3 so let's reset the index"
],
"metadata": {
"id": "03EzdkJszLan"
}
},
{
"cell_type": "code",
"source": [
"df_pricing = df_pricing.reset_index(drop=True)"
],
"metadata": {
"id": "GH1IqiJOzT3P"
},
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_pricing"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "27KxdpvTzdrw",
"outputId": "13fe8eba-0869-44a9-c297-95f2370de6c6"
},
"execution_count": 8,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low \\\n",
"0 2015-09-21 AAPL 26.144232 28.802500 28.842501 28.415001 \n",
"1 2015-09-22 AAPL 25.733498 28.350000 28.545000 28.129999 \n",
"2 2015-09-23 AAPL 25.942263 28.580000 28.680000 28.325001 \n",
"3 2015-09-24 AAPL 26.096575 28.750000 28.875000 28.092501 \n",
"4 2015-09-25 AAPL 26.030766 28.677500 29.172501 28.504999 \n",
"... ... ... ... ... ... ... \n",
"6479 2022-02-18 TSLA 285.660004 285.660004 295.623322 279.203339 \n",
"6480 2022-02-22 TSLA 273.843323 273.843323 285.576660 267.033325 \n",
"6481 2022-02-23 TSLA 254.679993 254.679993 278.433319 253.520004 \n",
"6482 2022-02-24 TSLA 266.923340 266.923340 267.493347 233.333328 \n",
"6483 2022-02-25 TSLA 269.956665 269.956665 273.166656 260.799988 \n",
"\n",
" Open Volume \n",
"0 28.417500 200888000 \n",
"1 28.344999 201384800 \n",
"2 28.407499 143026800 \n",
"3 28.312500 200878000 \n",
"4 29.110001 224607600 \n",
"... ... ... \n",
"6479 295.333344 68501700 \n",
"6480 278.043335 83288100 \n",
"6481 276.809998 95256900 \n",
"6482 233.463333 135322200 \n",
"6483 269.743347 76067700 \n",
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},
"metadata": {},
"execution_count": 8
}
]
},
{
"cell_type": "markdown",
"source": [
"Let's create some features now that we have a panel dataset"
],
"metadata": {
"id": "9kS-63BOmMR5"
}
},
{
"cell_type": "code",
"source": [
"def col_join(df, win):\n",
" df.columns = [\"_\".join(x) for x in df.columns.ravel()]\n",
" return df.add_suffix(\"_rolling_{}\".format(win))\n",
"\n",
"def rolling_features(df_daily, features=[\"Close\"], windows=[7,14], functions=[\"mean\",\"std\"], method=False, ticker=False):\n",
"\n",
" if method == \"Fast\":\n",
" rolling_dfs = [df_daily[features].rolling(i) # 1. Create rolling window\n",
" .agg(functions).reset_index(drop=True) # 2. Apply function\n",
" for i in windows] # 3. For every window size\n",
" elif method ==\"Slow\":\n",
" rolling_dfs = [df_daily.groupby(ticker)[features].rolling(i)\n",
" .agg(functions).reset_index(drop=True)\n",
" for i in windows]\n",
"\n",
" rolling_dfs = [col_join(df, win) for df, win in zip(rolling_dfs,windows)] # piece of code to create pretty column names\n",
"\n",
" df_daily = pd.concat((df_daily.reset_index(drop=True), *rolling_dfs), axis=1)\n",
" return df_daily"
],
"metadata": {
"id": "xYTukCMOd0yB"
},
"execution_count": 9,
"outputs": []
},
{
"cell_type": "code",
"source": [
"ticker = \"Ticker\"\n",
"windows = [3, 4, 6, 8]\n",
"columns = [\"High\", \"Low\"]\n",
"functions=[\"mean\",\"std\",\"skew\",\"max\",\"min\",\"median\"]\n",
"\n",
"df_pricing_features = rolling_features(df_pricing, features=columns, windows=windows, functions=functions, method=\"Slow\", ticker=ticker)"
],
"metadata": {
"id": "2H9ObxVCptVP"
},
"execution_count": 10,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_pricing_features.head()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 287
},
"id": "LJi7CZcnrCL3",
"outputId": "14e8e9dc-6f72-4888-a868-34f9326106a1"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low Open \\\n",
"0 2015-09-21 AAPL 26.215746 28.8025 28.842501 28.415001 28.417500 \n",
"1 2015-09-22 AAPL 25.803885 28.3500 28.545000 28.129999 28.344999 \n",
"2 2015-09-23 AAPL 26.013227 28.5800 28.680000 28.325001 28.407499 \n",
"3 2015-09-24 AAPL 26.167961 28.7500 28.875000 28.092501 28.312500 \n",
"4 2015-09-25 AAPL 26.101976 28.6775 29.172501 28.504999 29.110001 \n",
"\n",
" Volume High_mean_rolling_3 High_std_rolling_3 High_skew_rolling_3 \\\n",
"0 200888000 NaN NaN NaN \n",
"1 201384800 NaN NaN NaN \n",
"2 143026800 28.689167 0.148962 0.275869 \n",
"3 200878000 28.700000 0.165907 0.534586 \n",
"4 224607600 28.909167 0.248022 0.608147 \n",
"\n",
" High_max_rolling_3 High_min_rolling_3 High_median_rolling_3 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 28.842501 28.545 28.680 \n",
"3 28.875000 28.545 28.680 \n",
"4 29.172501 28.680 28.875 \n",
"\n",
" Low_mean_rolling_3 Low_std_rolling_3 Low_skew_rolling_3 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 28.2900 0.145689 -1.018690 \n",
"3 28.1825 0.124825 1.557865 \n",
"4 28.3075 0.206805 -0.378078 \n",
"\n",
" Low_max_rolling_3 Low_min_rolling_3 Low_median_rolling_3 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
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"3 28.325001 28.092501 28.129999 \n",
"4 28.504999 28.092501 28.325001 \n",
"\n",
" High_mean_rolling_4 High_std_rolling_4 High_skew_rolling_4 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 28.735625 0.153057 -0.589555 \n",
"4 28.818125 0.272331 0.715527 \n",
"\n",
" High_max_rolling_4 High_min_rolling_4 High_median_rolling_4 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 28.875000 28.545 28.76125 \n",
"4 29.172501 28.545 28.77750 \n",
"\n",
" Low_mean_rolling_4 Low_std_rolling_4 Low_skew_rolling_4 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 28.240625 0.154602 0.234362 \n",
"4 28.263125 0.190759 0.678109 \n",
"\n",
" Low_max_rolling_4 Low_min_rolling_4 Low_median_rolling_4 \\\n",
"0 NaN NaN NaN \n",
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"2 NaN NaN NaN \n",
"3 28.415001 28.092501 28.2275 \n",
"4 28.504999 28.092501 28.2275 \n",
"\n",
" High_mean_rolling_6 High_std_rolling_6 High_skew_rolling_6 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
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"\n",
" High_max_rolling_6 High_min_rolling_6 High_median_rolling_6 \\\n",
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"1 NaN NaN NaN \n",
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"3 NaN NaN NaN \n",
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"\n",
" Low_mean_rolling_6 Low_std_rolling_6 Low_skew_rolling_6 \\\n",
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"\n",
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>Ticker</th>\n",
" <th>Adj Close</th>\n",
" <th>Close</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
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" <th>Low_max_rolling_3</th>\n",
" <th>Low_min_rolling_3</th>\n",
" <th>Low_median_rolling_3</th>\n",
" <th>High_mean_rolling_4</th>\n",
" <th>High_std_rolling_4</th>\n",
" <th>High_skew_rolling_4</th>\n",
" <th>High_max_rolling_4</th>\n",
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" <th>Low_min_rolling_4</th>\n",
" <th>Low_median_rolling_4</th>\n",
" <th>High_mean_rolling_6</th>\n",
" <th>High_std_rolling_6</th>\n",
" <th>High_skew_rolling_6</th>\n",
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-09-21</td>\n",
" <td>AAPL</td>\n",
" <td>26.215746</td>\n",
" <td>28.8025</td>\n",
" <td>28.842501</td>\n",
" <td>28.415001</td>\n",
" <td>28.417500</td>\n",
" <td>200888000</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>2015-09-22</td>\n",
" <td>AAPL</td>\n",
" <td>25.803885</td>\n",
" <td>28.3500</td>\n",
" <td>28.545000</td>\n",
" <td>28.129999</td>\n",
" <td>28.344999</td>\n",
" <td>201384800</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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]
},
"metadata": {},
"execution_count": 86
}
]
},
{
"cell_type": "code",
"source": [
"df_pricing_features[df_pricing_features[\"Ticker\"]==\"TSLA\"]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 488
},
"id": "XCRMRU43qomH",
"outputId": "06655e0b-1ac1-4d77-cc6f-eefc53819553"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low \\\n",
"4863 2015-09-21 TSLA 17.613333 17.613333 18.104668 17.053333 \n",
"4864 2015-09-22 TSLA 17.396000 17.396000 17.510000 17.058001 \n",
"4865 2015-09-23 TSLA 17.403999 17.403999 17.472000 17.172001 \n",
"4866 2015-09-24 TSLA 17.541332 17.541332 17.563334 17.080667 \n",
"4867 2015-09-25 TSLA 17.127333 17.127333 17.794001 17.076668 \n",
"... ... ... ... ... ... ... \n",
"6479 2022-02-18 TSLA 285.660004 285.660004 295.623322 279.203339 \n",
"6480 2022-02-22 TSLA 273.843323 273.843323 285.576660 267.033325 \n",
"6481 2022-02-23 TSLA 254.679993 254.679993 278.433319 253.520004 \n",
"6482 2022-02-24 TSLA 266.923340 266.923340 267.493347 233.333328 \n",
"6483 2022-02-25 TSLA 269.956665 269.956665 273.166656 260.799988 \n",
"\n",
" Open Volume High_mean_rolling_3 High_std_rolling_3 \\\n",
"4863 17.598667 91803000 NaN NaN \n",
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"4866 17.302000 51723000 17.515111 0.045881 \n",
"4867 17.774000 56601000 17.609778 0.165949 \n",
"... ... ... ... ... \n",
"6479 295.333344 68501700 303.533325 6.976599 \n",
"6480 278.043335 83288100 295.788879 10.295997 \n",
"6481 276.809998 95256900 286.544434 8.635768 \n",
"6482 233.463333 135322200 277.167775 9.107840 \n",
"6483 269.743347 76067700 273.031108 5.471245 \n",
"\n",
" High_skew_rolling_3 High_max_rolling_3 High_min_rolling_3 \\\n",
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"4864 NaN NaN NaN \n",
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"... ... ... ... \n",
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"6483 -0.111418 278.433319 267.493347 \n",
"\n",
" High_median_rolling_3 Low_mean_rolling_3 Low_std_rolling_3 \\\n",
"4863 NaN NaN NaN \n",
"4864 NaN NaN NaN \n",
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"4866 17.510000 17.103556 0.060349 \n",
"4867 17.563334 17.109779 0.053923 \n",
"... ... ... ... \n",
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"6481 285.576660 266.585556 12.847521 \n",
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"... ... ... ... \n",
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"4863 NaN NaN NaN \n",
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"4863 NaN NaN NaN \n",
"4864 NaN NaN NaN \n",
"4865 NaN NaN NaN \n",
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"6479 294.580002 303.868886 5.142155 \n",
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"4863 NaN NaN NaN \n",
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"6483 282.004990 264.209442 20.246131 \n",
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" Low_median_rolling_6 High_mean_rolling_8 High_std_rolling_8 \\\n",
"4863 NaN NaN NaN \n",
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"... ... ... ... \n",
"6479 287.875000 306.654999 6.749002 \n",
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"6481 285.285004 298.402912 11.178854 \n",
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"4863 NaN NaN NaN \n",
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"4864 NaN NaN NaN \n",
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"... ... ... ... \n",
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" <td>17.053333</td>\n",
" <td>17.058001</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4866</th>\n",
" <td>2015-09-24</td>\n",
" <td>TSLA</td>\n",
" <td>17.541332</td>\n",
" <td>17.541332</td>\n",
" <td>17.563334</td>\n",
" <td>17.080667</td>\n",
" <td>17.302000</td>\n",
" <td>51723000</td>\n",
" <td>17.515111</td>\n",
" <td>0.045881</td>\n",
" <td>0.495063</td>\n",
" <td>17.563334</td>\n",
" <td>17.472000</td>\n",
" <td>17.510000</td>\n",
" <td>17.103556</td>\n",
" <td>0.060349</td>\n",
" <td>1.461206</td>\n",
" <td>17.172001</td>\n",
" <td>17.058001</td>\n",
" <td>17.080667</td>\n",
" <td>17.662500</td>\n",
" <td>0.297149</td>\n",
" <td>1.906019</td>\n",
" <td>18.104668</td>\n",
" <td>17.472000</td>\n",
" <td>17.536667</td>\n",
" <td>17.091001</td>\n",
" <td>0.055304</td>\n",
" <td>1.737955</td>\n",
" <td>17.172001</td>\n",
" <td>17.053333</td>\n",
" <td>17.069334</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4867</th>\n",
" <td>2015-09-25</td>\n",
" <td>TSLA</td>\n",
" <td>17.127333</td>\n",
" <td>17.127333</td>\n",
" <td>17.794001</td>\n",
" <td>17.076668</td>\n",
" <td>17.774000</td>\n",
" <td>56601000</td>\n",
" <td>17.609778</td>\n",
" <td>0.165949</td>\n",
" <td>1.160781</td>\n",
" <td>17.794001</td>\n",
" <td>17.472000</td>\n",
" <td>17.563334</td>\n",
" <td>17.109779</td>\n",
" <td>0.053923</td>\n",
" <td>1.721296</td>\n",
" <td>17.172001</td>\n",
" <td>17.076668</td>\n",
" <td>17.080667</td>\n",
" <td>17.584834</td>\n",
" <td>0.144389</td>\n",
" <td>1.613532</td>\n",
" <td>17.794001</td>\n",
" <td>17.472000</td>\n",
" <td>17.536667</td>\n",
" <td>17.096834</td>\n",
" <td>0.051076</td>\n",
" <td>1.769746</td>\n",
" <td>17.172001</td>\n",
" <td>17.058001</td>\n",
" <td>17.078668</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>...</td>\n",
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" <tr>\n",
" <th>6479</th>\n",
" <td>2022-02-18</td>\n",
" <td>TSLA</td>\n",
" <td>285.660004</td>\n",
" <td>285.660004</td>\n",
" <td>295.623322</td>\n",
" <td>279.203339</td>\n",
" <td>295.333344</td>\n",
" <td>68501700</td>\n",
" <td>303.533325</td>\n",
" <td>6.976599</td>\n",
" <td>-1.456544</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>306.166656</td>\n",
" <td>290.324443</td>\n",
" <td>10.638350</td>\n",
" <td>-0.436628</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>291.366669</td>\n",
" <td>304.566658</td>\n",
" <td>6.059681</td>\n",
" <td>-1.812729</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>306.916656</td>\n",
" <td>292.191666</td>\n",
" <td>9.454932</td>\n",
" <td>-1.153258</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>294.580002</td>\n",
" <td>303.868886</td>\n",
" <td>5.142155</td>\n",
" <td>-0.984845</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>305.743332</td>\n",
" <td>289.452779</td>\n",
" <td>8.468042</td>\n",
" <td>0.241799</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>287.875000</td>\n",
" <td>306.654999</td>\n",
" <td>6.749002</td>\n",
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" <td>292.785416</td>\n",
" <td>9.675111</td>\n",
" <td>-0.087055</td>\n",
" <td>306.666656</td>\n",
" <td>279.203339</td>\n",
" <td>294.580002</td>\n",
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" <tr>\n",
" <th>6480</th>\n",
" <td>2022-02-22</td>\n",
" <td>TSLA</td>\n",
" <td>273.843323</td>\n",
" <td>273.843323</td>\n",
" <td>285.576660</td>\n",
" <td>267.033325</td>\n",
" <td>278.043335</td>\n",
" <td>83288100</td>\n",
" <td>295.788879</td>\n",
" <td>10.295997</td>\n",
" <td>0.072341</td>\n",
" <td>306.166656</td>\n",
" <td>285.576660</td>\n",
" <td>295.623322</td>\n",
" <td>279.201111</td>\n",
" <td>12.166672</td>\n",
" <td>-0.000824</td>\n",
" <td>291.366669</td>\n",
" <td>267.033325</td>\n",
" <td>279.203339</td>\n",
" <td>299.044159</td>\n",
" <td>10.632924</td>\n",
" <td>-0.659913</td>\n",
" <td>308.809998</td>\n",
" <td>285.576660</td>\n",
" <td>300.894989</td>\n",
" <td>284.501663</td>\n",
" <td>14.528203</td>\n",
" <td>-0.246670</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>285.285004</td>\n",
" <td>300.578328</td>\n",
" <td>8.941387</td>\n",
" <td>-1.011483</td>\n",
" <td>308.809998</td>\n",
" <td>285.576660</td>\n",
" <td>302.896667</td>\n",
" <td>286.697220</td>\n",
" <td>12.497726</td>\n",
" <td>-0.613790</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>287.875000</td>\n",
" <td>302.924164</td>\n",
" <td>9.062503</td>\n",
" <td>-0.945353</td>\n",
" <td>314.603333</td>\n",
" <td>285.576660</td>\n",
" <td>305.743332</td>\n",
" <td>287.831249</td>\n",
" <td>11.522559</td>\n",
" <td>-0.669967</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>287.875000</td>\n",
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" <tr>\n",
" <th>6481</th>\n",
" <td>2022-02-23</td>\n",
" <td>TSLA</td>\n",
" <td>254.679993</td>\n",
" <td>254.679993</td>\n",
" <td>278.433319</td>\n",
" <td>253.520004</td>\n",
" <td>276.809998</td>\n",
" <td>95256900</td>\n",
" <td>286.544434</td>\n",
" <td>8.635768</td>\n",
" <td>0.497962</td>\n",
" <td>295.623322</td>\n",
" <td>278.433319</td>\n",
" <td>285.576660</td>\n",
" <td>266.585556</td>\n",
" <td>12.847521</td>\n",
" <td>-0.156646</td>\n",
" <td>279.203339</td>\n",
" <td>253.520004</td>\n",
" <td>267.033325</td>\n",
" <td>291.449989</td>\n",
" <td>12.082035</td>\n",
" <td>0.322037</td>\n",
" <td>306.166656</td>\n",
" <td>278.433319</td>\n",
" <td>290.599991</td>\n",
" <td>272.780834</td>\n",
" <td>16.234688</td>\n",
" <td>-0.101296</td>\n",
" <td>291.366669</td>\n",
" <td>253.520004</td>\n",
" <td>273.118332</td>\n",
" <td>297.046102</td>\n",
" <td>12.762273</td>\n",
" <td>-0.631437</td>\n",
" <td>308.809998</td>\n",
" <td>278.433319</td>\n",
" <td>300.894989</td>\n",
" <td>281.553332</td>\n",
" <td>18.534195</td>\n",
" <td>-0.620976</td>\n",
" <td>300.403320</td>\n",
" <td>253.520004</td>\n",
" <td>285.285004</td>\n",
" <td>298.402912</td>\n",
" <td>11.178854</td>\n",
" <td>-1.005187</td>\n",
" <td>308.809998</td>\n",
" <td>278.433319</td>\n",
" <td>302.473343</td>\n",
" <td>282.158751</td>\n",
" <td>15.705832</td>\n",
" <td>-0.800698</td>\n",
" <td>300.403320</td>\n",
" <td>253.520004</td>\n",
" <td>283.975006</td>\n",
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" <tr>\n",
" <th>6482</th>\n",
" <td>2022-02-24</td>\n",
" <td>TSLA</td>\n",
" <td>266.923340</td>\n",
" <td>266.923340</td>\n",
" <td>267.493347</td>\n",
" <td>233.333328</td>\n",
" <td>233.463333</td>\n",
" <td>135322200</td>\n",
" <td>277.167775</td>\n",
" <td>9.107840</td>\n",
" <td>-0.613207</td>\n",
" <td>285.576660</td>\n",
" <td>267.493347</td>\n",
" <td>278.433319</td>\n",
" <td>251.295553</td>\n",
" <td>16.959764</td>\n",
" <td>-0.580069</td>\n",
" <td>267.033325</td>\n",
" <td>233.333328</td>\n",
" <td>253.520004</td>\n",
" <td>281.781662</td>\n",
" <td>11.851313</td>\n",
" <td>-0.099319</td>\n",
" <td>295.623322</td>\n",
" <td>267.493347</td>\n",
" <td>282.004990</td>\n",
" <td>258.272499</td>\n",
" <td>19.658760</td>\n",
" <td>-0.506867</td>\n",
" <td>279.203339</td>\n",
" <td>233.333328</td>\n",
" <td>260.276665</td>\n",
" <td>290.350550</td>\n",
" <td>16.161465</td>\n",
" <td>-0.238081</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>290.599991</td>\n",
" <td>270.809998</td>\n",
" <td>24.845513</td>\n",
" <td>-0.443312</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>273.118332</td>\n",
" <td>293.674580</td>\n",
" <td>15.134943</td>\n",
" <td>-0.749583</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>297.625000</td>\n",
" <td>275.879581</td>\n",
" <td>23.278525</td>\n",
" <td>-0.894656</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>281.793335</td>\n",
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" <tr>\n",
" <th>6483</th>\n",
" <td>2022-02-25</td>\n",
" <td>TSLA</td>\n",
" <td>269.956665</td>\n",
" <td>269.956665</td>\n",
" <td>273.166656</td>\n",
" <td>260.799988</td>\n",
" <td>269.743347</td>\n",
" <td>76067700</td>\n",
" <td>273.031108</td>\n",
" <td>5.471245</td>\n",
" <td>-0.111418</td>\n",
" <td>278.433319</td>\n",
" <td>267.493347</td>\n",
" <td>273.166656</td>\n",
" <td>249.217773</td>\n",
" <td>14.229766</td>\n",
" <td>-1.236165</td>\n",
" <td>260.799988</td>\n",
" <td>233.333328</td>\n",
" <td>253.520004</td>\n",
" <td>276.167496</td>\n",
" <td>7.700914</td>\n",
" <td>0.240825</td>\n",
" <td>285.576660</td>\n",
" <td>267.493347</td>\n",
" <td>275.799988</td>\n",
" <td>253.671661</td>\n",
" <td>14.640331</td>\n",
" <td>-1.203567</td>\n",
" <td>267.033325</td>\n",
" <td>233.333328</td>\n",
" <td>257.159996</td>\n",
" <td>284.409993</td>\n",
" <td>14.482806</td>\n",
" <td>0.516911</td>\n",
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" <td>233.333328</td>\n",
" <td>263.916656</td>\n",
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" <td>16.479842</td>\n",
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" <td>290.599991</td>\n",
" <td>272.931664</td>\n",
" <td>23.539592</td>\n",
" <td>-0.420350</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>273.118332</td>\n",
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]
},
"metadata": {},
"execution_count": 87
}
]
},
{
"cell_type": "code",
"source": [
"%%timeit\n",
"rolling_features(df_pricing, features=columns, windows=windows, functions=functions, method=\"Slow\", ticker=ticker)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "b4MfduqDrHUA",
"outputId": "9c3424a5-63e5-474d-b6e8-eee3717317ec"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"210 ms ± 8.08 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"### Append History\n",
"Is there a way to ignore the slow groupbys? Well one thing we can do is to create more historical data so that when we apply the rolling window the tickers don't overlap."
],
"metadata": {
"id": "KdmSvro_raJX"
}
},
{
"cell_type": "code",
"source": [
"## Beautiful offsets add to start\n",
"\n",
"from pandas.tseries.offsets import DateOffset\n",
"def range1(start, end):\n",
" return range(start, end+1)\n",
"\n",
"## Create old data for look\n",
"\n",
"from pandas.tseries.offsets import DateOffset\n",
"def range1(start, end):\n",
" return range(start, end+1)\n",
"\n",
"## Create old data for look\n",
"\n",
"def create_old(df_fund=None, id=\"ticker\", date=\"date\", window=24, gran=\"months\"):\n",
"\n",
" #with this function you have to make sure that everything has already been date-sorted.\n",
"\n",
" offsets = range1(1, window)\n",
" offsets = list(offsets)\n",
" offsets_list = []\n",
"\n",
" for off in offsets:\n",
" if gran==\"months\":\n",
" df_fund['date_old'] = df_fund[date] - DateOffset(months=off)\n",
" df_fund['date_old']=df_fund['date_old'] + pd.offsets.MonthEnd(0)\n",
" else:\n",
" df_fund['date_old'] = df_fund[date] - DateOffset(days=off)\n",
" df_old = df_fund[[\"date_old\",id]].groupby(id).first().reset_index()\n",
" df_old.columns = [id,date]\n",
" offsets_list.append(df_old)\n",
"\n",
" old_dates_df = pd.concat(offsets_list,axis=0)\n",
" df_fund = pd.concat((df_fund,old_dates_df),axis=0)\n",
" return df_fund\n",
"\n",
"# choose any number larger than your expected rolling window\n",
"\n",
"df_pricing_hist = create_old(df_pricing, ticker, \"Date\", 10, gran=\"days\")\n",
"df_pricing_hist = df_pricing_hist.sort_values([ticker,\"Date\"]).reset_index(drop=True)"
],
"metadata": {
"id": "fTPJhOSlr27_"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"### When you are working with very large window sizes, the following method might work better still.\n",
"\n",
"# import pandas as pd\n",
"# import numpy as np\n",
"\n",
"# def create_old(df_pricing, history_add= 370*5):\n",
"# df = pd.DataFrame({\"date\": pd.date_range(start=df_pricing[\"date\"].min()- pd.Timedelta(history_add, unit='D'),end=df_pricing[\"date\"].max(), freq=\"D\")[::-1]})\n",
"# df['key'] = 1\n",
"# # Convert list to dataframe & create 'key' columns\n",
"# li = df_pricing[\"ticker\"].unique()\n",
"# li_df = pd.DataFrame(li,columns=['ticker']).assign(key=1)\n",
"\n",
"# df = pd.merge(li_df,df,on='key').drop('key',axis=1)\n",
"\n",
"# df = pd.merge(df, df_pricing[[\"ticker\",\"date\"]].add_suffix(\"_old\"), left_on=[\"ticker\",\"date\"], right_on=[\"ticker_old\",\"date_old\"], how=\"left\")\n",
"# df.date_old = df[[\"ticker\",\"date_old\"]].groupby(\"ticker\").date_old.bfill()\n",
"# df[\"date_old\"] = df[\"date_old\"].fillna(df[\"date\"])\n",
"# df[\"equal\"] = df[\"date\"]==df[\"date_old\"]\n",
"# df = df[df[\"equal\"]==True]\n",
"\n",
"# df.ticker_old = np.where(df.ticker_old.isnull(), 1, 0)\n",
"# df['cumsum_col'] = df.groupby(['ticker'])['ticker_old'].cumsum()\n",
"\n",
"# df = df[df[\"cumsum_col\"]<history_add]\n",
"# df = df[[\"ticker\",\"date\"]]\n",
"\n",
"# df_pricing = pd.merge(df, df_pricing, on=[\"ticker\",\"date\"], how=\"left\")\n",
"# df_pricing = df_pricing.sort_values([\"ticker\",\"date\"])\n",
"\n",
"# return df_pricing"
],
"metadata": {
"id": "vHoGhQqS0Kvs"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_pricing_hist.head(20)"
],
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"base_uri": "https://localhost:8080/",
"height": 677
},
"id": "GFcSaog-seOH",
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{
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"text/plain": [
" Date Ticker Adj Close Close High Low Open \\\n",
"0 2014-11-30 AAPL NaN NaN NaN NaN NaN \n",
"1 2014-12-31 AAPL NaN NaN NaN NaN NaN \n",
"2 2015-01-31 AAPL NaN NaN NaN NaN NaN \n",
"3 2015-02-28 AAPL NaN NaN NaN NaN NaN \n",
"4 2015-03-31 AAPL NaN NaN NaN NaN NaN \n",
"5 2015-04-30 AAPL NaN NaN NaN NaN NaN \n",
"6 2015-05-31 AAPL NaN NaN NaN NaN NaN \n",
"7 2015-06-30 AAPL NaN NaN NaN NaN NaN \n",
"8 2015-07-31 AAPL NaN NaN NaN NaN NaN \n",
"9 2015-08-31 AAPL NaN NaN NaN NaN NaN \n",
"10 2015-09-21 AAPL 26.215746 28.802500 28.842501 28.415001 28.417500 \n",
"11 2015-09-22 AAPL 25.803885 28.350000 28.545000 28.129999 28.344999 \n",
"12 2015-09-23 AAPL 26.013227 28.580000 28.680000 28.325001 28.407499 \n",
"13 2015-09-24 AAPL 26.167961 28.750000 28.875000 28.092501 28.312500 \n",
"14 2015-09-25 AAPL 26.101976 28.677500 29.172501 28.504999 29.110001 \n",
"15 2015-09-28 AAPL 25.585443 28.110001 28.642500 28.110001 28.462500 \n",
"16 2015-09-29 AAPL 24.816328 27.264999 28.377501 26.965000 28.207500 \n",
"17 2015-09-30 AAPL 25.098488 27.575001 27.885000 27.182501 27.542500 \n",
"18 2015-10-01 AAPL 24.934654 27.395000 27.405001 26.827499 27.267500 \n",
"19 2015-10-02 AAPL 25.116686 27.594999 27.752501 26.887501 27.002501 \n",
"\n",
" Volume date_old \n",
"0 NaN NaT \n",
"1 NaN NaT \n",
"2 NaN NaT \n",
"3 NaN NaT \n",
"4 NaN NaT \n",
"5 NaN NaT \n",
"6 NaN NaT \n",
"7 NaN NaT \n",
"8 NaN NaT \n",
"9 NaN NaT \n",
"10 200888000.0 2014-11-30 \n",
"11 201384800.0 2014-11-30 \n",
"12 143026800.0 2014-11-30 \n",
"13 200878000.0 2014-11-30 \n",
"14 224607600.0 2014-11-30 \n",
"15 208436000.0 2014-11-30 \n",
"16 293461600.0 2014-11-30 \n",
"17 265892000.0 2014-11-30 \n",
"18 255716400.0 2014-12-31 \n",
"19 232079200.0 2014-12-31 "
],
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>27.182501</td>\n",
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" 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",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 90
}
]
},
{
"cell_type": "markdown",
"source": [
"Now let's apply the faster rolling algorithm, that doesn't need a groupby"
],
"metadata": {
"id": "Ysi_e6fdsjtQ"
}
},
{
"cell_type": "code",
"source": [
"%%timeit\n",
"rolling_features(df_pricing_hist, features=columns, windows=windows, functions=functions, method=\"Fast\", ticker=None)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "NpqUxQBlsoGg",
"outputId": "80c60cee-206f-4b33-a475-52506095b668"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"49.2 ms ± 1.17 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Compare this performance against 224 ms ± 6.61 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)"
],
"metadata": {
"id": "0DjhAnFSs_vv"
}
},
{
"cell_type": "code",
"source": [
"df_pricing_hist = rolling_features(df_pricing_hist, features=columns, windows=windows, functions=functions, method=\"Fast\", ticker=None)"
],
"metadata": {
"id": "i_0trzN4tDa_"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_pricing_hist.head(20)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 758
},
"id": "6Z9XaiQWtFFY",
"outputId": "ff32b2f9-d872-4270-a0f8-aeb3f8012767"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low Open \\\n",
"0 2014-11-30 AAPL NaN NaN NaN NaN NaN \n",
"1 2014-12-31 AAPL NaN NaN NaN NaN NaN \n",
"2 2015-01-31 AAPL NaN NaN NaN NaN NaN \n",
"3 2015-02-28 AAPL NaN NaN NaN NaN NaN \n",
"4 2015-03-31 AAPL NaN NaN NaN NaN NaN \n",
"5 2015-04-30 AAPL NaN NaN NaN NaN NaN \n",
"6 2015-05-31 AAPL NaN NaN NaN NaN NaN \n",
"7 2015-06-30 AAPL NaN NaN NaN NaN NaN \n",
"8 2015-07-31 AAPL NaN NaN NaN NaN NaN \n",
"9 2015-08-31 AAPL NaN NaN NaN NaN NaN \n",
"10 2015-09-21 AAPL 26.215746 28.802500 28.842501 28.415001 28.417500 \n",
"11 2015-09-22 AAPL 25.803885 28.350000 28.545000 28.129999 28.344999 \n",
"12 2015-09-23 AAPL 26.013227 28.580000 28.680000 28.325001 28.407499 \n",
"13 2015-09-24 AAPL 26.167961 28.750000 28.875000 28.092501 28.312500 \n",
"14 2015-09-25 AAPL 26.101976 28.677500 29.172501 28.504999 29.110001 \n",
"15 2015-09-28 AAPL 25.585443 28.110001 28.642500 28.110001 28.462500 \n",
"16 2015-09-29 AAPL 24.816328 27.264999 28.377501 26.965000 28.207500 \n",
"17 2015-09-30 AAPL 25.098488 27.575001 27.885000 27.182501 27.542500 \n",
"18 2015-10-01 AAPL 24.934654 27.395000 27.405001 26.827499 27.267500 \n",
"19 2015-10-02 AAPL 25.116686 27.594999 27.752501 26.887501 27.002501 \n",
"\n",
" Volume date_old High_mean_rolling_3 High_std_rolling_3 \\\n",
"0 NaN NaT NaN NaN \n",
"1 NaN NaT NaN NaN \n",
"2 NaN NaT NaN NaN \n",
"3 NaN NaT NaN NaN \n",
"4 NaN NaT NaN NaN \n",
"5 NaN NaT NaN NaN \n",
"6 NaN NaT NaN NaN \n",
"7 NaN NaT NaN NaN \n",
"8 NaN NaT NaN NaN \n",
"9 NaN NaT NaN NaN \n",
"10 200888000.0 2014-11-30 NaN NaN \n",
"11 201384800.0 2014-11-30 NaN NaN \n",
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"13 200878000.0 2014-11-30 28.700000 0.165907 \n",
"14 224607600.0 2014-11-30 28.909167 0.248022 \n",
"15 208436000.0 2014-11-30 28.896667 0.265664 \n",
"16 293461600.0 2014-11-30 28.730834 0.404794 \n",
"17 265892000.0 2014-11-30 28.301667 0.384401 \n",
"18 255716400.0 2014-12-31 27.889167 0.486263 \n",
"19 232079200.0 2014-12-31 27.680834 0.247895 \n",
"\n",
" High_skew_rolling_3 High_max_rolling_3 High_min_rolling_3 \\\n",
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"\n",
" High_median_rolling_3 Low_mean_rolling_3 Low_std_rolling_3 \\\n",
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"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
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"16 28.110001 28.766875 0.338282 \n",
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"\n",
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"2 NaN NaN NaN \n",
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"\n",
" Low_median_rolling_4 High_mean_rolling_6 High_std_rolling_6 \\\n",
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"6 NaN NaN NaN \n",
"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 28.227500 NaN NaN \n",
"14 28.227500 NaN NaN \n",
"15 28.217501 28.792917 0.223660 \n",
"16 28.101251 28.715417 0.277198 \n",
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"18 27.073750 28.392917 0.653704 \n",
"19 26.926250 28.205834 0.648748 \n",
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" High_skew_rolling_6 High_max_rolling_6 High_min_rolling_6 \\\n",
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"5 NaN NaN NaN \n",
"6 NaN NaN NaN \n",
"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 NaN NaN NaN \n",
"14 NaN NaN NaN \n",
"15 0.946157 29.172501 28.545000 \n",
"16 0.783024 29.172501 28.377501 \n",
"17 -0.641467 29.172501 27.885000 \n",
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" High_median_rolling_6 Low_mean_rolling_6 Low_std_rolling_6 \\\n",
"0 NaN NaN NaN \n",
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"5 NaN NaN NaN \n",
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"8 NaN NaN NaN \n",
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"11 NaN NaN NaN \n",
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"13 NaN NaN NaN \n",
"14 NaN NaN NaN \n",
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"16 28.66125 28.021250 0.541613 \n",
"17 28.66125 27.863334 0.633841 \n",
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" Low_skew_rolling_6 Low_max_rolling_6 Low_min_rolling_6 \\\n",
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"5 NaN NaN NaN \n",
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"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
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"13 NaN NaN NaN \n",
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" Low_median_rolling_6 High_mean_rolling_8 High_std_rolling_8 \\\n",
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"1 NaN NaN NaN \n",
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"5 NaN NaN NaN \n",
"6 NaN NaN NaN \n",
"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 NaN NaN NaN \n",
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"17 28.101251 28.627500 0.383238 \n",
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"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
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"5 NaN NaN NaN \n",
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"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 NaN NaN NaN \n",
"14 NaN NaN NaN \n",
"15 NaN NaN NaN \n",
"16 NaN NaN NaN \n",
"17 -0.806771 29.172501 27.885000 \n",
"18 -0.889841 29.172501 27.405001 \n",
"19 -0.322145 29.172501 27.405001 \n",
"\n",
" High_median_rolling_8 Low_mean_rolling_8 Low_std_rolling_8 \\\n",
"0 NaN NaN NaN \n",
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"15 NaN NaN NaN \n",
"16 NaN NaN NaN \n",
"17 28.66125 27.965625 0.573275 \n",
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" Low_skew_rolling_8 Low_max_rolling_8 Low_min_rolling_8 \\\n",
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"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
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"7 NaN NaN NaN \n",
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" Low_median_rolling_8 \n",
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"1 NaN \n",
"2 NaN \n",
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"9 NaN \n",
"10 NaN \n",
"11 NaN \n",
"12 NaN \n",
"13 NaN \n",
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"17 28.120000 \n",
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" <th>Date</th>\n",
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" <th>Adj Close</th>\n",
" <th>Close</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Open</th>\n",
" <th>Volume</th>\n",
" <th>date_old</th>\n",
" <th>High_mean_rolling_3</th>\n",
" <th>High_std_rolling_3</th>\n",
" <th>High_skew_rolling_3</th>\n",
" <th>High_max_rolling_3</th>\n",
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" <th>Low_min_rolling_3</th>\n",
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" <th>High_mean_rolling_4</th>\n",
" <th>High_std_rolling_4</th>\n",
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" <th>Low_max_rolling_4</th>\n",
" <th>Low_min_rolling_4</th>\n",
" <th>Low_median_rolling_4</th>\n",
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" <th>High_median_rolling_8</th>\n",
" <th>Low_mean_rolling_8</th>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2014-12-31</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015-01-31</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2015-02-28</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-03-31</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2015-04-30</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2015-05-31</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2015-06-30</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2015-07-31</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2015-08-31</td>\n",
" <td>AAPL</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2015-09-21</td>\n",
" <td>AAPL</td>\n",
" <td>26.215746</td>\n",
" <td>28.802500</td>\n",
" <td>28.842501</td>\n",
" <td>28.415001</td>\n",
" <td>28.417500</td>\n",
" <td>200888000.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2015-09-22</td>\n",
" <td>AAPL</td>\n",
" <td>25.803885</td>\n",
" <td>28.350000</td>\n",
" <td>28.545000</td>\n",
" <td>28.129999</td>\n",
" <td>28.344999</td>\n",
" <td>201384800.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2015-09-23</td>\n",
" <td>AAPL</td>\n",
" <td>26.013227</td>\n",
" <td>28.580000</td>\n",
" <td>28.680000</td>\n",
" <td>28.325001</td>\n",
" <td>28.407499</td>\n",
" <td>143026800.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.689167</td>\n",
" <td>0.148962</td>\n",
" <td>0.275869</td>\n",
" <td>28.842501</td>\n",
" <td>28.545000</td>\n",
" <td>28.680000</td>\n",
" <td>28.290000</td>\n",
" <td>0.145689</td>\n",
" <td>-1.018690</td>\n",
" <td>28.415001</td>\n",
" <td>28.129999</td>\n",
" <td>28.325001</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2015-09-24</td>\n",
" <td>AAPL</td>\n",
" <td>26.167961</td>\n",
" <td>28.750000</td>\n",
" <td>28.875000</td>\n",
" <td>28.092501</td>\n",
" <td>28.312500</td>\n",
" <td>200878000.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.700000</td>\n",
" <td>0.165907</td>\n",
" <td>0.534586</td>\n",
" <td>28.875000</td>\n",
" <td>28.545000</td>\n",
" <td>28.680000</td>\n",
" <td>28.182500</td>\n",
" <td>0.124825</td>\n",
" <td>1.557865</td>\n",
" <td>28.325001</td>\n",
" <td>28.092501</td>\n",
" <td>28.129999</td>\n",
" <td>28.735625</td>\n",
" <td>0.153057</td>\n",
" <td>-0.589555</td>\n",
" <td>28.875000</td>\n",
" <td>28.545000</td>\n",
" <td>28.76125</td>\n",
" <td>28.240625</td>\n",
" <td>0.154602</td>\n",
" <td>0.234362</td>\n",
" <td>28.415001</td>\n",
" <td>28.092501</td>\n",
" <td>28.227500</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2015-09-25</td>\n",
" <td>AAPL</td>\n",
" <td>26.101976</td>\n",
" <td>28.677500</td>\n",
" <td>29.172501</td>\n",
" <td>28.504999</td>\n",
" <td>29.110001</td>\n",
" <td>224607600.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.909167</td>\n",
" <td>0.248022</td>\n",
" <td>0.608147</td>\n",
" <td>29.172501</td>\n",
" <td>28.680000</td>\n",
" <td>28.875000</td>\n",
" <td>28.307500</td>\n",
" <td>0.206805</td>\n",
" <td>-0.378078</td>\n",
" <td>28.504999</td>\n",
" <td>28.092501</td>\n",
" <td>28.325001</td>\n",
" <td>28.818125</td>\n",
" <td>0.272331</td>\n",
" <td>0.715527</td>\n",
" <td>29.172501</td>\n",
" <td>28.545000</td>\n",
" <td>28.77750</td>\n",
" <td>28.263125</td>\n",
" <td>0.190759</td>\n",
" <td>0.678109</td>\n",
" <td>28.504999</td>\n",
" <td>28.092501</td>\n",
" <td>28.227500</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2015-09-28</td>\n",
" <td>AAPL</td>\n",
" <td>25.585443</td>\n",
" <td>28.110001</td>\n",
" <td>28.642500</td>\n",
" <td>28.110001</td>\n",
" <td>28.462500</td>\n",
" <td>208436000.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.896667</td>\n",
" <td>0.265664</td>\n",
" <td>0.364567</td>\n",
" <td>29.172501</td>\n",
" <td>28.642500</td>\n",
" <td>28.875000</td>\n",
" <td>28.235833</td>\n",
" <td>0.233268</td>\n",
" <td>1.721091</td>\n",
" <td>28.504999</td>\n",
" <td>28.092501</td>\n",
" <td>28.110001</td>\n",
" <td>28.842500</td>\n",
" <td>0.242462</td>\n",
" <td>1.107565</td>\n",
" <td>29.172501</td>\n",
" <td>28.642500</td>\n",
" <td>28.77750</td>\n",
" <td>28.258125</td>\n",
" <td>0.195611</td>\n",
" <td>0.672640</td>\n",
" <td>28.504999</td>\n",
" <td>28.092501</td>\n",
" <td>28.217501</td>\n",
" <td>28.792917</td>\n",
" <td>0.223660</td>\n",
" <td>0.946157</td>\n",
" <td>29.172501</td>\n",
" <td>28.545000</td>\n",
" <td>28.76125</td>\n",
" <td>28.262917</td>\n",
" <td>0.176454</td>\n",
" <td>0.386093</td>\n",
" <td>28.504999</td>\n",
" <td>28.092501</td>\n",
" <td>28.227500</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>2015-09-29</td>\n",
" <td>AAPL</td>\n",
" <td>24.816328</td>\n",
" <td>27.264999</td>\n",
" <td>28.377501</td>\n",
" <td>26.965000</td>\n",
" <td>28.207500</td>\n",
" <td>293461600.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.730834</td>\n",
" <td>0.404794</td>\n",
" <td>0.935223</td>\n",
" <td>29.172501</td>\n",
" <td>28.377501</td>\n",
" <td>28.642500</td>\n",
" <td>27.860000</td>\n",
" <td>0.799859</td>\n",
" <td>-1.269099</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.110001</td>\n",
" <td>28.766875</td>\n",
" <td>0.338282</td>\n",
" <td>0.121313</td>\n",
" <td>29.172501</td>\n",
" <td>28.377501</td>\n",
" <td>28.75875</td>\n",
" <td>27.918125</td>\n",
" <td>0.663348</td>\n",
" <td>-1.487680</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.101251</td>\n",
" <td>28.715417</td>\n",
" <td>0.277198</td>\n",
" <td>0.783024</td>\n",
" <td>29.172501</td>\n",
" <td>28.377501</td>\n",
" <td>28.66125</td>\n",
" <td>28.021250</td>\n",
" <td>0.541613</td>\n",
" <td>-1.954024</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.120000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2015-09-30</td>\n",
" <td>AAPL</td>\n",
" <td>25.098488</td>\n",
" <td>27.575001</td>\n",
" <td>27.885000</td>\n",
" <td>27.182501</td>\n",
" <td>27.542500</td>\n",
" <td>265892000.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.301667</td>\n",
" <td>0.384401</td>\n",
" <td>-0.853198</td>\n",
" <td>28.642500</td>\n",
" <td>27.885000</td>\n",
" <td>28.377501</td>\n",
" <td>27.419167</td>\n",
" <td>0.608083</td>\n",
" <td>1.486106</td>\n",
" <td>28.110001</td>\n",
" <td>26.965000</td>\n",
" <td>27.182501</td>\n",
" <td>28.519375</td>\n",
" <td>0.536747</td>\n",
" <td>0.096241</td>\n",
" <td>29.172501</td>\n",
" <td>27.885000</td>\n",
" <td>28.51000</td>\n",
" <td>27.690625</td>\n",
" <td>0.735709</td>\n",
" <td>0.168414</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>27.646251</td>\n",
" <td>28.605417</td>\n",
" <td>0.440941</td>\n",
" <td>-0.641467</td>\n",
" <td>29.172501</td>\n",
" <td>27.885000</td>\n",
" <td>28.66125</td>\n",
" <td>27.863334</td>\n",
" <td>0.633841</td>\n",
" <td>-0.766834</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.101251</td>\n",
" <td>28.627500</td>\n",
" <td>0.383238</td>\n",
" <td>-0.806771</td>\n",
" <td>29.172501</td>\n",
" <td>27.885000</td>\n",
" <td>28.66125</td>\n",
" <td>27.965625</td>\n",
" <td>0.573275</td>\n",
" <td>-1.191551</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.120000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2015-10-01</td>\n",
" <td>AAPL</td>\n",
" <td>24.934654</td>\n",
" <td>27.395000</td>\n",
" <td>27.405001</td>\n",
" <td>26.827499</td>\n",
" <td>27.267500</td>\n",
" <td>255716400.0</td>\n",
" <td>2014-12-31</td>\n",
" <td>27.889167</td>\n",
" <td>0.486263</td>\n",
" <td>0.038559</td>\n",
" <td>28.377501</td>\n",
" <td>27.405001</td>\n",
" <td>27.885000</td>\n",
" <td>26.991667</td>\n",
" <td>0.178997</td>\n",
" <td>0.655523</td>\n",
" <td>27.182501</td>\n",
" <td>26.827499</td>\n",
" <td>26.965000</td>\n",
" <td>28.077500</td>\n",
" <td>0.547277</td>\n",
" <td>-0.422628</td>\n",
" <td>28.642500</td>\n",
" <td>27.405001</td>\n",
" <td>28.13125</td>\n",
" <td>27.271250</td>\n",
" <td>0.577951</td>\n",
" <td>1.634311</td>\n",
" <td>28.110001</td>\n",
" <td>26.827499</td>\n",
" <td>27.073750</td>\n",
" <td>28.392917</td>\n",
" <td>0.653704</td>\n",
" <td>-0.530357</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.51000</td>\n",
" <td>27.613750</td>\n",
" <td>0.706376</td>\n",
" <td>0.085612</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.637501</td>\n",
" <td>28.447813</td>\n",
" <td>0.562911</td>\n",
" <td>-0.889841</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.59375</td>\n",
" <td>27.767188</td>\n",
" <td>0.663204</td>\n",
" <td>-0.553837</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>28.101251</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2015-10-02</td>\n",
" <td>AAPL</td>\n",
" <td>25.116686</td>\n",
" <td>27.594999</td>\n",
" <td>27.752501</td>\n",
" <td>26.887501</td>\n",
" <td>27.002501</td>\n",
" <td>232079200.0</td>\n",
" <td>2014-12-31</td>\n",
" <td>27.680834</td>\n",
" <td>0.247895</td>\n",
" <td>-1.192221</td>\n",
" <td>27.885000</td>\n",
" <td>27.405001</td>\n",
" <td>27.752501</td>\n",
" <td>26.965834</td>\n",
" <td>0.190022</td>\n",
" <td>1.539802</td>\n",
" <td>27.182501</td>\n",
" <td>26.827499</td>\n",
" <td>26.887501</td>\n",
" <td>27.855000</td>\n",
" <td>0.402870</td>\n",
" <td>0.514584</td>\n",
" <td>28.377501</td>\n",
" <td>27.405001</td>\n",
" <td>27.81875</td>\n",
" <td>26.965625</td>\n",
" <td>0.155153</td>\n",
" <td>1.265287</td>\n",
" <td>27.182501</td>\n",
" <td>26.827499</td>\n",
" <td>26.926250</td>\n",
" <td>28.205834</td>\n",
" <td>0.648748</td>\n",
" <td>0.386565</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.13125</td>\n",
" <td>27.412917</td>\n",
" <td>0.714292</td>\n",
" <td>0.982397</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.073750</td>\n",
" <td>28.348750</td>\n",
" <td>0.611040</td>\n",
" <td>-0.322145</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.51000</td>\n",
" <td>27.611875</td>\n",
" <td>0.709942</td>\n",
" <td>0.051731</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.637501</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-f7dff90f-18c1-4910-8ad8-c08d424c7c7e');\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",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 93
}
]
},
{
"cell_type": "markdown",
"source": [
"However, we now realise that we have these 10 additional empty rows, what shall we do with them? Well we can just cut them off."
],
"metadata": {
"id": "1vy1d-adtNLh"
}
},
{
"cell_type": "code",
"source": [
"df_pricing_hist.dropna()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 488
},
"id": "fvebKD7ut9se",
"outputId": "b69b18aa-0e49-4240-a8e5-0b41a24d672f"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low \\\n",
"17 2015-09-30 AAPL 25.098488 27.575001 27.885000 27.182501 \n",
"18 2015-10-01 AAPL 24.934654 27.395000 27.405001 26.827499 \n",
"19 2015-10-02 AAPL 25.116686 27.594999 27.752501 26.887501 \n",
"20 2015-10-05 AAPL 25.207710 27.695000 27.842501 27.267500 \n",
"21 2015-10-06 AAPL 25.328310 27.827499 27.934999 27.442499 \n",
"... ... ... ... ... ... ... \n",
"6519 2022-02-18 TSLA 285.660004 285.660004 295.623322 279.203339 \n",
"6520 2022-02-22 TSLA 273.843323 273.843323 285.576660 267.033325 \n",
"6521 2022-02-23 TSLA 254.679993 254.679993 278.433319 253.520004 \n",
"6522 2022-02-24 TSLA 266.923340 266.923340 267.493347 233.333328 \n",
"6523 2022-02-25 TSLA 269.956665 269.956665 273.166656 260.799988 \n",
"\n",
" Open Volume date_old High_mean_rolling_3 \\\n",
"17 27.542500 265892000.0 2014-11-30 28.301667 \n",
"18 27.267500 255716400.0 2014-12-31 27.889167 \n",
"19 27.002501 232079200.0 2014-12-31 27.680834 \n",
"20 27.469999 208258800.0 2014-12-31 27.666667 \n",
"21 27.657499 192787200.0 2014-12-31 27.843334 \n",
"... ... ... ... ... \n",
"6519 295.333344 68501700.0 2021-04-30 303.533325 \n",
"6520 278.043335 83288100.0 2021-04-30 295.788879 \n",
"6521 276.809998 95256900.0 2021-04-30 286.544434 \n",
"6522 233.463333 135322200.0 2021-04-30 277.167775 \n",
"6523 269.743347 76067700.0 2021-04-30 273.031108 \n",
"\n",
" High_std_rolling_3 High_skew_rolling_3 High_max_rolling_3 \\\n",
"17 0.384401 -0.853198 28.642500 \n",
"18 0.486263 0.038559 28.377501 \n",
"19 0.247895 -1.192221 27.885000 \n",
"20 0.231035 -1.441072 27.842501 \n",
"21 0.091252 0.041068 27.934999 \n",
"... ... ... ... \n",
"6519 6.976599 -1.456544 308.809998 \n",
"6520 10.295997 0.072341 306.166656 \n",
"6521 8.635768 0.497962 295.623322 \n",
"6522 9.107840 -0.613207 285.576660 \n",
"6523 5.471245 -0.111418 278.433319 \n",
"\n",
" High_min_rolling_3 High_median_rolling_3 Low_mean_rolling_3 \\\n",
"17 27.885000 28.377501 27.419167 \n",
"18 27.405001 27.885000 26.991667 \n",
"19 27.405001 27.752501 26.965834 \n",
"20 27.405001 27.752501 26.994167 \n",
"21 27.752501 27.842501 27.199167 \n",
"... ... ... ... \n",
"6519 295.623322 306.166656 290.324443 \n",
"6520 285.576660 295.623322 279.201111 \n",
"6521 278.433319 285.576660 266.585556 \n",
"6522 267.493347 278.433319 251.295553 \n",
"6523 267.493347 273.166656 249.217773 \n",
"\n",
" Low_std_rolling_3 Low_skew_rolling_3 Low_max_rolling_3 \\\n",
"17 0.608083 1.486106 28.110001 \n",
"18 0.178997 0.655523 27.182501 \n",
"19 0.190022 1.539802 27.182501 \n",
"20 0.238607 1.609649 27.267500 \n",
"21 0.283739 -1.020885 27.442499 \n",
"... ... ... ... \n",
"6519 10.638350 -0.436628 300.403320 \n",
"6520 12.166672 -0.000824 291.366669 \n",
"6521 12.847521 -0.156646 279.203339 \n",
"6522 16.959764 -0.580069 267.033325 \n",
"6523 14.229766 -1.236165 260.799988 \n",
"\n",
" Low_min_rolling_3 Low_median_rolling_3 High_mean_rolling_4 \\\n",
"17 26.965000 27.182501 28.519375 \n",
"18 26.827499 26.965000 28.077500 \n",
"19 26.827499 26.887501 27.855000 \n",
"20 26.827499 26.887501 27.721251 \n",
"21 26.887501 27.267500 27.733750 \n",
"... ... ... ... \n",
"6519 279.203339 291.366669 304.566658 \n",
"6520 267.033325 279.203339 299.044159 \n",
"6521 253.520004 267.033325 291.449989 \n",
"6522 233.333328 253.520004 281.781662 \n",
"6523 233.333328 253.520004 276.167496 \n",
"\n",
" High_std_rolling_4 High_skew_rolling_4 High_max_rolling_4 \\\n",
"17 0.536747 0.096241 29.172501 \n",
"18 0.547277 -0.422628 28.642500 \n",
"19 0.402870 0.514584 28.377501 \n",
"20 0.217950 -1.637233 27.885000 \n",
"21 0.231485 -1.402027 27.934999 \n",
"... ... ... ... \n",
"6519 6.059681 -1.812729 308.809998 \n",
"6520 10.632924 -0.659913 308.809998 \n",
"6521 12.082035 0.322037 306.166656 \n",
"6522 11.851313 -0.099319 295.623322 \n",
"6523 7.700914 0.240825 285.576660 \n",
"\n",
" High_min_rolling_4 High_median_rolling_4 Low_mean_rolling_4 \\\n",
"17 27.885000 28.510000 27.690625 \n",
"18 27.405001 28.131250 27.271250 \n",
"19 27.405001 27.818750 26.965625 \n",
"20 27.405001 27.797501 27.041250 \n",
"21 27.405001 27.797501 27.106250 \n",
"... ... ... ... \n",
"6519 295.623322 306.916656 292.191666 \n",
"6520 285.576660 300.894989 284.501663 \n",
"6521 278.433319 290.599991 272.780834 \n",
"6522 267.493347 282.004990 258.272499 \n",
"6523 267.493347 275.799988 253.671661 \n",
"\n",
" Low_std_rolling_4 Low_skew_rolling_4 Low_max_rolling_4 \\\n",
"17 0.735709 0.168414 28.504999 \n",
"18 0.577951 1.634311 28.110001 \n",
"19 0.155153 1.265287 27.182501 \n",
"20 0.216386 0.065737 27.267500 \n",
"21 0.296995 0.256610 27.442499 \n",
"... ... ... ... \n",
"6519 9.454932 -1.153258 300.403320 \n",
"6520 14.528203 -0.246670 300.403320 \n",
"6521 16.234688 -0.101296 291.366669 \n",
"6522 19.658760 -0.506867 279.203339 \n",
"6523 14.640331 -1.203567 267.033325 \n",
"\n",
" Low_min_rolling_4 Low_median_rolling_4 High_mean_rolling_6 \\\n",
"17 26.965000 27.646251 28.605417 \n",
"18 26.827499 27.073750 28.392917 \n",
"19 26.827499 26.926250 28.205834 \n",
"20 26.827499 27.035001 27.984167 \n",
"21 26.827499 27.077500 27.866250 \n",
"... ... ... ... \n",
"6519 279.203339 294.580002 303.868886 \n",
"6520 267.033325 285.285004 300.578328 \n",
"6521 253.520004 273.118332 297.046102 \n",
"6522 233.333328 260.276665 290.350550 \n",
"6523 233.333328 257.159996 284.409993 \n",
"\n",
" High_std_rolling_6 High_skew_rolling_6 High_max_rolling_6 \\\n",
"17 0.440941 -0.641467 29.172501 \n",
"18 0.653704 -0.530357 29.172501 \n",
"19 0.648748 0.386565 29.172501 \n",
"20 0.448803 0.450175 28.642500 \n",
"21 0.313914 0.333072 28.377501 \n",
"... ... ... ... \n",
"6519 5.142155 -0.984845 308.809998 \n",
"6520 8.941387 -1.011483 308.809998 \n",
"6521 12.762273 -0.631437 308.809998 \n",
"6522 16.161465 -0.238081 308.809998 \n",
"6523 14.482806 0.516911 306.166656 \n",
"\n",
" High_min_rolling_6 High_median_rolling_6 Low_mean_rolling_6 \\\n",
"17 27.885000 28.661250 27.863334 \n",
"18 27.405001 28.510000 27.613750 \n",
"19 27.405001 28.131250 27.412917 \n",
"20 27.405001 27.863750 27.206667 \n",
"21 27.405001 27.863750 27.095417 \n",
"... ... ... ... \n",
"6519 295.623322 305.743332 289.452779 \n",
"6520 285.576660 302.896667 286.697220 \n",
"6521 278.433319 300.894989 281.553332 \n",
"6522 267.493347 290.599991 270.809998 \n",
"6523 267.493347 282.004990 264.209442 \n",
"\n",
" Low_std_rolling_6 Low_skew_rolling_6 Low_max_rolling_6 \\\n",
"17 0.633841 -0.766834 28.504999 \n",
"18 0.706376 0.085612 28.504999 \n",
"19 0.714292 0.982397 28.504999 \n",
"20 0.474201 1.789900 28.110001 \n",
"21 0.240699 0.368532 27.442499 \n",
"... ... ... ... \n",
"6519 8.468042 0.241799 300.403320 \n",
"6520 12.497726 -0.613790 300.403320 \n",
"6521 18.534195 -0.620976 300.403320 \n",
"6522 24.845513 -0.443312 300.403320 \n",
"6523 20.246131 -0.262949 291.366669 \n",
"\n",
" Low_min_rolling_6 Low_median_rolling_6 High_mean_rolling_8 \\\n",
"17 26.965000 28.101251 28.627500 \n",
"18 26.827499 27.637501 28.447813 \n",
"19 26.827499 27.073750 28.348750 \n",
"20 26.827499 27.073750 28.244063 \n",
"21 26.827499 27.073750 28.126563 \n",
"... ... ... ... \n",
"6519 279.203339 287.875000 306.654999 \n",
"6520 267.033325 287.875000 302.924164 \n",
"6521 253.520004 285.285004 298.402912 \n",
"6522 233.333328 273.118332 293.674580 \n",
"6523 233.333328 263.916656 290.367077 \n",
"\n",
" High_std_rolling_8 High_skew_rolling_8 High_max_rolling_8 \\\n",
"17 0.383238 -0.806771 29.172501 \n",
"18 0.562911 -0.889841 29.172501 \n",
"19 0.611040 -0.322145 29.172501 \n",
"20 0.617885 0.239458 29.172501 \n",
"21 0.568137 0.857231 29.172501 \n",
"... ... ... ... \n",
"6519 6.749002 -0.312829 315.423340 \n",
"6520 9.062503 -0.945353 314.603333 \n",
"6521 11.178854 -1.005187 308.809998 \n",
"6522 15.134943 -0.749583 308.809998 \n",
"6523 16.479842 -0.141558 308.809998 \n",
"\n",
" High_min_rolling_8 High_median_rolling_8 Low_mean_rolling_8 \\\n",
"17 27.885000 28.661250 27.965625 \n",
"18 27.405001 28.593750 27.767188 \n",
"19 27.405001 28.510000 27.611875 \n",
"20 27.405001 28.131250 27.479688 \n",
"21 27.405001 27.910000 27.398438 \n",
"... ... ... ... \n",
"6519 295.623322 306.916656 292.785416 \n",
"6520 285.576660 305.743332 287.831249 \n",
"6521 278.433319 302.473343 282.158751 \n",
"6522 267.493347 297.625000 275.879581 \n",
"6523 267.493347 290.599991 272.931664 \n",
"\n",
" Low_std_rolling_8 Low_skew_rolling_8 Low_max_rolling_8 \\\n",
"17 0.573275 -1.191551 28.504999 \n",
"18 0.663204 -0.553837 28.504999 \n",
"19 0.709942 0.051731 28.504999 \n",
"20 0.654477 0.612324 28.504999 \n",
"21 0.606089 1.113967 28.504999 \n",
"... ... ... ... \n",
"6519 9.675111 -0.087055 306.666656 \n",
"6520 11.522559 -0.669967 300.403320 \n",
"6521 15.705832 -0.800698 300.403320 \n",
"6522 23.278525 -0.894656 300.403320 \n",
"6523 23.539592 -0.420350 300.403320 \n",
"\n",
" Low_min_rolling_8 Low_median_rolling_8 \n",
"17 26.965000 28.120000 \n",
"18 26.827499 28.101251 \n",
"19 26.827499 27.637501 \n",
"20 26.827499 27.225000 \n",
"21 26.827499 27.225000 \n",
"... ... ... \n",
"6519 279.203339 294.580002 \n",
"6520 267.033325 287.875000 \n",
"6521 253.520004 283.975006 \n",
"6522 233.333328 281.793335 \n",
"6523 233.333328 273.118332 \n",
"\n",
"[6456 rows x 57 columns]"
],
"text/html": [
"\n",
" <div id=\"df-b7c0f567-869f-4ded-9d9b-42219c3e8f8e\">\n",
" <div 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>Date</th>\n",
" <th>Ticker</th>\n",
" <th>Adj Close</th>\n",
" <th>Close</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Open</th>\n",
" <th>Volume</th>\n",
" <th>date_old</th>\n",
" <th>High_mean_rolling_3</th>\n",
" <th>High_std_rolling_3</th>\n",
" <th>High_skew_rolling_3</th>\n",
" <th>High_max_rolling_3</th>\n",
" <th>High_min_rolling_3</th>\n",
" <th>High_median_rolling_3</th>\n",
" <th>Low_mean_rolling_3</th>\n",
" <th>Low_std_rolling_3</th>\n",
" <th>Low_skew_rolling_3</th>\n",
" <th>Low_max_rolling_3</th>\n",
" <th>Low_min_rolling_3</th>\n",
" <th>Low_median_rolling_3</th>\n",
" <th>High_mean_rolling_4</th>\n",
" <th>High_std_rolling_4</th>\n",
" <th>High_skew_rolling_4</th>\n",
" <th>High_max_rolling_4</th>\n",
" <th>High_min_rolling_4</th>\n",
" <th>High_median_rolling_4</th>\n",
" <th>Low_mean_rolling_4</th>\n",
" <th>Low_std_rolling_4</th>\n",
" <th>Low_skew_rolling_4</th>\n",
" <th>Low_max_rolling_4</th>\n",
" <th>Low_min_rolling_4</th>\n",
" <th>Low_median_rolling_4</th>\n",
" <th>High_mean_rolling_6</th>\n",
" <th>High_std_rolling_6</th>\n",
" <th>High_skew_rolling_6</th>\n",
" <th>High_max_rolling_6</th>\n",
" <th>High_min_rolling_6</th>\n",
" <th>High_median_rolling_6</th>\n",
" <th>Low_mean_rolling_6</th>\n",
" <th>Low_std_rolling_6</th>\n",
" <th>Low_skew_rolling_6</th>\n",
" <th>Low_max_rolling_6</th>\n",
" <th>Low_min_rolling_6</th>\n",
" <th>Low_median_rolling_6</th>\n",
" <th>High_mean_rolling_8</th>\n",
" <th>High_std_rolling_8</th>\n",
" <th>High_skew_rolling_8</th>\n",
" <th>High_max_rolling_8</th>\n",
" <th>High_min_rolling_8</th>\n",
" <th>High_median_rolling_8</th>\n",
" <th>Low_mean_rolling_8</th>\n",
" <th>Low_std_rolling_8</th>\n",
" <th>Low_skew_rolling_8</th>\n",
" <th>Low_max_rolling_8</th>\n",
" <th>Low_min_rolling_8</th>\n",
" <th>Low_median_rolling_8</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2015-09-30</td>\n",
" <td>AAPL</td>\n",
" <td>25.098488</td>\n",
" <td>27.575001</td>\n",
" <td>27.885000</td>\n",
" <td>27.182501</td>\n",
" <td>27.542500</td>\n",
" <td>265892000.0</td>\n",
" <td>2014-11-30</td>\n",
" <td>28.301667</td>\n",
" <td>0.384401</td>\n",
" <td>-0.853198</td>\n",
" <td>28.642500</td>\n",
" <td>27.885000</td>\n",
" <td>28.377501</td>\n",
" <td>27.419167</td>\n",
" <td>0.608083</td>\n",
" <td>1.486106</td>\n",
" <td>28.110001</td>\n",
" <td>26.965000</td>\n",
" <td>27.182501</td>\n",
" <td>28.519375</td>\n",
" <td>0.536747</td>\n",
" <td>0.096241</td>\n",
" <td>29.172501</td>\n",
" <td>27.885000</td>\n",
" <td>28.510000</td>\n",
" <td>27.690625</td>\n",
" <td>0.735709</td>\n",
" <td>0.168414</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>27.646251</td>\n",
" <td>28.605417</td>\n",
" <td>0.440941</td>\n",
" <td>-0.641467</td>\n",
" <td>29.172501</td>\n",
" <td>27.885000</td>\n",
" <td>28.661250</td>\n",
" <td>27.863334</td>\n",
" <td>0.633841</td>\n",
" <td>-0.766834</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.101251</td>\n",
" <td>28.627500</td>\n",
" <td>0.383238</td>\n",
" <td>-0.806771</td>\n",
" <td>29.172501</td>\n",
" <td>27.885000</td>\n",
" <td>28.661250</td>\n",
" <td>27.965625</td>\n",
" <td>0.573275</td>\n",
" <td>-1.191551</td>\n",
" <td>28.504999</td>\n",
" <td>26.965000</td>\n",
" <td>28.120000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2015-10-01</td>\n",
" <td>AAPL</td>\n",
" <td>24.934654</td>\n",
" <td>27.395000</td>\n",
" <td>27.405001</td>\n",
" <td>26.827499</td>\n",
" <td>27.267500</td>\n",
" <td>255716400.0</td>\n",
" <td>2014-12-31</td>\n",
" <td>27.889167</td>\n",
" <td>0.486263</td>\n",
" <td>0.038559</td>\n",
" <td>28.377501</td>\n",
" <td>27.405001</td>\n",
" <td>27.885000</td>\n",
" <td>26.991667</td>\n",
" <td>0.178997</td>\n",
" <td>0.655523</td>\n",
" <td>27.182501</td>\n",
" <td>26.827499</td>\n",
" <td>26.965000</td>\n",
" <td>28.077500</td>\n",
" <td>0.547277</td>\n",
" <td>-0.422628</td>\n",
" <td>28.642500</td>\n",
" <td>27.405001</td>\n",
" <td>28.131250</td>\n",
" <td>27.271250</td>\n",
" <td>0.577951</td>\n",
" <td>1.634311</td>\n",
" <td>28.110001</td>\n",
" <td>26.827499</td>\n",
" <td>27.073750</td>\n",
" <td>28.392917</td>\n",
" <td>0.653704</td>\n",
" <td>-0.530357</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.510000</td>\n",
" <td>27.613750</td>\n",
" <td>0.706376</td>\n",
" <td>0.085612</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.637501</td>\n",
" <td>28.447813</td>\n",
" <td>0.562911</td>\n",
" <td>-0.889841</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.593750</td>\n",
" <td>27.767188</td>\n",
" <td>0.663204</td>\n",
" <td>-0.553837</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>28.101251</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2015-10-02</td>\n",
" <td>AAPL</td>\n",
" <td>25.116686</td>\n",
" <td>27.594999</td>\n",
" <td>27.752501</td>\n",
" <td>26.887501</td>\n",
" <td>27.002501</td>\n",
" <td>232079200.0</td>\n",
" <td>2014-12-31</td>\n",
" <td>27.680834</td>\n",
" <td>0.247895</td>\n",
" <td>-1.192221</td>\n",
" <td>27.885000</td>\n",
" <td>27.405001</td>\n",
" <td>27.752501</td>\n",
" <td>26.965834</td>\n",
" <td>0.190022</td>\n",
" <td>1.539802</td>\n",
" <td>27.182501</td>\n",
" <td>26.827499</td>\n",
" <td>26.887501</td>\n",
" <td>27.855000</td>\n",
" <td>0.402870</td>\n",
" <td>0.514584</td>\n",
" <td>28.377501</td>\n",
" <td>27.405001</td>\n",
" <td>27.818750</td>\n",
" <td>26.965625</td>\n",
" <td>0.155153</td>\n",
" <td>1.265287</td>\n",
" <td>27.182501</td>\n",
" <td>26.827499</td>\n",
" <td>26.926250</td>\n",
" <td>28.205834</td>\n",
" <td>0.648748</td>\n",
" <td>0.386565</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.131250</td>\n",
" <td>27.412917</td>\n",
" <td>0.714292</td>\n",
" <td>0.982397</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.073750</td>\n",
" <td>28.348750</td>\n",
" <td>0.611040</td>\n",
" <td>-0.322145</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.510000</td>\n",
" <td>27.611875</td>\n",
" <td>0.709942</td>\n",
" <td>0.051731</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.637501</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>2015-10-05</td>\n",
" <td>AAPL</td>\n",
" <td>25.207710</td>\n",
" <td>27.695000</td>\n",
" <td>27.842501</td>\n",
" <td>27.267500</td>\n",
" <td>27.469999</td>\n",
" <td>208258800.0</td>\n",
" <td>2014-12-31</td>\n",
" <td>27.666667</td>\n",
" <td>0.231035</td>\n",
" <td>-1.441072</td>\n",
" <td>27.842501</td>\n",
" <td>27.405001</td>\n",
" <td>27.752501</td>\n",
" <td>26.994167</td>\n",
" <td>0.238607</td>\n",
" <td>1.609649</td>\n",
" <td>27.267500</td>\n",
" <td>26.827499</td>\n",
" <td>26.887501</td>\n",
" <td>27.721251</td>\n",
" <td>0.217950</td>\n",
" <td>-1.637233</td>\n",
" <td>27.885000</td>\n",
" <td>27.405001</td>\n",
" <td>27.797501</td>\n",
" <td>27.041250</td>\n",
" <td>0.216386</td>\n",
" <td>0.065737</td>\n",
" <td>27.267500</td>\n",
" <td>26.827499</td>\n",
" <td>27.035001</td>\n",
" <td>27.984167</td>\n",
" <td>0.448803</td>\n",
" <td>0.450175</td>\n",
" <td>28.642500</td>\n",
" <td>27.405001</td>\n",
" <td>27.863750</td>\n",
" <td>27.206667</td>\n",
" <td>0.474201</td>\n",
" <td>1.789900</td>\n",
" <td>28.110001</td>\n",
" <td>26.827499</td>\n",
" <td>27.073750</td>\n",
" <td>28.244063</td>\n",
" <td>0.617885</td>\n",
" <td>0.239458</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>28.131250</td>\n",
" <td>27.479688</td>\n",
" <td>0.654477</td>\n",
" <td>0.612324</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.225000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>2015-10-06</td>\n",
" <td>AAPL</td>\n",
" <td>25.328310</td>\n",
" <td>27.827499</td>\n",
" <td>27.934999</td>\n",
" <td>27.442499</td>\n",
" <td>27.657499</td>\n",
" <td>192787200.0</td>\n",
" <td>2014-12-31</td>\n",
" <td>27.843334</td>\n",
" <td>0.091252</td>\n",
" <td>0.041068</td>\n",
" <td>27.934999</td>\n",
" <td>27.752501</td>\n",
" <td>27.842501</td>\n",
" <td>27.199167</td>\n",
" <td>0.283739</td>\n",
" <td>-1.020885</td>\n",
" <td>27.442499</td>\n",
" <td>26.887501</td>\n",
" <td>27.267500</td>\n",
" <td>27.733750</td>\n",
" <td>0.231485</td>\n",
" <td>-1.402027</td>\n",
" <td>27.934999</td>\n",
" <td>27.405001</td>\n",
" <td>27.797501</td>\n",
" <td>27.106250</td>\n",
" <td>0.296995</td>\n",
" <td>0.256610</td>\n",
" <td>27.442499</td>\n",
" <td>26.827499</td>\n",
" <td>27.077500</td>\n",
" <td>27.866250</td>\n",
" <td>0.313914</td>\n",
" <td>0.333072</td>\n",
" <td>28.377501</td>\n",
" <td>27.405001</td>\n",
" <td>27.863750</td>\n",
" <td>27.095417</td>\n",
" <td>0.240699</td>\n",
" <td>0.368532</td>\n",
" <td>27.442499</td>\n",
" <td>26.827499</td>\n",
" <td>27.073750</td>\n",
" <td>28.126563</td>\n",
" <td>0.568137</td>\n",
" <td>0.857231</td>\n",
" <td>29.172501</td>\n",
" <td>27.405001</td>\n",
" <td>27.910000</td>\n",
" <td>27.398438</td>\n",
" <td>0.606089</td>\n",
" <td>1.113967</td>\n",
" <td>28.504999</td>\n",
" <td>26.827499</td>\n",
" <td>27.225000</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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6519</th>\n",
" <td>2022-02-18</td>\n",
" <td>TSLA</td>\n",
" <td>285.660004</td>\n",
" <td>285.660004</td>\n",
" <td>295.623322</td>\n",
" <td>279.203339</td>\n",
" <td>295.333344</td>\n",
" <td>68501700.0</td>\n",
" <td>2021-04-30</td>\n",
" <td>303.533325</td>\n",
" <td>6.976599</td>\n",
" <td>-1.456544</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>306.166656</td>\n",
" <td>290.324443</td>\n",
" <td>10.638350</td>\n",
" <td>-0.436628</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>291.366669</td>\n",
" <td>304.566658</td>\n",
" <td>6.059681</td>\n",
" <td>-1.812729</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>306.916656</td>\n",
" <td>292.191666</td>\n",
" <td>9.454932</td>\n",
" <td>-1.153258</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>294.580002</td>\n",
" <td>303.868886</td>\n",
" <td>5.142155</td>\n",
" <td>-0.984845</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>305.743332</td>\n",
" <td>289.452779</td>\n",
" <td>8.468042</td>\n",
" <td>0.241799</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>287.875000</td>\n",
" <td>306.654999</td>\n",
" <td>6.749002</td>\n",
" <td>-0.312829</td>\n",
" <td>315.423340</td>\n",
" <td>295.623322</td>\n",
" <td>306.916656</td>\n",
" <td>292.785416</td>\n",
" <td>9.675111</td>\n",
" <td>-0.087055</td>\n",
" <td>306.666656</td>\n",
" <td>279.203339</td>\n",
" <td>294.580002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6520</th>\n",
" <td>2022-02-22</td>\n",
" <td>TSLA</td>\n",
" <td>273.843323</td>\n",
" <td>273.843323</td>\n",
" <td>285.576660</td>\n",
" <td>267.033325</td>\n",
" <td>278.043335</td>\n",
" <td>83288100.0</td>\n",
" <td>2021-04-30</td>\n",
" <td>295.788879</td>\n",
" <td>10.295997</td>\n",
" <td>0.072341</td>\n",
" <td>306.166656</td>\n",
" <td>285.576660</td>\n",
" <td>295.623322</td>\n",
" <td>279.201111</td>\n",
" <td>12.166672</td>\n",
" <td>-0.000824</td>\n",
" <td>291.366669</td>\n",
" <td>267.033325</td>\n",
" <td>279.203339</td>\n",
" <td>299.044159</td>\n",
" <td>10.632924</td>\n",
" <td>-0.659913</td>\n",
" <td>308.809998</td>\n",
" <td>285.576660</td>\n",
" <td>300.894989</td>\n",
" <td>284.501663</td>\n",
" <td>14.528203</td>\n",
" <td>-0.246670</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>285.285004</td>\n",
" <td>300.578328</td>\n",
" <td>8.941387</td>\n",
" <td>-1.011483</td>\n",
" <td>308.809998</td>\n",
" <td>285.576660</td>\n",
" <td>302.896667</td>\n",
" <td>286.697220</td>\n",
" <td>12.497726</td>\n",
" <td>-0.613790</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>287.875000</td>\n",
" <td>302.924164</td>\n",
" <td>9.062503</td>\n",
" <td>-0.945353</td>\n",
" <td>314.603333</td>\n",
" <td>285.576660</td>\n",
" <td>305.743332</td>\n",
" <td>287.831249</td>\n",
" <td>11.522559</td>\n",
" <td>-0.669967</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>287.875000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6521</th>\n",
" <td>2022-02-23</td>\n",
" <td>TSLA</td>\n",
" <td>254.679993</td>\n",
" <td>254.679993</td>\n",
" <td>278.433319</td>\n",
" <td>253.520004</td>\n",
" <td>276.809998</td>\n",
" <td>95256900.0</td>\n",
" <td>2021-04-30</td>\n",
" <td>286.544434</td>\n",
" <td>8.635768</td>\n",
" <td>0.497962</td>\n",
" <td>295.623322</td>\n",
" <td>278.433319</td>\n",
" <td>285.576660</td>\n",
" <td>266.585556</td>\n",
" <td>12.847521</td>\n",
" <td>-0.156646</td>\n",
" <td>279.203339</td>\n",
" <td>253.520004</td>\n",
" <td>267.033325</td>\n",
" <td>291.449989</td>\n",
" <td>12.082035</td>\n",
" <td>0.322037</td>\n",
" <td>306.166656</td>\n",
" <td>278.433319</td>\n",
" <td>290.599991</td>\n",
" <td>272.780834</td>\n",
" <td>16.234688</td>\n",
" <td>-0.101296</td>\n",
" <td>291.366669</td>\n",
" <td>253.520004</td>\n",
" <td>273.118332</td>\n",
" <td>297.046102</td>\n",
" <td>12.762273</td>\n",
" <td>-0.631437</td>\n",
" <td>308.809998</td>\n",
" <td>278.433319</td>\n",
" <td>300.894989</td>\n",
" <td>281.553332</td>\n",
" <td>18.534195</td>\n",
" <td>-0.620976</td>\n",
" <td>300.403320</td>\n",
" <td>253.520004</td>\n",
" <td>285.285004</td>\n",
" <td>298.402912</td>\n",
" <td>11.178854</td>\n",
" <td>-1.005187</td>\n",
" <td>308.809998</td>\n",
" <td>278.433319</td>\n",
" <td>302.473343</td>\n",
" <td>282.158751</td>\n",
" <td>15.705832</td>\n",
" <td>-0.800698</td>\n",
" <td>300.403320</td>\n",
" <td>253.520004</td>\n",
" <td>283.975006</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6522</th>\n",
" <td>2022-02-24</td>\n",
" <td>TSLA</td>\n",
" <td>266.923340</td>\n",
" <td>266.923340</td>\n",
" <td>267.493347</td>\n",
" <td>233.333328</td>\n",
" <td>233.463333</td>\n",
" <td>135322200.0</td>\n",
" <td>2021-04-30</td>\n",
" <td>277.167775</td>\n",
" <td>9.107840</td>\n",
" <td>-0.613207</td>\n",
" <td>285.576660</td>\n",
" <td>267.493347</td>\n",
" <td>278.433319</td>\n",
" <td>251.295553</td>\n",
" <td>16.959764</td>\n",
" <td>-0.580069</td>\n",
" <td>267.033325</td>\n",
" <td>233.333328</td>\n",
" <td>253.520004</td>\n",
" <td>281.781662</td>\n",
" <td>11.851313</td>\n",
" <td>-0.099319</td>\n",
" <td>295.623322</td>\n",
" <td>267.493347</td>\n",
" <td>282.004990</td>\n",
" <td>258.272499</td>\n",
" <td>19.658760</td>\n",
" <td>-0.506867</td>\n",
" <td>279.203339</td>\n",
" <td>233.333328</td>\n",
" <td>260.276665</td>\n",
" <td>290.350550</td>\n",
" <td>16.161465</td>\n",
" <td>-0.238081</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>290.599991</td>\n",
" <td>270.809998</td>\n",
" <td>24.845513</td>\n",
" <td>-0.443312</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>273.118332</td>\n",
" <td>293.674580</td>\n",
" <td>15.134943</td>\n",
" <td>-0.749583</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>297.625000</td>\n",
" <td>275.879581</td>\n",
" <td>23.278525</td>\n",
" <td>-0.894656</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>281.793335</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6523</th>\n",
" <td>2022-02-25</td>\n",
" <td>TSLA</td>\n",
" <td>269.956665</td>\n",
" <td>269.956665</td>\n",
" <td>273.166656</td>\n",
" <td>260.799988</td>\n",
" <td>269.743347</td>\n",
" <td>76067700.0</td>\n",
" <td>2021-04-30</td>\n",
" <td>273.031108</td>\n",
" <td>5.471245</td>\n",
" <td>-0.111418</td>\n",
" <td>278.433319</td>\n",
" <td>267.493347</td>\n",
" <td>273.166656</td>\n",
" <td>249.217773</td>\n",
" <td>14.229766</td>\n",
" <td>-1.236165</td>\n",
" <td>260.799988</td>\n",
" <td>233.333328</td>\n",
" <td>253.520004</td>\n",
" <td>276.167496</td>\n",
" <td>7.700914</td>\n",
" <td>0.240825</td>\n",
" <td>285.576660</td>\n",
" <td>267.493347</td>\n",
" <td>275.799988</td>\n",
" <td>253.671661</td>\n",
" <td>14.640331</td>\n",
" <td>-1.203567</td>\n",
" <td>267.033325</td>\n",
" <td>233.333328</td>\n",
" <td>257.159996</td>\n",
" <td>284.409993</td>\n",
" <td>14.482806</td>\n",
" <td>0.516911</td>\n",
" <td>306.166656</td>\n",
" <td>267.493347</td>\n",
" <td>282.004990</td>\n",
" <td>264.209442</td>\n",
" <td>20.246131</td>\n",
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]
},
"metadata": {},
"execution_count": 94
}
]
},
{
"cell_type": "markdown",
"source": [
"## Technical Features\n",
"\n",
"Maybe we want to move away from \"mean\",\"std\",\"skew\",\"max\",\"min\",\"median\" featurs towards more sophesticated features?"
],
"metadata": {
"id": "KQPvpH0tuOE3"
}
},
{
"cell_type": "code",
"source": [
"%%capture\n",
"!pip install pandas_ta"
],
"metadata": {
"id": "ICGJFCaOuejI"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"## really good technical indicator methods:\n",
"\n",
"import pandas_ta as ta\n",
"# rsi = lambda x: talib.RSI(idf.loc[x.index, \"close\"], 14)\n",
"\n",
"efi = lambda x: pd.concat([\n",
" ta.donchian(df_pricing_hist.loc[x.index,\"High\"], df_pricing_hist.loc[x.index,\"Low\"]),\n",
" ta.bbands(df_pricing_hist.loc[x.index,\"Close\"]),\n",
" ta.sma(df_pricing_hist.loc[x.index,\"Close\"]),\n",
" ta.macd(df_pricing_hist.loc[x.index,\"Close\"])],axis=1)\n"
],
"metadata": {
"id": "eyo6zBt5ugPw"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"These new features can now be merged/concatenated with the original dataframe"
],
"metadata": {
"id": "X11gsGIMvFMw"
}
},
{
"cell_type": "code",
"source": [
"df_pricing_tech = df_pricing.groupby([ticker]).apply(efi).reset_index(drop=True); df_pricing_tech.tail(20) # this groupby is fast and is already doing everything important ;"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 677
},
"id": "ZT3BaIbAvJC3",
"outputId": "10042a24-3974-4c10-f040-caa01dc8160d"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
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},
"metadata": {},
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{
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"df_pricing.shape"
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{
"cell_type": "code",
"source": [
"df_pricing_tech = pd.concat([df_pricing,df_pricing_tech],axis=1)"
],
"metadata": {
"id": "lQnPDUG4yu6J"
},
"execution_count": null,
"outputs": []
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{
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],
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{
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"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low \\\n",
"6479 2022-02-18 TSLA 285.660004 285.660004 295.623322 279.203339 \n",
"6480 2022-02-22 TSLA 273.843323 273.843323 285.576660 267.033325 \n",
"6481 2022-02-23 TSLA 254.679993 254.679993 278.433319 253.520004 \n",
"6482 2022-02-24 TSLA 266.923340 266.923340 267.493347 233.333328 \n",
"6483 2022-02-25 TSLA 269.956665 269.956665 273.166656 260.799988 \n",
"\n",
" Open Volume date_old DCL_20_20 DCM_20_20 DCU_20_20 \\\n",
"6479 295.333344 68501700 2021-04-30 295.373322 343.159988 390.946655 \n",
"6480 278.043335 83288100 2021-04-30 295.373322 343.159988 390.946655 \n",
"6481 276.809998 95256900 2021-04-30 295.373322 343.159988 390.946655 \n",
"6482 233.463333 135322200 2021-04-30 295.373322 343.159988 390.946655 \n",
"6483 269.743347 76067700 2021-04-30 295.373322 343.159988 390.946655 \n",
"\n",
" BBL_5_2.0 BBM_5_2.0 BBU_5_2.0 BBB_5_2.0 BBP_5_2.0 SMA_10 \\\n",
"6479 289.628083 313.788666 337.949248 15.399270 0.965662 320.952332 \n",
"6480 282.886134 323.127332 363.368529 24.907331 0.904304 323.058997 \n",
"6481 284.742234 333.885333 383.028433 29.437112 0.812977 325.622662 \n",
"6482 307.294982 346.453998 385.613013 22.605608 0.709011 329.691330 \n",
"6483 335.393692 356.297998 377.202304 11.734170 0.637898 333.947330 \n",
"\n",
" MACD_12_26_9 MACDh_12_26_9 MACDs_12_26_9 \n",
"6479 -9.463210 -3.049010 -6.414200 \n",
"6480 -6.431282 -0.013665 -6.417616 \n",
"6481 -3.266195 2.521138 -5.787332 \n",
"6482 -0.894655 3.914142 -4.808797 \n",
"6483 0.912957 4.577403 -3.664446 "
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" <td>254.679993</td>\n",
" <td>278.433319</td>\n",
" <td>253.520004</td>\n",
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" <td>390.946655</td>\n",
" <td>284.742234</td>\n",
" <td>333.885333</td>\n",
" <td>383.028433</td>\n",
" <td>29.437112</td>\n",
" <td>0.812977</td>\n",
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" <tr>\n",
" <th>6482</th>\n",
" <td>2022-02-24</td>\n",
" <td>TSLA</td>\n",
" <td>266.923340</td>\n",
" <td>266.923340</td>\n",
" <td>267.493347</td>\n",
" <td>233.333328</td>\n",
" <td>233.463333</td>\n",
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" <th>6483</th>\n",
" <td>2022-02-25</td>\n",
" <td>TSLA</td>\n",
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" <td>269.956665</td>\n",
" <td>273.166656</td>\n",
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]
},
"metadata": {},
"execution_count": 101
}
]
},
{
"cell_type": "markdown",
"source": [
"For fun, let's add the rolling features that we calculated at the start to the technical frame."
],
"metadata": {
"id": "8xeW5kl10ZXb"
}
},
{
"cell_type": "code",
"source": [
"df_pricing_tech_and_rolling = rolling_features(df_pricing_tech, features=columns, windows=windows, functions=functions, method=\"Slow\", ticker=ticker)"
],
"metadata": {
"id": "N1UqZm_i0S8_"
},
"execution_count": null,
"outputs": []
},
{
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"df_pricing_tech_and_rolling.shape"
],
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"execution_count": null,
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{
"output_type": "execute_result",
"data": {
"text/plain": [
"(6484, 69)"
]
},
"metadata": {},
"execution_count": 103
}
]
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{
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"df_pricing_tech_and_rolling.dropna().head(10)"
],
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"height": 444
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"id": "lnXUnlQ40j2z",
"outputId": "473d91f8-89d5-4be7-d289-f528f4ce9055"
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"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low Open \\\n",
"33 2015-11-05 AAPL 27.632818 30.230000 30.672501 30.045000 30.462500 \n",
"34 2015-11-06 AAPL 27.664812 30.264999 30.452499 30.155001 30.277500 \n",
"35 2015-11-09 AAPL 27.552839 30.142500 30.452499 30.012501 30.240000 \n",
"36 2015-11-10 AAPL 26.684456 29.192499 29.517500 29.014999 29.225000 \n",
"37 2015-11-11 AAPL 26.533632 29.027500 29.355000 28.802500 29.092501 \n",
"38 2015-11-12 AAPL 26.444510 28.930000 29.205000 28.912500 29.065001 \n",
"39 2015-11-13 AAPL 25.672104 28.084999 28.892500 28.067499 28.799999 \n",
"40 2015-11-16 AAPL 26.092585 28.545000 28.559999 27.750000 27.844999 \n",
"41 2015-11-17 AAPL 25.980610 28.422501 28.762501 28.330000 28.730000 \n",
"42 2015-11-18 AAPL 26.803289 29.322500 29.372499 28.875000 28.940001 \n",
"\n",
" Volume date_old DCL_20_20 DCM_20_20 DCU_20_20 BBL_5_2.0 \\\n",
"33 158210800 2015-01-31 26.827499 28.000000 29.172501 27.491659 \n",
"34 132169200 2015-01-31 26.827499 28.317500 29.807501 27.459712 \n",
"35 135485600 2015-01-31 26.827499 28.317500 29.807501 27.897829 \n",
"36 236511600 2015-01-31 26.827499 28.317500 29.807501 27.994577 \n",
"37 180872000 2015-01-31 26.827499 28.326250 29.825001 28.175494 \n",
"38 130102400 2015-01-31 26.887501 28.530001 30.172501 28.249156 \n",
"39 183249600 2015-01-31 27.052500 28.678750 30.305000 28.243790 \n",
"40 152426800 2015-01-31 27.052500 28.696250 30.340000 28.584913 \n",
"41 110467600 2015-01-31 27.052500 28.962500 30.872499 29.552474 \n",
"42 186698800 2015-01-31 27.052500 29.003750 30.955000 29.748328 \n",
"\n",
" BBM_5_2.0 BBU_5_2.0 BBB_5_2.0 BBP_5_2.0 SMA_10 MACD_12_26_9 \\\n",
"33 28.2900 29.088342 5.643984 0.866384 28.08450 0.081246 \n",
"34 28.6920 29.924288 8.589768 0.937398 28.25850 0.204487 \n",
"35 28.8695 29.841171 6.731472 0.474528 28.35050 0.222930 \n",
"36 28.9085 29.822424 6.322870 0.351738 28.41950 0.220281 \n",
"37 29.1840 30.192506 6.911365 0.814078 28.64600 0.309826 \n",
"38 29.4355 30.621844 8.060636 0.793759 28.86275 0.401580 \n",
"39 29.4565 30.669209 8.233901 0.672548 29.07425 0.448349 \n",
"40 29.7515 30.918087 7.842204 0.732945 29.31050 0.513387 \n",
"41 30.1525 30.752525 3.979938 0.908316 29.53050 0.586212 \n",
"42 30.2890 30.829672 3.570087 0.695128 29.73650 0.625221 \n",
"\n",
" MACDh_12_26_9 MACDs_12_26_9 High_mean_rolling_3 High_std_rolling_3 \\\n",
"33 0.140346 -0.059101 30.833333 0.145265 \n",
"34 0.210871 -0.006383 30.693333 0.251897 \n",
"35 0.183451 0.039479 30.525833 0.127018 \n",
"36 0.144641 0.075640 30.140833 0.539822 \n",
"37 0.187349 0.122477 29.775000 0.592331 \n",
"38 0.223282 0.178298 29.359166 0.156292 \n",
"39 0.216041 0.232308 29.150833 0.235960 \n",
"40 0.224863 0.288524 28.885833 0.322552 \n",
"41 0.238151 0.348062 28.738333 0.167562 \n",
"42 0.221728 0.403493 28.898333 0.422938 \n",
"\n",
" High_skew_rolling_3 High_max_rolling_3 High_min_rolling_3 \\\n",
"33 -1.125084 30.955000 30.672501 \n",
"34 0.369619 30.955000 30.452499 \n",
"35 1.732051 30.672501 30.452499 \n",
"36 -1.732051 30.452499 29.517500 \n",
"37 1.586552 30.452499 29.355000 \n",
"38 0.119890 29.517500 29.205000 \n",
"39 -0.978580 29.355000 28.892500 \n",
"40 -0.092971 29.205000 28.559999 \n",
"41 -0.635530 28.892500 28.559999 \n",
"42 1.296166 29.372499 28.559999 \n",
"\n",
" High_median_rolling_3 Low_mean_rolling_3 Low_std_rolling_3 \\\n",
"33 30.872499 30.208333 0.182301 \n",
"34 30.672501 30.201667 0.184482 \n",
"35 30.452499 30.070834 0.074680 \n",
"36 30.452499 29.727500 0.621144 \n",
"37 29.517500 29.276667 0.646048 \n",
"38 29.355000 28.910000 0.106272 \n",
"39 29.205000 28.594166 0.459411 \n",
"40 28.892500 28.243333 0.600866 \n",
"41 28.762501 28.049166 0.290434 \n",
"42 28.762501 28.318333 0.562591 \n",
"\n",
" Low_skew_rolling_3 Low_max_rolling_3 Low_min_rolling_3 \\\n",
"33 0.795324 30.405001 30.045000 \n",
"34 1.065481 30.405001 30.045000 \n",
"35 1.370390 30.155001 30.012501 \n",
"36 -1.630060 30.155001 29.014999 \n",
"37 1.523628 30.012501 28.802500 \n",
"38 -0.105825 29.014999 28.802500 \n",
"39 -1.621008 28.912500 28.067499 \n",
"40 1.204086 28.912500 27.750000 \n",
"41 -0.282917 28.330000 27.750000 \n",
"42 -0.093278 28.875000 27.750000 \n",
"\n",
" Low_median_rolling_3 High_mean_rolling_4 High_std_rolling_4 \\\n",
"33 30.174999 30.710000 0.273701 \n",
"34 30.155001 30.738125 0.224336 \n",
"35 30.045000 30.633125 0.238331 \n",
"36 30.012501 30.273750 0.514723 \n",
"37 29.014999 29.944375 0.590471 \n",
"38 28.912500 29.632500 0.561363 \n",
"39 28.802500 29.242500 0.265950 \n",
"40 28.067499 29.003125 0.352688 \n",
"41 28.067499 28.855000 0.270486 \n",
"42 28.330000 28.896875 0.345340 \n",
"\n",
" High_skew_rolling_4 High_max_rolling_4 High_min_rolling_4 \\\n",
"33 -1.030993 30.955000 30.340000 \n",
"34 -0.647027 30.955000 30.452499 \n",
"35 1.064809 30.955000 30.452499 \n",
"36 -1.748594 30.672501 29.517500 \n",
"37 -0.065175 30.452499 29.355000 \n",
"38 1.697171 30.452499 29.205000 \n",
"39 -0.733885 29.517500 28.892500 \n",
"40 -0.555741 29.355000 28.559999 \n",
"41 0.554631 29.205000 28.559999 \n",
"42 1.083536 29.372499 28.559999 \n",
"\n",
" High_median_rolling_4 Low_mean_rolling_4 Low_std_rolling_4 \\\n",
"33 30.772500 30.131875 0.213399 \n",
"34 30.772500 30.195000 0.151218 \n",
"35 30.562500 30.154376 0.177862 \n",
"36 30.452499 29.806875 0.531427 \n",
"37 29.985000 29.496250 0.686382 \n",
"38 29.436250 29.185625 0.558038 \n",
"39 29.280000 28.699375 0.430094 \n",
"40 29.048750 28.383125 0.564677 \n",
"41 28.827500 28.265000 0.492515 \n",
"42 28.827500 28.255625 0.476167 \n",
"\n",
" Low_skew_rolling_4 Low_max_rolling_4 Low_min_rolling_4 \\\n",
"33 0.530355 30.405001 29.902500 \n",
"34 1.120939 30.405001 30.045000 \n",
"35 1.371842 30.405001 30.012501 \n",
"36 -1.919709 30.155001 29.014999 \n",
"37 -0.045148 30.155001 28.802500 \n",
"38 1.855930 30.012501 28.802500 \n",
"39 -1.760258 29.014999 28.067499 \n",
"40 -0.233707 28.912500 27.750000 \n",
"41 0.711192 28.912500 27.750000 \n",
"42 0.630431 28.875000 27.750000 \n",
"\n",
" Low_median_rolling_4 High_mean_rolling_6 High_std_rolling_6 \\\n",
"33 30.110000 30.552917 0.325459 \n",
"34 30.165000 30.599583 0.276376 \n",
"35 30.100000 30.624166 0.250258 \n",
"36 30.028750 30.487083 0.518528 \n",
"37 29.513750 30.234166 0.647089 \n",
"38 28.963750 29.942500 0.651581 \n",
"39 28.857500 29.645833 0.657924 \n",
"40 28.434999 29.330416 0.647413 \n",
"41 28.198750 29.048750 0.369637 \n",
"42 28.198750 29.024583 0.336078 \n",
"\n",
" High_skew_rolling_6 High_max_rolling_6 High_min_rolling_6 \\\n",
"33 0.168935 30.955000 30.172501 \n",
"34 0.275333 30.955000 30.305000 \n",
"35 0.355497 30.955000 30.340000 \n",
"36 -1.604189 30.955000 29.517500 \n",
"37 -0.628943 30.955000 29.355000 \n",
"38 -0.028582 30.672501 29.205000 \n",
"39 0.537136 30.452499 28.892500 \n",
"40 0.968589 30.452499 28.559999 \n",
"41 -0.050410 29.517500 28.559999 \n",
"42 -0.288634 29.372499 28.559999 \n",
"\n",
" High_median_rolling_6 Low_mean_rolling_6 Low_std_rolling_6 \\\n",
"33 30.506250 29.992916 0.287000 \n",
"34 30.562500 30.090833 0.199804 \n",
"35 30.562500 30.115834 0.173123 \n",
"36 30.562500 29.967917 0.486807 \n",
"37 30.452499 29.739167 0.661251 \n",
"38 29.985000 29.490417 0.641100 \n",
"39 29.436250 29.160833 0.789991 \n",
"40 29.280000 28.760000 0.794796 \n",
"41 29.048750 28.479583 0.510459 \n",
"42 29.048750 28.456250 0.483583 \n",
"\n",
" Low_skew_rolling_6 Low_max_rolling_6 Low_min_rolling_6 \\\n",
"33 -0.048145 30.405001 29.567499 \n",
"34 0.496012 30.405001 29.862499 \n",
"35 0.767741 30.405001 29.902500 \n",
"36 -1.991487 30.405001 29.014999 \n",
"37 -0.814947 30.405001 28.802500 \n",
"38 -0.022329 30.155001 28.802500 \n",
"39 0.139329 30.155001 28.067499 \n",
"40 0.372066 30.012501 27.750000 \n",
"41 -0.436161 29.014999 27.750000 \n",
"42 -0.538836 28.912500 27.750000 \n",
"\n",
" Low_median_rolling_6 High_mean_rolling_8 High_std_rolling_8 \\\n",
"33 29.97375 30.284688 0.596944 \n",
"34 30.10000 30.449375 0.374890 \n",
"35 30.10000 30.527812 0.278963 \n",
"36 30.10000 30.445937 0.444908 \n",
"37 30.02875 30.327187 0.590770 \n",
"38 29.51375 30.185312 0.711254 \n",
"39 28.96375 29.937812 0.779218 \n",
"40 28.85750 29.638437 0.792551 \n",
"41 28.56625 29.399687 0.721004 \n",
"42 28.56625 29.264687 0.583763 \n",
"\n",
" High_skew_rolling_8 High_max_rolling_8 High_min_rolling_8 \\\n",
"33 -0.945052 30.955000 29.135000 \n",
"34 -0.190964 30.955000 29.825001 \n",
"35 0.513638 30.955000 30.172501 \n",
"36 -1.261241 30.955000 29.517500 \n",
"37 -0.919163 30.955000 29.355000 \n",
"38 -0.464838 30.955000 29.205000 \n",
"39 -0.034719 30.955000 28.892500 \n",
"40 0.156636 30.672501 28.559999 \n",
"41 0.684460 30.452499 28.559999 \n",
"42 1.116115 30.452499 28.559999 \n",
"\n",
" High_median_rolling_8 Low_mean_rolling_8 Low_std_rolling_8 \\\n",
"33 30.322500 29.683750 0.636931 \n",
"34 30.396250 29.890937 0.432805 \n",
"35 30.452499 30.015625 0.249105 \n",
"36 30.452499 29.946563 0.413461 \n",
"37 30.452499 29.814063 0.580396 \n",
"38 30.452499 29.690313 0.659057 \n",
"39 29.985000 29.426875 0.835285 \n",
"40 29.436250 29.095000 0.914795 \n",
"41 29.280000 28.880625 0.859653 \n",
"42 29.280000 28.720625 0.691192 \n",
"\n",
" Low_skew_rolling_8 Low_max_rolling_8 Low_min_rolling_8 \\\n",
"33 -1.041511 30.405001 28.497499 \n",
"34 -1.233687 30.405001 29.014999 \n",
"35 -0.359982 30.405001 29.567499 \n",
"36 -1.860894 30.405001 29.014999 \n",
"37 -1.199744 30.405001 28.802500 \n",
"38 -0.546286 30.405001 28.802500 \n",
"39 -0.393034 30.405001 28.067499 \n",
"40 -0.181332 30.155001 27.750000 \n",
"41 0.411318 30.155001 27.750000 \n",
"42 0.542343 30.012501 27.750000 \n",
"\n",
" Low_median_rolling_8 \n",
"33 29.88250 \n",
"34 29.97375 \n",
"35 30.02875 \n",
"36 30.02875 \n",
"37 30.02875 \n",
"38 30.02875 \n",
"39 29.51375 \n",
"40 28.96375 \n",
"41 28.85750 \n",
"42 28.83875 "
],
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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>Ticker</th>\n",
" <th>Adj Close</th>\n",
" <th>Close</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Open</th>\n",
" <th>Volume</th>\n",
" <th>date_old</th>\n",
" <th>DCL_20_20</th>\n",
" <th>DCM_20_20</th>\n",
" <th>DCU_20_20</th>\n",
" <th>BBL_5_2.0</th>\n",
" <th>BBM_5_2.0</th>\n",
" <th>BBU_5_2.0</th>\n",
" <th>BBB_5_2.0</th>\n",
" <th>BBP_5_2.0</th>\n",
" <th>SMA_10</th>\n",
" <th>MACD_12_26_9</th>\n",
" <th>MACDh_12_26_9</th>\n",
" <th>MACDs_12_26_9</th>\n",
" <th>High_mean_rolling_3</th>\n",
" <th>High_std_rolling_3</th>\n",
" <th>High_skew_rolling_3</th>\n",
" <th>High_max_rolling_3</th>\n",
" <th>High_min_rolling_3</th>\n",
" <th>High_median_rolling_3</th>\n",
" <th>Low_mean_rolling_3</th>\n",
" <th>Low_std_rolling_3</th>\n",
" <th>Low_skew_rolling_3</th>\n",
" <th>Low_max_rolling_3</th>\n",
" <th>Low_min_rolling_3</th>\n",
" <th>Low_median_rolling_3</th>\n",
" <th>High_mean_rolling_4</th>\n",
" <th>High_std_rolling_4</th>\n",
" <th>High_skew_rolling_4</th>\n",
" <th>High_max_rolling_4</th>\n",
" <th>High_min_rolling_4</th>\n",
" <th>High_median_rolling_4</th>\n",
" <th>Low_mean_rolling_4</th>\n",
" <th>Low_std_rolling_4</th>\n",
" <th>Low_skew_rolling_4</th>\n",
" <th>Low_max_rolling_4</th>\n",
" <th>Low_min_rolling_4</th>\n",
" <th>Low_median_rolling_4</th>\n",
" <th>High_mean_rolling_6</th>\n",
" <th>High_std_rolling_6</th>\n",
" <th>High_skew_rolling_6</th>\n",
" <th>High_max_rolling_6</th>\n",
" <th>High_min_rolling_6</th>\n",
" <th>High_median_rolling_6</th>\n",
" <th>Low_mean_rolling_6</th>\n",
" <th>Low_std_rolling_6</th>\n",
" <th>Low_skew_rolling_6</th>\n",
" <th>Low_max_rolling_6</th>\n",
" <th>Low_min_rolling_6</th>\n",
" <th>Low_median_rolling_6</th>\n",
" <th>High_mean_rolling_8</th>\n",
" <th>High_std_rolling_8</th>\n",
" <th>High_skew_rolling_8</th>\n",
" <th>High_max_rolling_8</th>\n",
" <th>High_min_rolling_8</th>\n",
" <th>High_median_rolling_8</th>\n",
" <th>Low_mean_rolling_8</th>\n",
" <th>Low_std_rolling_8</th>\n",
" <th>Low_skew_rolling_8</th>\n",
" <th>Low_max_rolling_8</th>\n",
" <th>Low_min_rolling_8</th>\n",
" <th>Low_median_rolling_8</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>2015-11-05</td>\n",
" <td>AAPL</td>\n",
" <td>27.632818</td>\n",
" <td>30.230000</td>\n",
" <td>30.672501</td>\n",
" <td>30.045000</td>\n",
" <td>30.462500</td>\n",
" <td>158210800</td>\n",
" <td>2015-01-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.000000</td>\n",
" <td>29.172501</td>\n",
" <td>27.491659</td>\n",
" <td>28.2900</td>\n",
" <td>29.088342</td>\n",
" <td>5.643984</td>\n",
" <td>0.866384</td>\n",
" <td>28.08450</td>\n",
" <td>0.081246</td>\n",
" <td>0.140346</td>\n",
" <td>-0.059101</td>\n",
" <td>30.833333</td>\n",
" <td>0.145265</td>\n",
" <td>-1.125084</td>\n",
" <td>30.955000</td>\n",
" <td>30.672501</td>\n",
" <td>30.872499</td>\n",
" <td>30.208333</td>\n",
" <td>0.182301</td>\n",
" <td>0.795324</td>\n",
" <td>30.405001</td>\n",
" <td>30.045000</td>\n",
" <td>30.174999</td>\n",
" <td>30.710000</td>\n",
" <td>0.273701</td>\n",
" <td>-1.030993</td>\n",
" <td>30.955000</td>\n",
" <td>30.340000</td>\n",
" <td>30.772500</td>\n",
" <td>30.131875</td>\n",
" <td>0.213399</td>\n",
" <td>0.530355</td>\n",
" <td>30.405001</td>\n",
" <td>29.902500</td>\n",
" <td>30.110000</td>\n",
" <td>30.552917</td>\n",
" <td>0.325459</td>\n",
" <td>0.168935</td>\n",
" <td>30.955000</td>\n",
" <td>30.172501</td>\n",
" <td>30.506250</td>\n",
" <td>29.992916</td>\n",
" <td>0.287000</td>\n",
" <td>-0.048145</td>\n",
" <td>30.405001</td>\n",
" <td>29.567499</td>\n",
" <td>29.97375</td>\n",
" <td>30.284688</td>\n",
" <td>0.596944</td>\n",
" <td>-0.945052</td>\n",
" <td>30.955000</td>\n",
" <td>29.135000</td>\n",
" <td>30.322500</td>\n",
" <td>29.683750</td>\n",
" <td>0.636931</td>\n",
" <td>-1.041511</td>\n",
" <td>30.405001</td>\n",
" <td>28.497499</td>\n",
" <td>29.88250</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>2015-11-06</td>\n",
" <td>AAPL</td>\n",
" <td>27.664812</td>\n",
" <td>30.264999</td>\n",
" <td>30.452499</td>\n",
" <td>30.155001</td>\n",
" <td>30.277500</td>\n",
" <td>132169200</td>\n",
" <td>2015-01-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.317500</td>\n",
" <td>29.807501</td>\n",
" <td>27.459712</td>\n",
" <td>28.6920</td>\n",
" <td>29.924288</td>\n",
" <td>8.589768</td>\n",
" <td>0.937398</td>\n",
" <td>28.25850</td>\n",
" <td>0.204487</td>\n",
" <td>0.210871</td>\n",
" <td>-0.006383</td>\n",
" <td>30.693333</td>\n",
" <td>0.251897</td>\n",
" <td>0.369619</td>\n",
" <td>30.955000</td>\n",
" <td>30.452499</td>\n",
" <td>30.672501</td>\n",
" <td>30.201667</td>\n",
" <td>0.184482</td>\n",
" <td>1.065481</td>\n",
" <td>30.405001</td>\n",
" <td>30.045000</td>\n",
" <td>30.155001</td>\n",
" <td>30.738125</td>\n",
" <td>0.224336</td>\n",
" <td>-0.647027</td>\n",
" <td>30.955000</td>\n",
" <td>30.452499</td>\n",
" <td>30.772500</td>\n",
" <td>30.195000</td>\n",
" <td>0.151218</td>\n",
" <td>1.120939</td>\n",
" <td>30.405001</td>\n",
" <td>30.045000</td>\n",
" <td>30.165000</td>\n",
" <td>30.599583</td>\n",
" <td>0.276376</td>\n",
" <td>0.275333</td>\n",
" <td>30.955000</td>\n",
" <td>30.305000</td>\n",
" <td>30.562500</td>\n",
" <td>30.090833</td>\n",
" <td>0.199804</td>\n",
" <td>0.496012</td>\n",
" <td>30.405001</td>\n",
" <td>29.862499</td>\n",
" <td>30.10000</td>\n",
" <td>30.449375</td>\n",
" <td>0.374890</td>\n",
" <td>-0.190964</td>\n",
" <td>30.955000</td>\n",
" <td>29.825001</td>\n",
" <td>30.396250</td>\n",
" <td>29.890937</td>\n",
" <td>0.432805</td>\n",
" <td>-1.233687</td>\n",
" <td>30.405001</td>\n",
" <td>29.014999</td>\n",
" <td>29.97375</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>2015-11-09</td>\n",
" <td>AAPL</td>\n",
" <td>27.552839</td>\n",
" <td>30.142500</td>\n",
" <td>30.452499</td>\n",
" <td>30.012501</td>\n",
" <td>30.240000</td>\n",
" <td>135485600</td>\n",
" <td>2015-01-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.317500</td>\n",
" <td>29.807501</td>\n",
" <td>27.897829</td>\n",
" <td>28.8695</td>\n",
" <td>29.841171</td>\n",
" <td>6.731472</td>\n",
" <td>0.474528</td>\n",
" <td>28.35050</td>\n",
" <td>0.222930</td>\n",
" <td>0.183451</td>\n",
" <td>0.039479</td>\n",
" <td>30.525833</td>\n",
" <td>0.127018</td>\n",
" <td>1.732051</td>\n",
" <td>30.672501</td>\n",
" <td>30.452499</td>\n",
" <td>30.452499</td>\n",
" <td>30.070834</td>\n",
" <td>0.074680</td>\n",
" <td>1.370390</td>\n",
" <td>30.155001</td>\n",
" <td>30.012501</td>\n",
" <td>30.045000</td>\n",
" <td>30.633125</td>\n",
" <td>0.238331</td>\n",
" <td>1.064809</td>\n",
" <td>30.955000</td>\n",
" <td>30.452499</td>\n",
" <td>30.562500</td>\n",
" <td>30.154376</td>\n",
" <td>0.177862</td>\n",
" <td>1.371842</td>\n",
" <td>30.405001</td>\n",
" <td>30.012501</td>\n",
" <td>30.100000</td>\n",
" <td>30.624166</td>\n",
" <td>0.250258</td>\n",
" <td>0.355497</td>\n",
" <td>30.955000</td>\n",
" <td>30.340000</td>\n",
" <td>30.562500</td>\n",
" <td>30.115834</td>\n",
" <td>0.173123</td>\n",
" <td>0.767741</td>\n",
" <td>30.405001</td>\n",
" <td>29.902500</td>\n",
" <td>30.10000</td>\n",
" <td>30.527812</td>\n",
" <td>0.278963</td>\n",
" <td>0.513638</td>\n",
" <td>30.955000</td>\n",
" <td>30.172501</td>\n",
" <td>30.452499</td>\n",
" <td>30.015625</td>\n",
" <td>0.249105</td>\n",
" <td>-0.359982</td>\n",
" <td>30.405001</td>\n",
" <td>29.567499</td>\n",
" <td>30.02875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>2015-11-10</td>\n",
" <td>AAPL</td>\n",
" <td>26.684456</td>\n",
" <td>29.192499</td>\n",
" <td>29.517500</td>\n",
" <td>29.014999</td>\n",
" <td>29.225000</td>\n",
" <td>236511600</td>\n",
" <td>2015-01-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.317500</td>\n",
" <td>29.807501</td>\n",
" <td>27.994577</td>\n",
" <td>28.9085</td>\n",
" <td>29.822424</td>\n",
" <td>6.322870</td>\n",
" <td>0.351738</td>\n",
" <td>28.41950</td>\n",
" <td>0.220281</td>\n",
" <td>0.144641</td>\n",
" <td>0.075640</td>\n",
" <td>30.140833</td>\n",
" <td>0.539822</td>\n",
" <td>-1.732051</td>\n",
" <td>30.452499</td>\n",
" <td>29.517500</td>\n",
" <td>30.452499</td>\n",
" <td>29.727500</td>\n",
" <td>0.621144</td>\n",
" <td>-1.630060</td>\n",
" <td>30.155001</td>\n",
" <td>29.014999</td>\n",
" <td>30.012501</td>\n",
" <td>30.273750</td>\n",
" <td>0.514723</td>\n",
" <td>-1.748594</td>\n",
" <td>30.672501</td>\n",
" <td>29.517500</td>\n",
" <td>30.452499</td>\n",
" <td>29.806875</td>\n",
" <td>0.531427</td>\n",
" <td>-1.919709</td>\n",
" <td>30.155001</td>\n",
" <td>29.014999</td>\n",
" <td>30.028750</td>\n",
" <td>30.487083</td>\n",
" <td>0.518528</td>\n",
" <td>-1.604189</td>\n",
" <td>30.955000</td>\n",
" <td>29.517500</td>\n",
" <td>30.562500</td>\n",
" <td>29.967917</td>\n",
" <td>0.486807</td>\n",
" <td>-1.991487</td>\n",
" <td>30.405001</td>\n",
" <td>29.014999</td>\n",
" <td>30.10000</td>\n",
" <td>30.445937</td>\n",
" <td>0.444908</td>\n",
" <td>-1.261241</td>\n",
" <td>30.955000</td>\n",
" <td>29.517500</td>\n",
" <td>30.452499</td>\n",
" <td>29.946563</td>\n",
" <td>0.413461</td>\n",
" <td>-1.860894</td>\n",
" <td>30.405001</td>\n",
" <td>29.014999</td>\n",
" <td>30.02875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>2015-11-11</td>\n",
" <td>AAPL</td>\n",
" <td>26.533632</td>\n",
" <td>29.027500</td>\n",
" <td>29.355000</td>\n",
" <td>28.802500</td>\n",
" <td>29.092501</td>\n",
" <td>180872000</td>\n",
" <td>2015-01-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.326250</td>\n",
" <td>29.825001</td>\n",
" <td>28.175494</td>\n",
" <td>29.1840</td>\n",
" <td>30.192506</td>\n",
" <td>6.911365</td>\n",
" <td>0.814078</td>\n",
" <td>28.64600</td>\n",
" <td>0.309826</td>\n",
" <td>0.187349</td>\n",
" <td>0.122477</td>\n",
" <td>29.775000</td>\n",
" <td>0.592331</td>\n",
" <td>1.586552</td>\n",
" <td>30.452499</td>\n",
" <td>29.355000</td>\n",
" <td>29.517500</td>\n",
" <td>29.276667</td>\n",
" <td>0.646048</td>\n",
" <td>1.523628</td>\n",
" <td>30.012501</td>\n",
" <td>28.802500</td>\n",
" <td>29.014999</td>\n",
" <td>29.944375</td>\n",
" <td>0.590471</td>\n",
" <td>-0.065175</td>\n",
" <td>30.452499</td>\n",
" <td>29.355000</td>\n",
" <td>29.985000</td>\n",
" <td>29.496250</td>\n",
" <td>0.686382</td>\n",
" <td>-0.045148</td>\n",
" <td>30.155001</td>\n",
" <td>28.802500</td>\n",
" <td>29.513750</td>\n",
" <td>30.234166</td>\n",
" <td>0.647089</td>\n",
" <td>-0.628943</td>\n",
" <td>30.955000</td>\n",
" <td>29.355000</td>\n",
" <td>30.452499</td>\n",
" <td>29.739167</td>\n",
" <td>0.661251</td>\n",
" <td>-0.814947</td>\n",
" <td>30.405001</td>\n",
" <td>28.802500</td>\n",
" <td>30.02875</td>\n",
" <td>30.327187</td>\n",
" <td>0.590770</td>\n",
" <td>-0.919163</td>\n",
" <td>30.955000</td>\n",
" <td>29.355000</td>\n",
" <td>30.452499</td>\n",
" <td>29.814063</td>\n",
" <td>0.580396</td>\n",
" <td>-1.199744</td>\n",
" <td>30.405001</td>\n",
" <td>28.802500</td>\n",
" <td>30.02875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>2015-11-12</td>\n",
" <td>AAPL</td>\n",
" <td>26.444510</td>\n",
" <td>28.930000</td>\n",
" <td>29.205000</td>\n",
" <td>28.912500</td>\n",
" <td>29.065001</td>\n",
" <td>130102400</td>\n",
" <td>2015-01-31</td>\n",
" <td>26.887501</td>\n",
" <td>28.530001</td>\n",
" <td>30.172501</td>\n",
" <td>28.249156</td>\n",
" <td>29.4355</td>\n",
" <td>30.621844</td>\n",
" <td>8.060636</td>\n",
" <td>0.793759</td>\n",
" <td>28.86275</td>\n",
" <td>0.401580</td>\n",
" <td>0.223282</td>\n",
" <td>0.178298</td>\n",
" <td>29.359166</td>\n",
" <td>0.156292</td>\n",
" <td>0.119890</td>\n",
" <td>29.517500</td>\n",
" <td>29.205000</td>\n",
" <td>29.355000</td>\n",
" <td>28.910000</td>\n",
" <td>0.106272</td>\n",
" <td>-0.105825</td>\n",
" <td>29.014999</td>\n",
" <td>28.802500</td>\n",
" <td>28.912500</td>\n",
" <td>29.632500</td>\n",
" <td>0.561363</td>\n",
" <td>1.697171</td>\n",
" <td>30.452499</td>\n",
" <td>29.205000</td>\n",
" <td>29.436250</td>\n",
" <td>29.185625</td>\n",
" <td>0.558038</td>\n",
" <td>1.855930</td>\n",
" <td>30.012501</td>\n",
" <td>28.802500</td>\n",
" <td>28.963750</td>\n",
" <td>29.942500</td>\n",
" <td>0.651581</td>\n",
" <td>-0.028582</td>\n",
" <td>30.672501</td>\n",
" <td>29.205000</td>\n",
" <td>29.985000</td>\n",
" <td>29.490417</td>\n",
" <td>0.641100</td>\n",
" <td>-0.022329</td>\n",
" <td>30.155001</td>\n",
" <td>28.802500</td>\n",
" <td>29.51375</td>\n",
" <td>30.185312</td>\n",
" <td>0.711254</td>\n",
" <td>-0.464838</td>\n",
" <td>30.955000</td>\n",
" <td>29.205000</td>\n",
" <td>30.452499</td>\n",
" <td>29.690313</td>\n",
" <td>0.659057</td>\n",
" <td>-0.546286</td>\n",
" <td>30.405001</td>\n",
" <td>28.802500</td>\n",
" <td>30.02875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>2015-11-13</td>\n",
" <td>AAPL</td>\n",
" <td>25.672104</td>\n",
" <td>28.084999</td>\n",
" <td>28.892500</td>\n",
" <td>28.067499</td>\n",
" <td>28.799999</td>\n",
" <td>183249600</td>\n",
" <td>2015-01-31</td>\n",
" <td>27.052500</td>\n",
" <td>28.678750</td>\n",
" <td>30.305000</td>\n",
" <td>28.243790</td>\n",
" <td>29.4565</td>\n",
" <td>30.669209</td>\n",
" <td>8.233901</td>\n",
" <td>0.672548</td>\n",
" <td>29.07425</td>\n",
" <td>0.448349</td>\n",
" <td>0.216041</td>\n",
" <td>0.232308</td>\n",
" <td>29.150833</td>\n",
" <td>0.235960</td>\n",
" <td>-0.978580</td>\n",
" <td>29.355000</td>\n",
" <td>28.892500</td>\n",
" <td>29.205000</td>\n",
" <td>28.594166</td>\n",
" <td>0.459411</td>\n",
" <td>-1.621008</td>\n",
" <td>28.912500</td>\n",
" <td>28.067499</td>\n",
" <td>28.802500</td>\n",
" <td>29.242500</td>\n",
" <td>0.265950</td>\n",
" <td>-0.733885</td>\n",
" <td>29.517500</td>\n",
" <td>28.892500</td>\n",
" <td>29.280000</td>\n",
" <td>28.699375</td>\n",
" <td>0.430094</td>\n",
" <td>-1.760258</td>\n",
" <td>29.014999</td>\n",
" <td>28.067499</td>\n",
" <td>28.857500</td>\n",
" <td>29.645833</td>\n",
" <td>0.657924</td>\n",
" <td>0.537136</td>\n",
" <td>30.452499</td>\n",
" <td>28.892500</td>\n",
" <td>29.436250</td>\n",
" <td>29.160833</td>\n",
" <td>0.789991</td>\n",
" <td>0.139329</td>\n",
" <td>30.155001</td>\n",
" <td>28.067499</td>\n",
" <td>28.96375</td>\n",
" <td>29.937812</td>\n",
" <td>0.779218</td>\n",
" <td>-0.034719</td>\n",
" <td>30.955000</td>\n",
" <td>28.892500</td>\n",
" <td>29.985000</td>\n",
" <td>29.426875</td>\n",
" <td>0.835285</td>\n",
" <td>-0.393034</td>\n",
" <td>30.405001</td>\n",
" <td>28.067499</td>\n",
" <td>29.51375</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>2015-11-16</td>\n",
" <td>AAPL</td>\n",
" <td>26.092585</td>\n",
" <td>28.545000</td>\n",
" <td>28.559999</td>\n",
" <td>27.750000</td>\n",
" <td>27.844999</td>\n",
" <td>152426800</td>\n",
" <td>2015-01-31</td>\n",
" <td>27.052500</td>\n",
" <td>28.696250</td>\n",
" <td>30.340000</td>\n",
" <td>28.584913</td>\n",
" <td>29.7515</td>\n",
" <td>30.918087</td>\n",
" <td>7.842204</td>\n",
" <td>0.732945</td>\n",
" <td>29.31050</td>\n",
" <td>0.513387</td>\n",
" <td>0.224863</td>\n",
" <td>0.288524</td>\n",
" <td>28.885833</td>\n",
" <td>0.322552</td>\n",
" <td>-0.092971</td>\n",
" <td>29.205000</td>\n",
" <td>28.559999</td>\n",
" <td>28.892500</td>\n",
" <td>28.243333</td>\n",
" <td>0.600866</td>\n",
" <td>1.204086</td>\n",
" <td>28.912500</td>\n",
" <td>27.750000</td>\n",
" <td>28.067499</td>\n",
" <td>29.003125</td>\n",
" <td>0.352688</td>\n",
" <td>-0.555741</td>\n",
" <td>29.355000</td>\n",
" <td>28.559999</td>\n",
" <td>29.048750</td>\n",
" <td>28.383125</td>\n",
" <td>0.564677</td>\n",
" <td>-0.233707</td>\n",
" <td>28.912500</td>\n",
" <td>27.750000</td>\n",
" <td>28.434999</td>\n",
" <td>29.330416</td>\n",
" <td>0.647413</td>\n",
" <td>0.968589</td>\n",
" <td>30.452499</td>\n",
" <td>28.559999</td>\n",
" <td>29.280000</td>\n",
" <td>28.760000</td>\n",
" <td>0.794796</td>\n",
" <td>0.372066</td>\n",
" <td>30.012501</td>\n",
" <td>27.750000</td>\n",
" <td>28.85750</td>\n",
" <td>29.638437</td>\n",
" <td>0.792551</td>\n",
" <td>0.156636</td>\n",
" <td>30.672501</td>\n",
" <td>28.559999</td>\n",
" <td>29.436250</td>\n",
" <td>29.095000</td>\n",
" <td>0.914795</td>\n",
" <td>-0.181332</td>\n",
" <td>30.155001</td>\n",
" <td>27.750000</td>\n",
" <td>28.96375</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>2015-11-17</td>\n",
" <td>AAPL</td>\n",
" <td>25.980610</td>\n",
" <td>28.422501</td>\n",
" <td>28.762501</td>\n",
" <td>28.330000</td>\n",
" <td>28.730000</td>\n",
" <td>110467600</td>\n",
" <td>2015-01-31</td>\n",
" <td>27.052500</td>\n",
" <td>28.962500</td>\n",
" <td>30.872499</td>\n",
" <td>29.552474</td>\n",
" <td>30.1525</td>\n",
" <td>30.752525</td>\n",
" <td>3.979938</td>\n",
" <td>0.908316</td>\n",
" <td>29.53050</td>\n",
" <td>0.586212</td>\n",
" <td>0.238151</td>\n",
" <td>0.348062</td>\n",
" <td>28.738333</td>\n",
" <td>0.167562</td>\n",
" <td>-0.635530</td>\n",
" <td>28.892500</td>\n",
" <td>28.559999</td>\n",
" <td>28.762501</td>\n",
" <td>28.049166</td>\n",
" <td>0.290434</td>\n",
" <td>-0.282917</td>\n",
" <td>28.330000</td>\n",
" <td>27.750000</td>\n",
" <td>28.067499</td>\n",
" <td>28.855000</td>\n",
" <td>0.270486</td>\n",
" <td>0.554631</td>\n",
" <td>29.205000</td>\n",
" <td>28.559999</td>\n",
" <td>28.827500</td>\n",
" <td>28.265000</td>\n",
" <td>0.492515</td>\n",
" <td>0.711192</td>\n",
" <td>28.912500</td>\n",
" <td>27.750000</td>\n",
" <td>28.198750</td>\n",
" <td>29.048750</td>\n",
" <td>0.369637</td>\n",
" <td>-0.050410</td>\n",
" <td>29.517500</td>\n",
" <td>28.559999</td>\n",
" <td>29.048750</td>\n",
" <td>28.479583</td>\n",
" <td>0.510459</td>\n",
" <td>-0.436161</td>\n",
" <td>29.014999</td>\n",
" <td>27.750000</td>\n",
" <td>28.56625</td>\n",
" <td>29.399687</td>\n",
" <td>0.721004</td>\n",
" <td>0.684460</td>\n",
" <td>30.452499</td>\n",
" <td>28.559999</td>\n",
" <td>29.280000</td>\n",
" <td>28.880625</td>\n",
" <td>0.859653</td>\n",
" <td>0.411318</td>\n",
" <td>30.155001</td>\n",
" <td>27.750000</td>\n",
" <td>28.85750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>2015-11-18</td>\n",
" <td>AAPL</td>\n",
" <td>26.803289</td>\n",
" <td>29.322500</td>\n",
" <td>29.372499</td>\n",
" <td>28.875000</td>\n",
" <td>28.940001</td>\n",
" <td>186698800</td>\n",
" <td>2015-01-31</td>\n",
" <td>27.052500</td>\n",
" <td>29.003750</td>\n",
" <td>30.955000</td>\n",
" <td>29.748328</td>\n",
" <td>30.2890</td>\n",
" <td>30.829672</td>\n",
" <td>3.570087</td>\n",
" <td>0.695128</td>\n",
" <td>29.73650</td>\n",
" <td>0.625221</td>\n",
" <td>0.221728</td>\n",
" <td>0.403493</td>\n",
" <td>28.898333</td>\n",
" <td>0.422938</td>\n",
" <td>1.296166</td>\n",
" <td>29.372499</td>\n",
" <td>28.559999</td>\n",
" <td>28.762501</td>\n",
" <td>28.318333</td>\n",
" <td>0.562591</td>\n",
" <td>-0.093278</td>\n",
" <td>28.875000</td>\n",
" <td>27.750000</td>\n",
" <td>28.330000</td>\n",
" <td>28.896875</td>\n",
" <td>0.345340</td>\n",
" <td>1.083536</td>\n",
" <td>29.372499</td>\n",
" <td>28.559999</td>\n",
" <td>28.827500</td>\n",
" <td>28.255625</td>\n",
" <td>0.476167</td>\n",
" <td>0.630431</td>\n",
" <td>28.875000</td>\n",
" <td>27.750000</td>\n",
" <td>28.198750</td>\n",
" <td>29.024583</td>\n",
" <td>0.336078</td>\n",
" <td>-0.288634</td>\n",
" <td>29.372499</td>\n",
" <td>28.559999</td>\n",
" <td>29.048750</td>\n",
" <td>28.456250</td>\n",
" <td>0.483583</td>\n",
" <td>-0.538836</td>\n",
" <td>28.912500</td>\n",
" <td>27.750000</td>\n",
" <td>28.56625</td>\n",
" <td>29.264687</td>\n",
" <td>0.583763</td>\n",
" <td>1.116115</td>\n",
" <td>30.452499</td>\n",
" <td>28.559999</td>\n",
" <td>29.280000</td>\n",
" <td>28.720625</td>\n",
" <td>0.691192</td>\n",
" <td>0.542343</td>\n",
" <td>30.012501</td>\n",
" <td>27.750000</td>\n",
" <td>28.83875</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
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]
},
"metadata": {},
"execution_count": 104
}
]
},
{
"cell_type": "markdown",
"source": [
"Catch 22 Features"
],
"metadata": {
"id": "Bf7dV6tW5Nrb"
}
},
{
"cell_type": "code",
"source": [
"%%capture\n",
"!sudo apt-get install python3-setuptools\n",
"!pip install setuptools --upgrade\n",
"!pip install pycatch22\n",
"!pip install tsflex"
],
"metadata": {
"id": "4fwY99fI5rk3"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from tsflex.features import FeatureCollection, MultipleFeatureDescriptors\n",
"from tsflex.features.integrations import tsfresh_settings_wrapper, catch22_wrapper\n",
"import pycatch22\n",
"from pycatch22.catch22 import catch22_all\n",
"\n",
"# (data, features, windows, strides) = (df_daily,[\"adj_close\"], 30, 1)\n",
"\n",
"def catch_feats(data, features, windows, strides):\n",
" fc = FeatureCollection(\n",
" MultipleFeatureDescriptors(\n",
" functions=catch22_wrapper(pycatch22.catch22.catch22_all),\n",
" series_names=features,\n",
" windows=windows,\n",
" strides=strides\n",
" )\n",
" )\n",
" print(\"Data Shape before Catch22:\", data.shape)\n",
" data_temp = fc.calculate(data, show_progress=True, return_df=True, window_idx=\"begin\")\n",
"\n",
" empty_df = pd.DataFrame(np.nan, index = np.arange(windows), columns = data_temp.columns)\n",
" empty_df = empty_df.append(data_temp, ignore_index = True)\n",
" empty_df.index = data.index\n",
"\n",
" empty_df.columns= empty_df.columns.str.lower()\n",
"\n",
" return empty_df.add_suffix(\"_catch\")\n",
"\n",
"\n",
"def signal_feats(df_daily, periods = [30, 7]):\n",
" df_daily[\"log_return\"] = np.log(df_daily[\"Adj Close\"]).diff() # I think it is better to use log.\n",
" df_daily[\"log_volume\"] = np.log(df_daily[\"Volume\"]).diff() # I think it is better to use log.\n",
"\n",
" data_temp = pd.concat([catch_feats(df_daily,[\"log_return\",\"log_volume\"], period, 1) for period in periods], axis=1)\n",
" df_daily = pd.concat([df_daily, data_temp], axis=1)\n",
" return df_daily\n"
],
"metadata": {
"id": "YXgDlO_Y5Qf5"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"The catch-22 functions do not have a groupby statement (so lets add history)\n"
],
"metadata": {
"id": "yWjlL6xc73fY"
}
},
{
"cell_type": "code",
"source": [
"df_pricing_tech_and_rolling_hist = create_old(df_pricing_tech_and_rolling, ticker, \"Date\", 35, gran=\"days\")\n",
"df_pricing_tech_and_rolling_hist = df_pricing_tech_and_rolling_hist.sort_values([ticker,\"Date\"]).reset_index(drop=True)\n",
"df_pricing_tech_and_rolling_and_signal = signal_feats(df_pricing_tech_and_rolling_hist)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 188,
"referenced_widgets": [
"f9e2fcfae248497ea78b6d6080bef63c",
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"cbf8ff70374d4206b85f35365c7fb70f",
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"e893b98160b74e3dbc4176e0acb8b6f6",
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"d4555036417d425da89c334e1f7feb1e",
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},
"id": "cEo5gf1k7xFn",
"outputId": "6edad465-cdb1-456b-a877-58cdca5f10e8"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Data Shape before Catch22: (6624, 71)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/2 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "f9e2fcfae248497ea78b6d6080bef63c"
}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"INFO:feature_calculation_logger:Finished function [[wrapped]__catch22_all] on [('log_volume',)] with window-stride [30, ('1',)] in [4.390152454376221 seconds]!\n",
"INFO:feature_calculation_logger:Finished function [[wrapped]__catch22_all] on [('log_return',)] with window-stride [30, ('1',)] in [4.842772722244263 seconds]!\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Data Shape before Catch22: (6624, 71)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/2 [00:00<?, ?it/s]"
],
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"version_major": 2,
"version_minor": 0,
"model_id": "263ab0da987349339f7e0fb8c9add7ba"
}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"INFO:feature_calculation_logger:Finished function [[wrapped]__catch22_all] on [('log_volume',)] with window-stride [7, ('1',)] in [1.4735333919525146 seconds]!\n",
"INFO:feature_calculation_logger:Finished function [[wrapped]__catch22_all] on [('log_return',)] with window-stride [7, ('1',)] in [1.7090227603912354 seconds]!\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"df_pricing_tech_and_rolling_and_signal.dropna()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 488
},
"id": "wp025gst7B07",
"outputId": "585a36a4-65f7-4d44-e6b4-83f684522068"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low \\\n",
"68 2015-11-05 AAPL 27.632818 30.230000 30.672501 30.045000 \n",
"69 2015-11-06 AAPL 27.664812 30.264999 30.452499 30.155001 \n",
"70 2015-11-09 AAPL 27.552839 30.142500 30.452499 30.012501 \n",
"71 2015-11-10 AAPL 26.684456 29.192499 29.517500 29.014999 \n",
"72 2015-11-11 AAPL 26.533632 29.027500 29.355000 28.802500 \n",
"... ... ... ... ... ... ... \n",
"6619 2022-02-18 TSLA 285.660004 285.660004 295.623322 279.203339 \n",
"6620 2022-02-22 TSLA 273.843323 273.843323 285.576660 267.033325 \n",
"6621 2022-02-23 TSLA 254.679993 254.679993 278.433319 253.520004 \n",
"6622 2022-02-24 TSLA 266.923340 266.923340 267.493347 233.333328 \n",
"6623 2022-02-25 TSLA 269.956665 269.956665 273.166656 260.799988 \n",
"\n",
" Open Volume date_old DCL_20_20 DCM_20_20 DCU_20_20 \\\n",
"68 30.462500 158210800.0 2012-12-31 26.827499 28.000000 29.172501 \n",
"69 30.277500 132169200.0 2012-12-31 26.827499 28.317500 29.807501 \n",
"70 30.240000 135485600.0 2012-12-31 26.827499 28.317500 29.807501 \n",
"71 29.225000 236511600.0 2012-12-31 26.827499 28.317500 29.807501 \n",
"72 29.092501 180872000.0 2012-12-31 26.827499 28.326250 29.825001 \n",
"... ... ... ... ... ... ... \n",
"6619 295.333344 68501700.0 2019-03-31 295.373322 343.159988 390.946655 \n",
"6620 278.043335 83288100.0 2019-03-31 295.373322 343.159988 390.946655 \n",
"6621 276.809998 95256900.0 2019-03-31 295.373322 343.159988 390.946655 \n",
"6622 233.463333 135322200.0 2019-03-31 295.373322 343.159988 390.946655 \n",
"6623 269.743347 76067700.0 2019-03-31 295.373322 343.159988 390.946655 \n",
"\n",
" BBL_5_2.0 BBM_5_2.0 BBU_5_2.0 BBB_5_2.0 BBP_5_2.0 SMA_10 \\\n",
"68 27.491659 28.290000 29.088342 5.643984 0.866384 28.084500 \n",
"69 27.459712 28.692000 29.924288 8.589768 0.937398 28.258500 \n",
"70 27.897829 28.869500 29.841171 6.731472 0.474528 28.350500 \n",
"71 27.994577 28.908500 29.822424 6.322870 0.351738 28.419500 \n",
"72 28.175494 29.184000 30.192506 6.911365 0.814078 28.646000 \n",
"... ... ... ... ... ... ... \n",
"6619 289.628083 313.788666 337.949248 15.399270 0.965662 320.952332 \n",
"6620 282.886134 323.127332 363.368529 24.907331 0.904304 323.058997 \n",
"6621 284.742234 333.885333 383.028433 29.437112 0.812977 325.622662 \n",
"6622 307.294982 346.453998 385.613013 22.605608 0.709011 329.691330 \n",
"6623 335.393692 356.297998 377.202304 11.734170 0.637898 333.947330 \n",
"\n",
" MACD_12_26_9 MACDh_12_26_9 MACDs_12_26_9 High_mean_rolling_3 \\\n",
"68 0.081246 0.140346 -0.059101 30.833333 \n",
"69 0.204487 0.210871 -0.006383 30.693333 \n",
"70 0.222930 0.183451 0.039479 30.525833 \n",
"71 0.220281 0.144641 0.075640 30.140833 \n",
"72 0.309826 0.187349 0.122477 29.775000 \n",
"... ... ... ... ... \n",
"6619 -9.463210 -3.049010 -6.414200 303.533325 \n",
"6620 -6.431282 -0.013665 -6.417616 295.788879 \n",
"6621 -3.266195 2.521138 -5.787332 286.544434 \n",
"6622 -0.894655 3.914142 -4.808797 277.167775 \n",
"6623 0.912957 4.577403 -3.664446 273.031108 \n",
"\n",
" High_std_rolling_3 High_skew_rolling_3 High_max_rolling_3 \\\n",
"68 0.145265 -1.125084 30.955000 \n",
"69 0.251897 0.369619 30.955000 \n",
"70 0.127018 1.732051 30.672501 \n",
"71 0.539822 -1.732051 30.452499 \n",
"72 0.592331 1.586552 30.452499 \n",
"... ... ... ... \n",
"6619 6.976599 -1.456544 308.809998 \n",
"6620 10.295997 0.072341 306.166656 \n",
"6621 8.635768 0.497962 295.623322 \n",
"6622 9.107840 -0.613207 285.576660 \n",
"6623 5.471245 -0.111418 278.433319 \n",
"\n",
" High_min_rolling_3 High_median_rolling_3 Low_mean_rolling_3 \\\n",
"68 30.672501 30.872499 30.208333 \n",
"69 30.452499 30.672501 30.201667 \n",
"70 30.452499 30.452499 30.070834 \n",
"71 29.517500 30.452499 29.727500 \n",
"72 29.355000 29.517500 29.276667 \n",
"... ... ... ... \n",
"6619 295.623322 306.166656 290.324443 \n",
"6620 285.576660 295.623322 279.201111 \n",
"6621 278.433319 285.576660 266.585556 \n",
"6622 267.493347 278.433319 251.295553 \n",
"6623 267.493347 273.166656 249.217773 \n",
"\n",
" Low_std_rolling_3 Low_skew_rolling_3 Low_max_rolling_3 \\\n",
"68 0.182301 0.795324 30.405001 \n",
"69 0.184482 1.065481 30.405001 \n",
"70 0.074680 1.370390 30.155001 \n",
"71 0.621144 -1.630060 30.155001 \n",
"72 0.646048 1.523628 30.012501 \n",
"... ... ... ... \n",
"6619 10.638350 -0.436628 300.403320 \n",
"6620 12.166672 -0.000824 291.366669 \n",
"6621 12.847521 -0.156646 279.203339 \n",
"6622 16.959764 -0.580069 267.033325 \n",
"6623 14.229766 -1.236165 260.799988 \n",
"\n",
" Low_min_rolling_3 Low_median_rolling_3 High_mean_rolling_4 \\\n",
"68 30.045000 30.174999 30.710000 \n",
"69 30.045000 30.155001 30.738125 \n",
"70 30.012501 30.045000 30.633125 \n",
"71 29.014999 30.012501 30.273750 \n",
"72 28.802500 29.014999 29.944375 \n",
"... ... ... ... \n",
"6619 279.203339 291.366669 304.566658 \n",
"6620 267.033325 279.203339 299.044159 \n",
"6621 253.520004 267.033325 291.449989 \n",
"6622 233.333328 253.520004 281.781662 \n",
"6623 233.333328 253.520004 276.167496 \n",
"\n",
" High_std_rolling_4 High_skew_rolling_4 High_max_rolling_4 \\\n",
"68 0.273701 -1.030993 30.955000 \n",
"69 0.224336 -0.647027 30.955000 \n",
"70 0.238331 1.064809 30.955000 \n",
"71 0.514723 -1.748594 30.672501 \n",
"72 0.590471 -0.065175 30.452499 \n",
"... ... ... ... \n",
"6619 6.059681 -1.812729 308.809998 \n",
"6620 10.632924 -0.659913 308.809998 \n",
"6621 12.082035 0.322037 306.166656 \n",
"6622 11.851313 -0.099319 295.623322 \n",
"6623 7.700914 0.240825 285.576660 \n",
"\n",
" High_min_rolling_4 High_median_rolling_4 Low_mean_rolling_4 \\\n",
"68 30.340000 30.772500 30.131875 \n",
"69 30.452499 30.772500 30.195000 \n",
"70 30.452499 30.562500 30.154376 \n",
"71 29.517500 30.452499 29.806875 \n",
"72 29.355000 29.985000 29.496250 \n",
"... ... ... ... \n",
"6619 295.623322 306.916656 292.191666 \n",
"6620 285.576660 300.894989 284.501663 \n",
"6621 278.433319 290.599991 272.780834 \n",
"6622 267.493347 282.004990 258.272499 \n",
"6623 267.493347 275.799988 253.671661 \n",
"\n",
" Low_std_rolling_4 Low_skew_rolling_4 Low_max_rolling_4 \\\n",
"68 0.213399 0.530355 30.405001 \n",
"69 0.151218 1.120939 30.405001 \n",
"70 0.177862 1.371842 30.405001 \n",
"71 0.531427 -1.919709 30.155001 \n",
"72 0.686382 -0.045148 30.155001 \n",
"... ... ... ... \n",
"6619 9.454932 -1.153258 300.403320 \n",
"6620 14.528203 -0.246670 300.403320 \n",
"6621 16.234688 -0.101296 291.366669 \n",
"6622 19.658760 -0.506867 279.203339 \n",
"6623 14.640331 -1.203567 267.033325 \n",
"\n",
" Low_min_rolling_4 Low_median_rolling_4 High_mean_rolling_6 \\\n",
"68 29.902500 30.110000 30.552917 \n",
"69 30.045000 30.165000 30.599583 \n",
"70 30.012501 30.100000 30.624166 \n",
"71 29.014999 30.028750 30.487083 \n",
"72 28.802500 29.513750 30.234166 \n",
"... ... ... ... \n",
"6619 279.203339 294.580002 303.868886 \n",
"6620 267.033325 285.285004 300.578328 \n",
"6621 253.520004 273.118332 297.046102 \n",
"6622 233.333328 260.276665 290.350550 \n",
"6623 233.333328 257.159996 284.409993 \n",
"\n",
" High_std_rolling_6 High_skew_rolling_6 High_max_rolling_6 \\\n",
"68 0.325459 0.168935 30.955000 \n",
"69 0.276376 0.275333 30.955000 \n",
"70 0.250258 0.355497 30.955000 \n",
"71 0.518528 -1.604189 30.955000 \n",
"72 0.647089 -0.628943 30.955000 \n",
"... ... ... ... \n",
"6619 5.142155 -0.984845 308.809998 \n",
"6620 8.941387 -1.011483 308.809998 \n",
"6621 12.762273 -0.631437 308.809998 \n",
"6622 16.161465 -0.238081 308.809998 \n",
"6623 14.482806 0.516911 306.166656 \n",
"\n",
" High_min_rolling_6 High_median_rolling_6 Low_mean_rolling_6 \\\n",
"68 30.172501 30.506250 29.992916 \n",
"69 30.305000 30.562500 30.090833 \n",
"70 30.340000 30.562500 30.115834 \n",
"71 29.517500 30.562500 29.967917 \n",
"72 29.355000 30.452499 29.739167 \n",
"... ... ... ... \n",
"6619 295.623322 305.743332 289.452779 \n",
"6620 285.576660 302.896667 286.697220 \n",
"6621 278.433319 300.894989 281.553332 \n",
"6622 267.493347 290.599991 270.809998 \n",
"6623 267.493347 282.004990 264.209442 \n",
"\n",
" Low_std_rolling_6 Low_skew_rolling_6 Low_max_rolling_6 \\\n",
"68 0.287000 -0.048145 30.405001 \n",
"69 0.199804 0.496012 30.405001 \n",
"70 0.173123 0.767741 30.405001 \n",
"71 0.486807 -1.991487 30.405001 \n",
"72 0.661251 -0.814947 30.405001 \n",
"... ... ... ... \n",
"6619 8.468042 0.241799 300.403320 \n",
"6620 12.497726 -0.613790 300.403320 \n",
"6621 18.534195 -0.620976 300.403320 \n",
"6622 24.845513 -0.443312 300.403320 \n",
"6623 20.246131 -0.262949 291.366669 \n",
"\n",
" Low_min_rolling_6 Low_median_rolling_6 High_mean_rolling_8 \\\n",
"68 29.567499 29.973750 30.284688 \n",
"69 29.862499 30.100000 30.449375 \n",
"70 29.902500 30.100000 30.527812 \n",
"71 29.014999 30.100000 30.445937 \n",
"72 28.802500 30.028750 30.327187 \n",
"... ... ... ... \n",
"6619 279.203339 287.875000 306.654999 \n",
"6620 267.033325 287.875000 302.924164 \n",
"6621 253.520004 285.285004 298.402912 \n",
"6622 233.333328 273.118332 293.674580 \n",
"6623 233.333328 263.916656 290.367077 \n",
"\n",
" High_std_rolling_8 High_skew_rolling_8 High_max_rolling_8 \\\n",
"68 0.596944 -0.945052 30.955000 \n",
"69 0.374890 -0.190964 30.955000 \n",
"70 0.278963 0.513638 30.955000 \n",
"71 0.444908 -1.261241 30.955000 \n",
"72 0.590770 -0.919163 30.955000 \n",
"... ... ... ... \n",
"6619 6.749002 -0.312829 315.423340 \n",
"6620 9.062503 -0.945353 314.603333 \n",
"6621 11.178854 -1.005187 308.809998 \n",
"6622 15.134943 -0.749583 308.809998 \n",
"6623 16.479842 -0.141558 308.809998 \n",
"\n",
" High_min_rolling_8 High_median_rolling_8 Low_mean_rolling_8 \\\n",
"68 29.135000 30.322500 29.683750 \n",
"69 29.825001 30.396250 29.890937 \n",
"70 30.172501 30.452499 30.015625 \n",
"71 29.517500 30.452499 29.946563 \n",
"72 29.355000 30.452499 29.814063 \n",
"... ... ... ... \n",
"6619 295.623322 306.916656 292.785416 \n",
"6620 285.576660 305.743332 287.831249 \n",
"6621 278.433319 302.473343 282.158751 \n",
"6622 267.493347 297.625000 275.879581 \n",
"6623 267.493347 290.599991 272.931664 \n",
"\n",
" Low_std_rolling_8 Low_skew_rolling_8 Low_max_rolling_8 \\\n",
"68 0.636931 -1.041511 30.405001 \n",
"69 0.432805 -1.233687 30.405001 \n",
"70 0.249105 -0.359982 30.405001 \n",
"71 0.413461 -1.860894 30.405001 \n",
"72 0.580396 -1.199744 30.405001 \n",
"... ... ... ... \n",
"6619 9.675111 -0.087055 306.666656 \n",
"6620 11.522559 -0.669967 300.403320 \n",
"6621 15.705832 -0.800698 300.403320 \n",
"6622 23.278525 -0.894656 300.403320 \n",
"6623 23.539592 -0.420350 300.403320 \n",
"\n",
" Low_min_rolling_8 Low_median_rolling_8 log_return log_volume \\\n",
"68 28.497499 29.882500 -0.004621 -0.126494 \n",
"69 29.014999 29.973750 0.001157 -0.179845 \n",
"70 29.567499 30.028750 -0.004056 0.024782 \n",
"71 29.014999 30.028750 -0.032024 0.557132 \n",
"72 28.802500 30.028750 -0.005668 -0.268208 \n",
"... ... ... ... ... \n",
"6619 279.203339 294.580002 -0.022351 0.216287 \n",
"6620 267.033325 287.875000 -0.042246 0.195447 \n",
"6621 253.520004 283.975006 -0.072548 0.134272 \n",
"6622 233.333328 281.793335 0.046954 0.351081 \n",
"6623 233.333328 273.118332 0.011300 -0.576035 \n",
"\n",
" log_return__co_embed2_dist_tau_d_expfit_meandiff__w=30_catch \\\n",
"68 0.095161 \n",
"69 0.095468 \n",
"70 0.079102 \n",
"71 0.069762 \n",
"72 0.089185 \n",
"... ... \n",
"6619 0.098153 \n",
"6620 0.098166 \n",
"6621 0.097814 \n",
"6622 0.094199 \n",
"6623 0.089844 \n",
"\n",
" log_return__co_firstmin_ac__w=30_catch \\\n",
"68 2.0 \n",
"69 2.0 \n",
"70 2.0 \n",
"71 2.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 2.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_return__co_histogramami_even_2_5__w=30_catch \\\n",
"68 0.244176 \n",
"69 0.214961 \n",
"70 0.232680 \n",
"71 0.261533 \n",
"72 0.265111 \n",
"... ... \n",
"6619 0.232905 \n",
"6620 0.235336 \n",
"6621 0.246009 \n",
"6622 0.225208 \n",
"6623 0.230762 \n",
"\n",
" log_return__co_f1ecac__w=30_catch \\\n",
"68 0.569850 \n",
"69 0.574485 \n",
"70 0.567913 \n",
"71 0.516105 \n",
"72 0.550065 \n",
"... ... \n",
"6619 0.556793 \n",
"6620 0.559354 \n",
"6621 0.575685 \n",
"6622 0.594008 \n",
"6623 0.556260 \n",
"\n",
" log_return__co_trev_1_num__w=30_catch \\\n",
"68 -0.480451 \n",
"69 -0.472759 \n",
"70 -0.428801 \n",
"71 -0.461476 \n",
"72 -1.298579 \n",
"... ... \n",
"6619 -0.494393 \n",
"6620 -0.480247 \n",
"6621 -0.610911 \n",
"6622 -0.575053 \n",
"6623 0.132107 \n",
"\n",
" log_return__dn_histogrammode_10__w=30_catch \\\n",
"68 -0.567145 \n",
"69 -0.544240 \n",
"70 -0.552554 \n",
"71 -0.604113 \n",
"72 -0.596626 \n",
"... ... \n",
"6619 -0.349433 \n",
"6620 -0.348902 \n",
"6621 -0.342700 \n",
"6622 -0.255517 \n",
"6623 -0.279552 \n",
"\n",
" log_return__dn_histogrammode_5__w=30_catch \\\n",
"68 -0.340642 \n",
"69 -0.770317 \n",
"70 -0.778916 \n",
"71 -0.837640 \n",
"72 -0.828493 \n",
"... ... \n",
"6619 -0.082217 \n",
"6620 -0.081732 \n",
"6621 -0.076549 \n",
"6622 0.004405 \n",
"6623 -0.026577 \n",
"\n",
" log_return__dn_outlierinclude_n_001_mdrmd__w=30_catch \\\n",
"68 -0.100000 \n",
"69 -0.166667 \n",
"70 -0.233333 \n",
"71 -0.300000 \n",
"72 0.633333 \n",
"... ... \n",
"6619 -0.133333 \n",
"6620 -0.066667 \n",
"6621 -0.133333 \n",
"6622 0.166667 \n",
"6623 0.100000 \n",
"\n",
" log_return__dn_outlierinclude_p_001_mdrmd__w=30_catch \\\n",
"68 0.433333 \n",
"69 0.366667 \n",
"70 0.300000 \n",
"71 0.233333 \n",
"72 0.166667 \n",
"... ... \n",
"6619 0.133333 \n",
"6620 0.066667 \n",
"6621 0.000000 \n",
"6622 0.066667 \n",
"6623 0.133333 \n",
"\n",
" log_return__fc_localsimple_mean1_tauresrat__w=30_catch \\\n",
"68 1.0 \n",
"69 1.0 \n",
"70 1.0 \n",
"71 1.0 \n",
"72 1.0 \n",
"... ... \n",
"6619 1.0 \n",
"6620 1.0 \n",
"6621 1.0 \n",
"6622 1.0 \n",
"6623 1.0 \n",
"\n",
" log_return__fc_localsimple_mean3_stderr__w=30_catch \\\n",
"68 1.189575 \n",
"69 1.154024 \n",
"70 1.103884 \n",
"71 1.136336 \n",
"72 1.166204 \n",
"... ... \n",
"6619 1.286030 \n",
"6620 1.286934 \n",
"6621 1.268502 \n",
"6622 1.175494 \n",
"6623 1.211264 \n",
"\n",
" log_return__in_automutualinfostats_40_gaussian_fmmi__w=30_catch \\\n",
"68 3.0 \n",
"69 3.0 \n",
"70 3.0 \n",
"71 3.0 \n",
"72 3.0 \n",
"... ... \n",
"6619 2.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_return__md_hrv_classic_pnn40__w=30_catch \\\n",
"68 1.000000 \n",
"69 0.965517 \n",
"70 0.965517 \n",
"71 0.965517 \n",
"72 0.965517 \n",
"... ... \n",
"6619 1.000000 \n",
"6620 1.000000 \n",
"6621 1.000000 \n",
"6622 1.000000 \n",
"6623 1.000000 \n",
"\n",
" log_return__pd_periodicitywang_th0_01__w=30_catch \\\n",
"68 2.0 \n",
"69 2.0 \n",
"70 2.0 \n",
"71 2.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 3.0 \n",
"6620 3.0 \n",
"6621 3.0 \n",
"6622 3.0 \n",
"6623 3.0 \n",
"\n",
" log_return__sb_binarystats_diff_longstretch0__w=30_catch \\\n",
"68 3.0 \n",
"69 3.0 \n",
"70 3.0 \n",
"71 3.0 \n",
"72 3.0 \n",
"... ... \n",
"6619 4.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_return__sb_binarystats_mean_longstretch1__w=30_catch \\\n",
"68 4.0 \n",
"69 4.0 \n",
"70 4.0 \n",
"71 4.0 \n",
"72 4.0 \n",
"... ... \n",
"6619 4.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_return__sb_motifthree_quantile_hh__w=30_catch \\\n",
"68 2.157176 \n",
"69 2.157176 \n",
"70 2.136746 \n",
"71 2.116316 \n",
"72 2.136746 \n",
"... ... \n",
"6619 2.079612 \n",
"6620 2.079612 \n",
"6621 2.091330 \n",
"6622 2.127416 \n",
"6623 2.079612 \n",
"\n",
" log_return__sb_transitionmatrix_3ac_sumdiagcov__w=30_catch \\\n",
"68 0.004360 \n",
"69 0.004360 \n",
"70 0.006738 \n",
"71 0.009116 \n",
"72 0.006738 \n",
"... ... \n",
"6619 0.012683 \n",
"6620 0.012683 \n",
"6621 0.011494 \n",
"6622 0.006738 \n",
"6623 0.012683 \n",
"\n",
" log_return__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=30_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=30_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sp_summaries_welch_rect_area_5_1__w=30_catch \\\n",
"68 0.092229 \n",
"69 0.104590 \n",
"70 0.096154 \n",
"71 0.067739 \n",
"72 0.079195 \n",
"... ... \n",
"6619 0.047405 \n",
"6620 0.049837 \n",
"6621 0.054055 \n",
"6622 0.059445 \n",
"6623 0.047641 \n",
"\n",
" log_return__sp_summaries_welch_rect_centroid__w=30_catch \\\n",
"68 1.767146 \n",
"69 1.767146 \n",
"70 1.767146 \n",
"71 1.963495 \n",
"72 1.767146 \n",
"... ... \n",
"6619 1.767146 \n",
"6620 1.767146 \n",
"6621 1.767146 \n",
"6622 1.767146 \n",
"6623 1.767146 \n",
"\n",
" log_volume__co_embed2_dist_tau_d_expfit_meandiff__w=30_catch \\\n",
"68 0.122753 \n",
"69 0.122818 \n",
"70 0.106804 \n",
"71 0.147533 \n",
"72 0.148080 \n",
"... ... \n",
"6619 0.095840 \n",
"6620 0.094481 \n",
"6621 0.077613 \n",
"6622 0.075907 \n",
"6623 0.092173 \n",
"\n",
" log_volume__co_firstmin_ac__w=30_catch \\\n",
"68 1.0 \n",
"69 1.0 \n",
"70 1.0 \n",
"71 1.0 \n",
"72 1.0 \n",
"... ... \n",
"6619 2.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_volume__co_histogramami_even_2_5__w=30_catch \\\n",
"68 0.296343 \n",
"69 0.296343 \n",
"70 0.318965 \n",
"71 0.318965 \n",
"72 0.280127 \n",
"... ... \n",
"6619 0.343197 \n",
"6620 0.364532 \n",
"6621 0.354693 \n",
"6622 0.350217 \n",
"6623 0.316679 \n",
"\n",
" log_volume__co_f1ecac__w=30_catch \\\n",
"68 0.514873 \n",
"69 0.501089 \n",
"70 0.507912 \n",
"71 0.511102 \n",
"72 0.532618 \n",
"... ... \n",
"6619 0.602674 \n",
"6620 0.613450 \n",
"6621 0.633729 \n",
"6622 0.655783 \n",
"6623 0.711029 \n",
"\n",
" log_volume__co_trev_1_num__w=30_catch \\\n",
"68 0.630505 \n",
"69 0.705963 \n",
"70 0.712556 \n",
"71 0.574399 \n",
"72 0.934085 \n",
"... ... \n",
"6619 -1.014913 \n",
"6620 -0.955248 \n",
"6621 -0.934084 \n",
"6622 -0.739176 \n",
"6623 -1.185135 \n",
"\n",
" log_volume__dn_histogrammode_10__w=30_catch \\\n",
"68 -0.332749 \n",
"69 -0.279664 \n",
"70 -0.240025 \n",
"71 -0.253355 \n",
"72 -0.167130 \n",
"... ... \n",
"6619 0.692150 \n",
"6620 0.065480 \n",
"6621 0.027201 \n",
"6622 0.617197 \n",
"6623 0.521897 \n",
"\n",
" log_volume__dn_histogrammode_5__w=30_catch \\\n",
"68 -0.129058 \n",
"69 -0.070467 \n",
"70 -0.031539 \n",
"71 -0.044767 \n",
"72 0.042184 \n",
"... ... \n",
"6619 0.080088 \n",
"6620 -0.338097 \n",
"6621 0.027201 \n",
"6622 0.020467 \n",
"6623 0.322854 \n",
"\n",
" log_volume__dn_outlierinclude_n_001_mdrmd__w=30_catch \\\n",
"68 0.466667 \n",
"69 0.400000 \n",
"70 0.333333 \n",
"71 0.266667 \n",
"72 0.200000 \n",
"... ... \n",
"6619 0.133333 \n",
"6620 0.066667 \n",
"6621 0.000000 \n",
"6622 -0.066667 \n",
"6623 -0.066667 \n",
"\n",
" log_volume__dn_outlierinclude_p_001_mdrmd__w=30_catch \\\n",
"68 0.133333 \n",
"69 0.200000 \n",
"70 0.133333 \n",
"71 0.066667 \n",
"72 0.233333 \n",
"... ... \n",
"6619 -0.200000 \n",
"6620 -0.166667 \n",
"6621 -0.200000 \n",
"6622 -0.233333 \n",
"6623 -0.266667 \n",
"\n",
" log_volume__fc_localsimple_mean1_tauresrat__w=30_catch \\\n",
"68 1.0 \n",
"69 1.0 \n",
"70 1.0 \n",
"71 1.0 \n",
"72 1.0 \n",
"... ... \n",
"6619 1.0 \n",
"6620 1.0 \n",
"6621 0.5 \n",
"6622 0.5 \n",
"6623 0.5 \n",
"\n",
" log_volume__fc_localsimple_mean3_stderr__w=30_catch \\\n",
"68 1.221689 \n",
"69 1.244295 \n",
"70 1.242631 \n",
"71 1.246326 \n",
"72 1.269305 \n",
"... ... \n",
"6619 1.292727 \n",
"6620 1.259527 \n",
"6621 1.219930 \n",
"6622 1.210666 \n",
"6623 1.189032 \n",
"\n",
" log_volume__in_automutualinfostats_40_gaussian_fmmi__w=30_catch \\\n",
"68 1.0 \n",
"69 1.0 \n",
"70 1.0 \n",
"71 1.0 \n",
"72 1.0 \n",
"... ... \n",
"6619 3.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_volume__md_hrv_classic_pnn40__w=30_catch \\\n",
"68 1.000000 \n",
"69 1.000000 \n",
"70 1.000000 \n",
"71 1.000000 \n",
"72 1.000000 \n",
"... ... \n",
"6619 0.896552 \n",
"6620 0.896552 \n",
"6621 0.896552 \n",
"6622 0.896552 \n",
"6623 0.896552 \n",
"\n",
" log_volume__pd_periodicitywang_th0_01__w=30_catch \\\n",
"68 4.0 \n",
"69 4.0 \n",
"70 4.0 \n",
"71 3.0 \n",
"72 4.0 \n",
"... ... \n",
"6619 5.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 5.0 \n",
"6623 5.0 \n",
"\n",
" log_volume__sb_binarystats_diff_longstretch0__w=30_catch \\\n",
"68 3.0 \n",
"69 3.0 \n",
"70 3.0 \n",
"71 4.0 \n",
"72 4.0 \n",
"... ... \n",
"6619 4.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_volume__sb_binarystats_mean_longstretch1__w=30_catch \\\n",
"68 5.0 \n",
"69 6.0 \n",
"70 6.0 \n",
"71 6.0 \n",
"72 6.0 \n",
"... ... \n",
"6619 4.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_volume__sb_motifthree_quantile_hh__w=30_catch \\\n",
"68 2.070900 \n",
"69 2.106986 \n",
"70 2.165889 \n",
"71 2.145459 \n",
"72 2.127416 \n",
"... ... \n",
"6619 2.165889 \n",
"6620 2.165889 \n",
"6621 2.154171 \n",
"6622 2.154171 \n",
"6623 2.127416 \n",
"\n",
" log_volume__sb_transitionmatrix_3ac_sumdiagcov__w=30_catch \\\n",
"68 0.013872 \n",
"69 0.009116 \n",
"70 0.003171 \n",
"71 0.005549 \n",
"72 0.006738 \n",
"... ... \n",
"6619 0.003171 \n",
"6620 0.003171 \n",
"6621 0.045918 \n",
"6622 0.035714 \n",
"6623 0.035714 \n",
"\n",
" log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=30_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=30_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sp_summaries_welch_rect_area_5_1__w=30_catch \\\n",
"68 0.083112 \n",
"69 0.068988 \n",
"70 0.068875 \n",
"71 0.070950 \n",
"72 0.067448 \n",
"... ... \n",
"6619 0.052942 \n",
"6620 0.058035 \n",
"6621 0.059494 \n",
"6622 0.063137 \n",
"6623 0.096202 \n",
"\n",
" log_volume__sp_summaries_welch_rect_centroid__w=30_catch \\\n",
"68 1.767146 \n",
"69 1.767146 \n",
"70 1.767146 \n",
"71 1.767146 \n",
"72 1.767146 \n",
"... ... \n",
"6619 1.374447 \n",
"6620 1.374447 \n",
"6621 1.374447 \n",
"6622 1.374447 \n",
"6623 1.374447 \n",
"\n",
" log_return__co_embed2_dist_tau_d_expfit_meandiff__w=7_catch \\\n",
"68 0.299197 \n",
"69 0.317793 \n",
"70 0.261495 \n",
"71 0.264484 \n",
"72 0.170823 \n",
"... ... \n",
"6619 0.266694 \n",
"6620 0.269532 \n",
"6621 0.259763 \n",
"6622 0.183356 \n",
"6623 0.308423 \n",
"\n",
" log_return__co_firstmin_ac__w=7_catch \\\n",
"68 2.0 \n",
"69 2.0 \n",
"70 2.0 \n",
"71 2.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 2.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_return__co_histogramami_even_2_5__w=7_catch \\\n",
"68 0.777661 \n",
"69 0.673012 \n",
"70 0.395753 \n",
"71 0.673012 \n",
"72 1.054920 \n",
"... ... \n",
"6619 1.332179 \n",
"6620 1.609438 \n",
"6621 1.054920 \n",
"6622 0.777661 \n",
"6623 1.054920 \n",
"\n",
" log_return__co_f1ecac__w=7_catch log_return__co_trev_1_num__w=7_catch \\\n",
"68 0.480637 2.549341 \n",
"69 0.664897 -0.923284 \n",
"70 0.513450 0.114906 \n",
"71 0.613279 1.844260 \n",
"72 0.766199 -1.268410 \n",
"... ... ... \n",
"6619 0.719998 0.008043 \n",
"6620 0.843579 0.292701 \n",
"6621 0.795123 0.268400 \n",
"6622 1.108849 -0.516886 \n",
"6623 0.597968 2.082936 \n",
"\n",
" log_return__dn_histogrammode_10__w=7_catch \\\n",
"68 -0.834786 \n",
"69 -0.861110 \n",
"70 -0.005385 \n",
"71 -0.671667 \n",
"72 0.342343 \n",
"... ... \n",
"6619 -0.221599 \n",
"6620 -0.647848 \n",
"6621 -0.847711 \n",
"6622 0.008382 \n",
"6623 1.209102 \n",
"\n",
" log_return__dn_histogrammode_5__w=7_catch \\\n",
"68 -0.691156 \n",
"69 -0.715483 \n",
"70 -0.005385 \n",
"71 -0.800892 \n",
"72 0.189664 \n",
"... ... \n",
"6619 -0.086716 \n",
"6620 -0.511007 \n",
"6621 -0.715166 \n",
"6622 -0.421676 \n",
"6623 0.051144 \n",
"\n",
" log_return__dn_outlierinclude_n_001_mdrmd__w=7_catch \\\n",
"68 0.142857 \n",
"69 0.714286 \n",
"70 0.428571 \n",
"71 0.285714 \n",
"72 0.428571 \n",
"... ... \n",
"6619 -0.142857 \n",
"6620 0.142857 \n",
"6621 0.428571 \n",
"6622 0.714286 \n",
"6623 0.357143 \n",
"\n",
" log_return__dn_outlierinclude_p_001_mdrmd__w=7_catch \\\n",
"68 0.142857 \n",
"69 -0.142857 \n",
"70 -0.142857 \n",
"71 -0.285714 \n",
"72 -0.571429 \n",
"... ... \n",
"6619 0.285714 \n",
"6620 0.000000 \n",
"6621 -0.285714 \n",
"6622 -0.428571 \n",
"6623 0.142857 \n",
"\n",
" log_return__fc_localsimple_mean1_tauresrat__w=7_catch \\\n",
"68 1.0 \n",
"69 0.5 \n",
"70 1.0 \n",
"71 1.0 \n",
"72 0.5 \n",
"... ... \n",
"6619 1.0 \n",
"6620 1.0 \n",
"6621 1.0 \n",
"6622 0.5 \n",
"6623 1.0 \n",
"\n",
" log_return__fc_localsimple_mean3_stderr__w=7_catch \\\n",
"68 0.756944 \n",
"69 0.501012 \n",
"70 0.931942 \n",
"71 0.698654 \n",
"72 0.912410 \n",
"... ... \n",
"6619 1.673149 \n",
"6620 1.615362 \n",
"6621 0.793878 \n",
"6622 0.611061 \n",
"6623 1.220217 \n",
"\n",
" log_return__in_automutualinfostats_40_gaussian_fmmi__w=7_catch \\\n",
"68 4.0 \n",
"69 2.0 \n",
"70 2.0 \n",
"71 2.0 \n",
"72 1.0 \n",
"... ... \n",
"6619 2.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 1.0 \n",
"6623 2.0 \n",
"\n",
" log_return__md_hrv_classic_pnn40__w=7_catch \\\n",
"68 1.000000 \n",
"69 0.833333 \n",
"70 0.833333 \n",
"71 0.833333 \n",
"72 0.833333 \n",
"... ... \n",
"6619 1.000000 \n",
"6620 1.000000 \n",
"6621 1.000000 \n",
"6622 1.000000 \n",
"6623 1.000000 \n",
"\n",
" log_return__pd_periodicitywang_th0_01__w=7_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sb_binarystats_diff_longstretch0__w=7_catch \\\n",
"68 3.0 \n",
"69 3.0 \n",
"70 3.0 \n",
"71 3.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 2.0 \n",
"6620 3.0 \n",
"6621 3.0 \n",
"6622 3.0 \n",
"6623 3.0 \n",
"\n",
" log_return__sb_binarystats_mean_longstretch1__w=7_catch \\\n",
"68 3.0 \n",
"69 3.0 \n",
"70 3.0 \n",
"71 3.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 3.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 3.0 \n",
"6623 2.0 \n",
"\n",
" log_return__sb_motifthree_quantile_hh__w=7_catch \\\n",
"68 1.329661 \n",
"69 1.329661 \n",
"70 1.791759 \n",
"71 1.560710 \n",
"72 1.560710 \n",
"... ... \n",
"6619 1.560710 \n",
"6620 1.560710 \n",
"6621 1.791759 \n",
"6622 1.560710 \n",
"6623 1.560710 \n",
"\n",
" log_return__sb_transitionmatrix_3ac_sumdiagcov__w=7_catch \\\n",
"68 0.074074 \n",
"69 0.074074 \n",
"70 0.027778 \n",
"71 0.046296 \n",
"72 0.074074 \n",
"... ... \n",
"6619 0.111111 \n",
"6620 0.074074 \n",
"6621 0.111111 \n",
"6622 0.074074 \n",
"6623 0.046296 \n",
"\n",
" log_return__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=7_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=7_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sp_summaries_welch_rect_area_5_1__w=7_catch \\\n",
"68 3.521700e-33 \n",
"69 0.000000e+00 \n",
"70 0.000000e+00 \n",
"71 1.980957e-33 \n",
"72 8.804251e-34 \n",
"... ... \n",
"6619 1.375664e-33 \n",
"6620 1.375664e-33 \n",
"6621 8.804251e-34 \n",
"6622 2.201063e-34 \n",
"6623 8.804251e-34 \n",
"\n",
" log_return__sp_summaries_welch_rect_centroid__w=7_catch \\\n",
"68 2.356194 \n",
"69 1.570796 \n",
"70 1.570796 \n",
"71 1.570796 \n",
"72 1.570796 \n",
"... ... \n",
"6619 1.570796 \n",
"6620 1.570796 \n",
"6621 1.570796 \n",
"6622 0.785398 \n",
"6623 2.356194 \n",
"\n",
" log_volume__co_embed2_dist_tau_d_expfit_meandiff__w=7_catch \\\n",
"68 0.314143 \n",
"69 0.306827 \n",
"70 0.300086 \n",
"71 0.334889 \n",
"72 0.266615 \n",
"... ... \n",
"6619 0.220995 \n",
"6620 0.189978 \n",
"6621 0.201281 \n",
"6622 0.102434 \n",
"6623 0.178820 \n",
"\n",
" log_volume__co_firstmin_ac__w=7_catch \\\n",
"68 1.0 \n",
"69 1.0 \n",
"70 1.0 \n",
"71 1.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 3.0 \n",
"6620 3.0 \n",
"6621 3.0 \n",
"6622 4.0 \n",
"6623 7.0 \n",
"\n",
" log_volume__co_histogramami_even_2_5__w=7_catch \\\n",
"68 0.777661 \n",
"69 0.673012 \n",
"70 0.777661 \n",
"71 0.777661 \n",
"72 0.777661 \n",
"... ... \n",
"6619 0.673012 \n",
"6620 0.291103 \n",
"6621 0.395753 \n",
"6622 0.395753 \n",
"6623 0.500402 \n",
"\n",
" log_volume__co_f1ecac__w=7_catch log_volume__co_trev_1_num__w=7_catch \\\n",
"68 0.450078 0.551313 \n",
"69 0.426250 0.540610 \n",
"70 0.485318 3.344358 \n",
"71 0.439386 4.729709 \n",
"72 0.533983 2.637069 \n",
"... ... ... \n",
"6619 0.989436 -1.020333 \n",
"6620 0.997755 -0.911989 \n",
"6621 1.018607 -1.017264 \n",
"6622 1.550838 0.316151 \n",
"6623 1.095155 0.513473 \n",
"\n",
" log_volume__dn_histogrammode_10__w=7_catch \\\n",
"68 -0.636531 \n",
"69 -0.560419 \n",
"70 -0.419124 \n",
"71 0.244540 \n",
"72 -0.030272 \n",
"... ... \n",
"6619 -0.972822 \n",
"6620 -0.027046 \n",
"6621 0.937631 \n",
"6622 -0.008053 \n",
"6623 0.665110 \n",
"\n",
" log_volume__dn_histogrammode_5__w=7_catch \\\n",
"68 -0.088103 \n",
"69 -0.006693 \n",
"70 0.184533 \n",
"71 0.079263 \n",
"72 -0.178985 \n",
"... ... \n",
"6619 -0.850018 \n",
"6620 -0.027046 \n",
"6621 -0.049980 \n",
"6622 -0.920174 \n",
"6623 -0.226934 \n",
"\n",
" log_volume__dn_outlierinclude_n_001_mdrmd__w=7_catch \\\n",
"68 0.142857 \n",
"69 -0.142857 \n",
"70 -0.428571 \n",
"71 0.428571 \n",
"72 0.142857 \n",
"... ... \n",
"6619 0.428571 \n",
"6620 0.142857 \n",
"6621 -0.142857 \n",
"6622 -0.428571 \n",
"6623 -0.571429 \n",
"\n",
" log_volume__dn_outlierinclude_p_001_mdrmd__w=7_catch \\\n",
"68 0.142857 \n",
"69 -0.142857 \n",
"70 0.142857 \n",
"71 0.142857 \n",
"72 0.285714 \n",
"... ... \n",
"6619 -0.285714 \n",
"6620 -0.428571 \n",
"6621 0.714286 \n",
"6622 0.571429 \n",
"6623 0.428571 \n",
"\n",
" log_volume__fc_localsimple_mean1_tauresrat__w=7_catch \\\n",
"68 1.000000 \n",
"69 1.000000 \n",
"70 1.000000 \n",
"71 1.000000 \n",
"72 1.000000 \n",
"... ... \n",
"6619 1.000000 \n",
"6620 1.000000 \n",
"6621 1.000000 \n",
"6622 0.666667 \n",
"6623 0.333333 \n",
"\n",
" log_volume__fc_localsimple_mean3_stderr__w=7_catch \\\n",
"68 1.308474 \n",
"69 1.363292 \n",
"70 1.421991 \n",
"71 0.697898 \n",
"72 1.187704 \n",
"... ... \n",
"6619 1.460030 \n",
"6620 1.381918 \n",
"6621 0.862023 \n",
"6622 0.800823 \n",
"6623 0.699394 \n",
"\n",
" log_volume__in_automutualinfostats_40_gaussian_fmmi__w=7_catch \\\n",
"68 1.0 \n",
"69 1.0 \n",
"70 1.0 \n",
"71 2.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 4.0 \n",
"6620 4.0 \n",
"6621 1.0 \n",
"6622 2.0 \n",
"6623 1.0 \n",
"\n",
" log_volume__md_hrv_classic_pnn40__w=7_catch \\\n",
"68 1.000000 \n",
"69 1.000000 \n",
"70 1.000000 \n",
"71 1.000000 \n",
"72 1.000000 \n",
"... ... \n",
"6619 0.833333 \n",
"6620 0.833333 \n",
"6621 0.833333 \n",
"6622 0.833333 \n",
"6623 1.000000 \n",
"\n",
" log_volume__pd_periodicitywang_th0_01__w=7_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sb_binarystats_diff_longstretch0__w=7_catch \\\n",
"68 2.0 \n",
"69 2.0 \n",
"70 3.0 \n",
"71 4.0 \n",
"72 4.0 \n",
"... ... \n",
"6619 4.0 \n",
"6620 3.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 3.0 \n",
"\n",
" log_volume__sb_binarystats_mean_longstretch1__w=7_catch \\\n",
"68 2.0 \n",
"69 2.0 \n",
"70 3.0 \n",
"71 3.0 \n",
"72 2.0 \n",
"... ... \n",
"6619 3.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 3.0 \n",
"6623 3.0 \n",
"\n",
" log_volume__sb_motifthree_quantile_hh__w=7_catch \\\n",
"68 1.791759 \n",
"69 1.791759 \n",
"70 1.791759 \n",
"71 1.329661 \n",
"72 1.791759 \n",
"... ... \n",
"6619 1.791759 \n",
"6620 1.791759 \n",
"6621 1.791759 \n",
"6622 1.791759 \n",
"6623 1.560710 \n",
"\n",
" log_volume__sb_transitionmatrix_3ac_sumdiagcov__w=7_catch \\\n",
"68 0.027778 \n",
"69 0.018519 \n",
"70 0.018519 \n",
"71 0.083333 \n",
"72 0.018519 \n",
"... ... \n",
"6619 0.111111 \n",
"6620 0.074074 \n",
"6621 0.111111 \n",
"6622 0.166667 \n",
"6623 0.166667 \n",
"\n",
" log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=7_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=7_catch \\\n",
"68 0.0 \n",
"69 0.0 \n",
"70 0.0 \n",
"71 0.0 \n",
"72 0.0 \n",
"... ... \n",
"6619 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sp_summaries_welch_rect_area_5_1__w=7_catch \\\n",
"68 0.000000e+00 \n",
"69 3.521700e-33 \n",
"70 3.521700e-33 \n",
"71 8.804251e-34 \n",
"72 2.201063e-34 \n",
"... ... \n",
"6619 8.804251e-34 \n",
"6620 0.000000e+00 \n",
"6621 2.201063e-34 \n",
"6622 1.980957e-33 \n",
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" log_volume__sp_summaries_welch_rect_centroid__w=7_catch \n",
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" <th>log_volume__dn_histogrammode_5__w=7_catch</th>\n",
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" <th>log_volume__sb_binarystats_mean_longstretch1__w=7_catch</th>\n",
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" <th>log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=7_catch</th>\n",
" <th>log_volume__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=7_catch</th>\n",
" <th>log_volume__sp_summaries_welch_rect_area_5_1__w=7_catch</th>\n",
" <th>log_volume__sp_summaries_welch_rect_centroid__w=7_catch</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>68</th>\n",
" <td>2015-11-05</td>\n",
" <td>AAPL</td>\n",
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" <tr>\n",
" <th>69</th>\n",
" <td>2015-11-06</td>\n",
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" <td>-0.179845</td>\n",
" <td>0.095468</td>\n",
" <td>2.0</td>\n",
" <td>0.214961</td>\n",
" <td>0.574485</td>\n",
" <td>-0.472759</td>\n",
" <td>-0.544240</td>\n",
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" <td>-0.166667</td>\n",
" <td>0.366667</td>\n",
" <td>1.0</td>\n",
" <td>1.154024</td>\n",
" <td>3.0</td>\n",
" <td>0.965517</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>2.157176</td>\n",
" <td>0.004360</td>\n",
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" <td>0.104590</td>\n",
" <td>1.767146</td>\n",
" <td>0.122818</td>\n",
" <td>1.0</td>\n",
" <td>0.296343</td>\n",
" <td>0.501089</td>\n",
" <td>0.705963</td>\n",
" <td>-0.279664</td>\n",
" <td>-0.070467</td>\n",
" <td>0.400000</td>\n",
" <td>0.200000</td>\n",
" <td>1.0</td>\n",
" <td>1.244295</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>6.0</td>\n",
" <td>2.106986</td>\n",
" <td>0.009116</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.068988</td>\n",
" <td>1.767146</td>\n",
" <td>0.317793</td>\n",
" <td>2.0</td>\n",
" <td>0.673012</td>\n",
" <td>0.664897</td>\n",
" <td>-0.923284</td>\n",
" <td>-0.861110</td>\n",
" <td>-0.715483</td>\n",
" <td>0.714286</td>\n",
" <td>-0.142857</td>\n",
" <td>0.5</td>\n",
" <td>0.501012</td>\n",
" <td>2.0</td>\n",
" <td>0.833333</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.329661</td>\n",
" <td>0.074074</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000e+00</td>\n",
" <td>1.570796</td>\n",
" <td>0.306827</td>\n",
" <td>1.0</td>\n",
" <td>0.673012</td>\n",
" <td>0.426250</td>\n",
" <td>0.540610</td>\n",
" <td>-0.560419</td>\n",
" <td>-0.006693</td>\n",
" <td>-0.142857</td>\n",
" <td>-0.142857</td>\n",
" <td>1.000000</td>\n",
" <td>1.363292</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.018519</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.521700e-33</td>\n",
" <td>2.356194</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70</th>\n",
" <td>2015-11-09</td>\n",
" <td>AAPL</td>\n",
" <td>27.552839</td>\n",
" <td>30.142500</td>\n",
" <td>30.452499</td>\n",
" <td>30.012501</td>\n",
" <td>30.240000</td>\n",
" <td>135485600.0</td>\n",
" <td>2012-12-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.317500</td>\n",
" <td>29.807501</td>\n",
" <td>27.897829</td>\n",
" <td>28.869500</td>\n",
" <td>29.841171</td>\n",
" <td>6.731472</td>\n",
" <td>0.474528</td>\n",
" <td>28.350500</td>\n",
" <td>0.222930</td>\n",
" <td>0.183451</td>\n",
" <td>0.039479</td>\n",
" <td>30.525833</td>\n",
" <td>0.127018</td>\n",
" <td>1.732051</td>\n",
" <td>30.672501</td>\n",
" <td>30.452499</td>\n",
" <td>30.452499</td>\n",
" <td>30.070834</td>\n",
" <td>0.074680</td>\n",
" <td>1.370390</td>\n",
" <td>30.155001</td>\n",
" <td>30.012501</td>\n",
" <td>30.045000</td>\n",
" <td>30.633125</td>\n",
" <td>0.238331</td>\n",
" <td>1.064809</td>\n",
" <td>30.955000</td>\n",
" <td>30.452499</td>\n",
" <td>30.562500</td>\n",
" <td>30.154376</td>\n",
" <td>0.177862</td>\n",
" <td>1.371842</td>\n",
" <td>30.405001</td>\n",
" <td>30.012501</td>\n",
" <td>30.100000</td>\n",
" <td>30.624166</td>\n",
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" <td>30.955000</td>\n",
" <td>30.340000</td>\n",
" <td>30.562500</td>\n",
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" <td>30.405001</td>\n",
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" <td>0.106804</td>\n",
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" <td>0.507912</td>\n",
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" <td>1.767146</td>\n",
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" <td>-0.005385</td>\n",
" <td>0.428571</td>\n",
" <td>-0.142857</td>\n",
" <td>1.0</td>\n",
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" <td>2.0</td>\n",
" <td>0.833333</td>\n",
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" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.027778</td>\n",
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" <td>0.0</td>\n",
" <td>0.000000e+00</td>\n",
" <td>1.570796</td>\n",
" <td>0.300086</td>\n",
" <td>1.0</td>\n",
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" <td>0.485318</td>\n",
" <td>3.344358</td>\n",
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" <td>0.184533</td>\n",
" <td>-0.428571</td>\n",
" <td>0.142857</td>\n",
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" <td>1.421991</td>\n",
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" <td>3.0</td>\n",
" <td>1.791759</td>\n",
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" <td>3.521700e-33</td>\n",
" <td>2.356194</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>2015-11-10</td>\n",
" <td>AAPL</td>\n",
" <td>26.684456</td>\n",
" <td>29.192499</td>\n",
" <td>29.517500</td>\n",
" <td>29.014999</td>\n",
" <td>29.225000</td>\n",
" <td>236511600.0</td>\n",
" <td>2012-12-31</td>\n",
" <td>26.827499</td>\n",
" <td>28.317500</td>\n",
" <td>29.807501</td>\n",
" <td>27.994577</td>\n",
" <td>28.908500</td>\n",
" <td>29.822424</td>\n",
" <td>6.322870</td>\n",
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" <td>28.419500</td>\n",
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" <td>0.144641</td>\n",
" <td>0.075640</td>\n",
" <td>30.140833</td>\n",
" <td>0.539822</td>\n",
" <td>-1.732051</td>\n",
" <td>30.452499</td>\n",
" <td>29.517500</td>\n",
" <td>30.452499</td>\n",
" <td>29.727500</td>\n",
" <td>0.621144</td>\n",
" <td>-1.630060</td>\n",
" <td>30.155001</td>\n",
" <td>29.014999</td>\n",
" <td>30.012501</td>\n",
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" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560710</td>\n",
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" <td>0.0</td>\n",
" <td>1.980957e-33</td>\n",
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" <td>2.356194</td>\n",
" </tr>\n",
" <tr>\n",
" <th>72</th>\n",
" <td>2015-11-11</td>\n",
" <td>AAPL</td>\n",
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" <td>29.027500</td>\n",
" <td>29.355000</td>\n",
" <td>28.802500</td>\n",
" <td>29.092501</td>\n",
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" <td>2012-12-31</td>\n",
" <td>26.827499</td>\n",
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" <td>29.825001</td>\n",
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" <td>29.517500</td>\n",
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" <td>-0.571429</td>\n",
" <td>0.5</td>\n",
" <td>0.912410</td>\n",
" <td>1.0</td>\n",
" <td>0.833333</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.560710</td>\n",
" <td>0.074074</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.804251e-34</td>\n",
" <td>1.570796</td>\n",
" <td>0.266615</td>\n",
" <td>2.0</td>\n",
" <td>0.777661</td>\n",
" <td>0.533983</td>\n",
" <td>2.637069</td>\n",
" <td>-0.030272</td>\n",
" <td>-0.178985</td>\n",
" <td>0.142857</td>\n",
" <td>0.285714</td>\n",
" <td>1.000000</td>\n",
" <td>1.187704</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.018519</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.201063e-34</td>\n",
" <td>1.570796</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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6619</th>\n",
" <td>2022-02-18</td>\n",
" <td>TSLA</td>\n",
" <td>285.660004</td>\n",
" <td>285.660004</td>\n",
" <td>295.623322</td>\n",
" <td>279.203339</td>\n",
" <td>295.333344</td>\n",
" <td>68501700.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>295.373322</td>\n",
" <td>343.159988</td>\n",
" <td>390.946655</td>\n",
" <td>289.628083</td>\n",
" <td>313.788666</td>\n",
" <td>337.949248</td>\n",
" <td>15.399270</td>\n",
" <td>0.965662</td>\n",
" <td>320.952332</td>\n",
" <td>-9.463210</td>\n",
" <td>-3.049010</td>\n",
" <td>-6.414200</td>\n",
" <td>303.533325</td>\n",
" <td>6.976599</td>\n",
" <td>-1.456544</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>306.166656</td>\n",
" <td>290.324443</td>\n",
" <td>10.638350</td>\n",
" <td>-0.436628</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>291.366669</td>\n",
" <td>304.566658</td>\n",
" <td>6.059681</td>\n",
" <td>-1.812729</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>306.916656</td>\n",
" <td>292.191666</td>\n",
" <td>9.454932</td>\n",
" <td>-1.153258</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>294.580002</td>\n",
" <td>303.868886</td>\n",
" <td>5.142155</td>\n",
" <td>-0.984845</td>\n",
" <td>308.809998</td>\n",
" <td>295.623322</td>\n",
" <td>305.743332</td>\n",
" <td>289.452779</td>\n",
" <td>8.468042</td>\n",
" <td>0.241799</td>\n",
" <td>300.403320</td>\n",
" <td>279.203339</td>\n",
" <td>287.875000</td>\n",
" <td>306.654999</td>\n",
" <td>6.749002</td>\n",
" <td>-0.312829</td>\n",
" <td>315.423340</td>\n",
" <td>295.623322</td>\n",
" <td>306.916656</td>\n",
" <td>292.785416</td>\n",
" <td>9.675111</td>\n",
" <td>-0.087055</td>\n",
" <td>306.666656</td>\n",
" <td>279.203339</td>\n",
" <td>294.580002</td>\n",
" <td>-0.022351</td>\n",
" <td>0.216287</td>\n",
" <td>0.098153</td>\n",
" <td>2.0</td>\n",
" <td>0.232905</td>\n",
" <td>0.556793</td>\n",
" <td>-0.494393</td>\n",
" <td>-0.349433</td>\n",
" <td>-0.082217</td>\n",
" <td>-0.133333</td>\n",
" <td>0.133333</td>\n",
" <td>1.0</td>\n",
" <td>1.286030</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.079612</td>\n",
" <td>0.012683</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.047405</td>\n",
" <td>1.767146</td>\n",
" <td>0.095840</td>\n",
" <td>2.0</td>\n",
" <td>0.343197</td>\n",
" <td>0.602674</td>\n",
" <td>-1.014913</td>\n",
" <td>0.692150</td>\n",
" <td>0.080088</td>\n",
" <td>0.133333</td>\n",
" <td>-0.200000</td>\n",
" <td>1.0</td>\n",
" <td>1.292727</td>\n",
" <td>3.0</td>\n",
" <td>0.896552</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.165889</td>\n",
" <td>0.003171</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.052942</td>\n",
" <td>1.374447</td>\n",
" <td>0.266694</td>\n",
" <td>2.0</td>\n",
" <td>1.332179</td>\n",
" <td>0.719998</td>\n",
" <td>0.008043</td>\n",
" <td>-0.221599</td>\n",
" <td>-0.086716</td>\n",
" <td>-0.142857</td>\n",
" <td>0.285714</td>\n",
" <td>1.0</td>\n",
" <td>1.673149</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560710</td>\n",
" <td>0.111111</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.375664e-33</td>\n",
" <td>1.570796</td>\n",
" <td>0.220995</td>\n",
" <td>3.0</td>\n",
" <td>0.673012</td>\n",
" <td>0.989436</td>\n",
" <td>-1.020333</td>\n",
" <td>-0.972822</td>\n",
" <td>-0.850018</td>\n",
" <td>0.428571</td>\n",
" <td>-0.285714</td>\n",
" <td>1.000000</td>\n",
" <td>1.460030</td>\n",
" <td>4.0</td>\n",
" <td>0.833333</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.111111</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.804251e-34</td>\n",
" <td>0.785398</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6620</th>\n",
" <td>2022-02-22</td>\n",
" <td>TSLA</td>\n",
" <td>273.843323</td>\n",
" <td>273.843323</td>\n",
" <td>285.576660</td>\n",
" <td>267.033325</td>\n",
" <td>278.043335</td>\n",
" <td>83288100.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>295.373322</td>\n",
" <td>343.159988</td>\n",
" <td>390.946655</td>\n",
" <td>282.886134</td>\n",
" <td>323.127332</td>\n",
" <td>363.368529</td>\n",
" <td>24.907331</td>\n",
" <td>0.904304</td>\n",
" <td>323.058997</td>\n",
" <td>-6.431282</td>\n",
" <td>-0.013665</td>\n",
" <td>-6.417616</td>\n",
" <td>295.788879</td>\n",
" <td>10.295997</td>\n",
" <td>0.072341</td>\n",
" <td>306.166656</td>\n",
" <td>285.576660</td>\n",
" <td>295.623322</td>\n",
" <td>279.201111</td>\n",
" <td>12.166672</td>\n",
" <td>-0.000824</td>\n",
" <td>291.366669</td>\n",
" <td>267.033325</td>\n",
" <td>279.203339</td>\n",
" <td>299.044159</td>\n",
" <td>10.632924</td>\n",
" <td>-0.659913</td>\n",
" <td>308.809998</td>\n",
" <td>285.576660</td>\n",
" <td>300.894989</td>\n",
" <td>284.501663</td>\n",
" <td>14.528203</td>\n",
" <td>-0.246670</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>285.285004</td>\n",
" <td>300.578328</td>\n",
" <td>8.941387</td>\n",
" <td>-1.011483</td>\n",
" <td>308.809998</td>\n",
" <td>285.576660</td>\n",
" <td>302.896667</td>\n",
" <td>286.697220</td>\n",
" <td>12.497726</td>\n",
" <td>-0.613790</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>287.875000</td>\n",
" <td>302.924164</td>\n",
" <td>9.062503</td>\n",
" <td>-0.945353</td>\n",
" <td>314.603333</td>\n",
" <td>285.576660</td>\n",
" <td>305.743332</td>\n",
" <td>287.831249</td>\n",
" <td>11.522559</td>\n",
" <td>-0.669967</td>\n",
" <td>300.403320</td>\n",
" <td>267.033325</td>\n",
" <td>287.875000</td>\n",
" <td>-0.042246</td>\n",
" <td>0.195447</td>\n",
" <td>0.098166</td>\n",
" <td>2.0</td>\n",
" <td>0.235336</td>\n",
" <td>0.559354</td>\n",
" <td>-0.480247</td>\n",
" <td>-0.348902</td>\n",
" <td>-0.081732</td>\n",
" <td>-0.066667</td>\n",
" <td>0.066667</td>\n",
" <td>1.0</td>\n",
" <td>1.286934</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.079612</td>\n",
" <td>0.012683</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.049837</td>\n",
" <td>1.767146</td>\n",
" <td>0.094481</td>\n",
" <td>2.0</td>\n",
" <td>0.364532</td>\n",
" <td>0.613450</td>\n",
" <td>-0.955248</td>\n",
" <td>0.065480</td>\n",
" <td>-0.338097</td>\n",
" <td>0.066667</td>\n",
" <td>-0.166667</td>\n",
" <td>1.0</td>\n",
" <td>1.259527</td>\n",
" <td>2.0</td>\n",
" <td>0.896552</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.165889</td>\n",
" <td>0.003171</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.058035</td>\n",
" <td>1.374447</td>\n",
" <td>0.269532</td>\n",
" <td>2.0</td>\n",
" <td>1.609438</td>\n",
" <td>0.843579</td>\n",
" <td>0.292701</td>\n",
" <td>-0.647848</td>\n",
" <td>-0.511007</td>\n",
" <td>0.142857</td>\n",
" <td>0.000000</td>\n",
" <td>1.0</td>\n",
" <td>1.615362</td>\n",
" <td>4.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.560710</td>\n",
" <td>0.074074</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.375664e-33</td>\n",
" <td>1.570796</td>\n",
" <td>0.189978</td>\n",
" <td>3.0</td>\n",
" <td>0.291103</td>\n",
" <td>0.997755</td>\n",
" <td>-0.911989</td>\n",
" <td>-0.027046</td>\n",
" <td>-0.027046</td>\n",
" <td>0.142857</td>\n",
" <td>-0.428571</td>\n",
" <td>1.000000</td>\n",
" <td>1.381918</td>\n",
" <td>4.0</td>\n",
" <td>0.833333</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.074074</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.785398</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6621</th>\n",
" <td>2022-02-23</td>\n",
" <td>TSLA</td>\n",
" <td>254.679993</td>\n",
" <td>254.679993</td>\n",
" <td>278.433319</td>\n",
" <td>253.520004</td>\n",
" <td>276.809998</td>\n",
" <td>95256900.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>295.373322</td>\n",
" <td>343.159988</td>\n",
" <td>390.946655</td>\n",
" <td>284.742234</td>\n",
" <td>333.885333</td>\n",
" <td>383.028433</td>\n",
" <td>29.437112</td>\n",
" <td>0.812977</td>\n",
" <td>325.622662</td>\n",
" <td>-3.266195</td>\n",
" <td>2.521138</td>\n",
" <td>-5.787332</td>\n",
" <td>286.544434</td>\n",
" <td>8.635768</td>\n",
" <td>0.497962</td>\n",
" <td>295.623322</td>\n",
" <td>278.433319</td>\n",
" <td>285.576660</td>\n",
" <td>266.585556</td>\n",
" <td>12.847521</td>\n",
" <td>-0.156646</td>\n",
" <td>279.203339</td>\n",
" <td>253.520004</td>\n",
" <td>267.033325</td>\n",
" <td>291.449989</td>\n",
" <td>12.082035</td>\n",
" <td>0.322037</td>\n",
" <td>306.166656</td>\n",
" <td>278.433319</td>\n",
" <td>290.599991</td>\n",
" <td>272.780834</td>\n",
" <td>16.234688</td>\n",
" <td>-0.101296</td>\n",
" <td>291.366669</td>\n",
" <td>253.520004</td>\n",
" <td>273.118332</td>\n",
" <td>297.046102</td>\n",
" <td>12.762273</td>\n",
" <td>-0.631437</td>\n",
" <td>308.809998</td>\n",
" <td>278.433319</td>\n",
" <td>300.894989</td>\n",
" <td>281.553332</td>\n",
" <td>18.534195</td>\n",
" <td>-0.620976</td>\n",
" <td>300.403320</td>\n",
" <td>253.520004</td>\n",
" <td>285.285004</td>\n",
" <td>298.402912</td>\n",
" <td>11.178854</td>\n",
" <td>-1.005187</td>\n",
" <td>308.809998</td>\n",
" <td>278.433319</td>\n",
" <td>302.473343</td>\n",
" <td>282.158751</td>\n",
" <td>15.705832</td>\n",
" <td>-0.800698</td>\n",
" <td>300.403320</td>\n",
" <td>253.520004</td>\n",
" <td>283.975006</td>\n",
" <td>-0.072548</td>\n",
" <td>0.134272</td>\n",
" <td>0.097814</td>\n",
" <td>2.0</td>\n",
" <td>0.246009</td>\n",
" <td>0.575685</td>\n",
" <td>-0.610911</td>\n",
" <td>-0.342700</td>\n",
" <td>-0.076549</td>\n",
" <td>-0.133333</td>\n",
" <td>0.000000</td>\n",
" <td>1.0</td>\n",
" <td>1.268502</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.091330</td>\n",
" <td>0.011494</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.054055</td>\n",
" <td>1.767146</td>\n",
" <td>0.077613</td>\n",
" <td>2.0</td>\n",
" <td>0.354693</td>\n",
" <td>0.633729</td>\n",
" <td>-0.934084</td>\n",
" <td>0.027201</td>\n",
" <td>0.027201</td>\n",
" <td>0.000000</td>\n",
" <td>-0.200000</td>\n",
" <td>0.5</td>\n",
" <td>1.219930</td>\n",
" <td>2.0</td>\n",
" <td>0.896552</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.154171</td>\n",
" <td>0.045918</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.059494</td>\n",
" <td>1.374447</td>\n",
" <td>0.259763</td>\n",
" <td>2.0</td>\n",
" <td>1.054920</td>\n",
" <td>0.795123</td>\n",
" <td>0.268400</td>\n",
" <td>-0.847711</td>\n",
" <td>-0.715166</td>\n",
" <td>0.428571</td>\n",
" <td>-0.285714</td>\n",
" <td>1.0</td>\n",
" <td>0.793878</td>\n",
" <td>4.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.111111</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.804251e-34</td>\n",
" <td>1.570796</td>\n",
" <td>0.201281</td>\n",
" <td>3.0</td>\n",
" <td>0.395753</td>\n",
" <td>1.018607</td>\n",
" <td>-1.017264</td>\n",
" <td>0.937631</td>\n",
" <td>-0.049980</td>\n",
" <td>-0.142857</td>\n",
" <td>0.714286</td>\n",
" <td>1.000000</td>\n",
" <td>0.862023</td>\n",
" <td>1.0</td>\n",
" <td>0.833333</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.111111</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.201063e-34</td>\n",
" <td>0.785398</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6622</th>\n",
" <td>2022-02-24</td>\n",
" <td>TSLA</td>\n",
" <td>266.923340</td>\n",
" <td>266.923340</td>\n",
" <td>267.493347</td>\n",
" <td>233.333328</td>\n",
" <td>233.463333</td>\n",
" <td>135322200.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>295.373322</td>\n",
" <td>343.159988</td>\n",
" <td>390.946655</td>\n",
" <td>307.294982</td>\n",
" <td>346.453998</td>\n",
" <td>385.613013</td>\n",
" <td>22.605608</td>\n",
" <td>0.709011</td>\n",
" <td>329.691330</td>\n",
" <td>-0.894655</td>\n",
" <td>3.914142</td>\n",
" <td>-4.808797</td>\n",
" <td>277.167775</td>\n",
" <td>9.107840</td>\n",
" <td>-0.613207</td>\n",
" <td>285.576660</td>\n",
" <td>267.493347</td>\n",
" <td>278.433319</td>\n",
" <td>251.295553</td>\n",
" <td>16.959764</td>\n",
" <td>-0.580069</td>\n",
" <td>267.033325</td>\n",
" <td>233.333328</td>\n",
" <td>253.520004</td>\n",
" <td>281.781662</td>\n",
" <td>11.851313</td>\n",
" <td>-0.099319</td>\n",
" <td>295.623322</td>\n",
" <td>267.493347</td>\n",
" <td>282.004990</td>\n",
" <td>258.272499</td>\n",
" <td>19.658760</td>\n",
" <td>-0.506867</td>\n",
" <td>279.203339</td>\n",
" <td>233.333328</td>\n",
" <td>260.276665</td>\n",
" <td>290.350550</td>\n",
" <td>16.161465</td>\n",
" <td>-0.238081</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>290.599991</td>\n",
" <td>270.809998</td>\n",
" <td>24.845513</td>\n",
" <td>-0.443312</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>273.118332</td>\n",
" <td>293.674580</td>\n",
" <td>15.134943</td>\n",
" <td>-0.749583</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>297.625000</td>\n",
" <td>275.879581</td>\n",
" <td>23.278525</td>\n",
" <td>-0.894656</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>281.793335</td>\n",
" <td>0.046954</td>\n",
" <td>0.351081</td>\n",
" <td>0.094199</td>\n",
" <td>2.0</td>\n",
" <td>0.225208</td>\n",
" <td>0.594008</td>\n",
" <td>-0.575053</td>\n",
" <td>-0.255517</td>\n",
" <td>0.004405</td>\n",
" <td>0.166667</td>\n",
" <td>0.066667</td>\n",
" <td>1.0</td>\n",
" <td>1.175494</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.127416</td>\n",
" <td>0.006738</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.059445</td>\n",
" <td>1.767146</td>\n",
" <td>0.075907</td>\n",
" <td>2.0</td>\n",
" <td>0.350217</td>\n",
" <td>0.655783</td>\n",
" <td>-0.739176</td>\n",
" <td>0.617197</td>\n",
" <td>0.020467</td>\n",
" <td>-0.066667</td>\n",
" <td>-0.233333</td>\n",
" <td>0.5</td>\n",
" <td>1.210666</td>\n",
" <td>2.0</td>\n",
" <td>0.896552</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.154171</td>\n",
" <td>0.035714</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.063137</td>\n",
" <td>1.374447</td>\n",
" <td>0.183356</td>\n",
" <td>2.0</td>\n",
" <td>0.777661</td>\n",
" <td>1.108849</td>\n",
" <td>-0.516886</td>\n",
" <td>0.008382</td>\n",
" <td>-0.421676</td>\n",
" <td>0.714286</td>\n",
" <td>-0.428571</td>\n",
" <td>0.5</td>\n",
" <td>0.611061</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560710</td>\n",
" <td>0.074074</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.201063e-34</td>\n",
" <td>0.785398</td>\n",
" <td>0.102434</td>\n",
" <td>4.0</td>\n",
" <td>0.395753</td>\n",
" <td>1.550838</td>\n",
" <td>0.316151</td>\n",
" <td>-0.008053</td>\n",
" <td>-0.920174</td>\n",
" <td>-0.428571</td>\n",
" <td>0.571429</td>\n",
" <td>0.666667</td>\n",
" <td>0.800823</td>\n",
" <td>2.0</td>\n",
" <td>0.833333</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>1.791759</td>\n",
" <td>0.166667</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.980957e-33</td>\n",
" <td>0.785398</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6623</th>\n",
" <td>2022-02-25</td>\n",
" <td>TSLA</td>\n",
" <td>269.956665</td>\n",
" <td>269.956665</td>\n",
" <td>273.166656</td>\n",
" <td>260.799988</td>\n",
" <td>269.743347</td>\n",
" <td>76067700.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>295.373322</td>\n",
" <td>343.159988</td>\n",
" <td>390.946655</td>\n",
" <td>335.393692</td>\n",
" <td>356.297998</td>\n",
" <td>377.202304</td>\n",
" <td>11.734170</td>\n",
" <td>0.637898</td>\n",
" <td>333.947330</td>\n",
" <td>0.912957</td>\n",
" <td>4.577403</td>\n",
" <td>-3.664446</td>\n",
" <td>273.031108</td>\n",
" <td>5.471245</td>\n",
" <td>-0.111418</td>\n",
" <td>278.433319</td>\n",
" <td>267.493347</td>\n",
" <td>273.166656</td>\n",
" <td>249.217773</td>\n",
" <td>14.229766</td>\n",
" <td>-1.236165</td>\n",
" <td>260.799988</td>\n",
" <td>233.333328</td>\n",
" <td>253.520004</td>\n",
" <td>276.167496</td>\n",
" <td>7.700914</td>\n",
" <td>0.240825</td>\n",
" <td>285.576660</td>\n",
" <td>267.493347</td>\n",
" <td>275.799988</td>\n",
" <td>253.671661</td>\n",
" <td>14.640331</td>\n",
" <td>-1.203567</td>\n",
" <td>267.033325</td>\n",
" <td>233.333328</td>\n",
" <td>257.159996</td>\n",
" <td>284.409993</td>\n",
" <td>14.482806</td>\n",
" <td>0.516911</td>\n",
" <td>306.166656</td>\n",
" <td>267.493347</td>\n",
" <td>282.004990</td>\n",
" <td>264.209442</td>\n",
" <td>20.246131</td>\n",
" <td>-0.262949</td>\n",
" <td>291.366669</td>\n",
" <td>233.333328</td>\n",
" <td>263.916656</td>\n",
" <td>290.367077</td>\n",
" <td>16.479842</td>\n",
" <td>-0.141558</td>\n",
" <td>308.809998</td>\n",
" <td>267.493347</td>\n",
" <td>290.599991</td>\n",
" <td>272.931664</td>\n",
" <td>23.539592</td>\n",
" <td>-0.420350</td>\n",
" <td>300.403320</td>\n",
" <td>233.333328</td>\n",
" <td>273.118332</td>\n",
" <td>0.011300</td>\n",
" <td>-0.576035</td>\n",
" <td>0.089844</td>\n",
" <td>2.0</td>\n",
" <td>0.230762</td>\n",
" <td>0.556260</td>\n",
" <td>0.132107</td>\n",
" <td>-0.279552</td>\n",
" <td>-0.026577</td>\n",
" <td>0.100000</td>\n",
" <td>0.133333</td>\n",
" <td>1.0</td>\n",
" <td>1.211264</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.079612</td>\n",
" <td>0.012683</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.047641</td>\n",
" <td>1.767146</td>\n",
" <td>0.092173</td>\n",
" <td>2.0</td>\n",
" <td>0.316679</td>\n",
" <td>0.711029</td>\n",
" <td>-1.185135</td>\n",
" <td>0.521897</td>\n",
" <td>0.322854</td>\n",
" <td>-0.066667</td>\n",
" <td>-0.266667</td>\n",
" <td>0.5</td>\n",
" <td>1.189032</td>\n",
" <td>2.0</td>\n",
" <td>0.896552</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.127416</td>\n",
" <td>0.035714</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.096202</td>\n",
" <td>1.374447</td>\n",
" <td>0.308423</td>\n",
" <td>2.0</td>\n",
" <td>1.054920</td>\n",
" <td>0.597968</td>\n",
" <td>2.082936</td>\n",
" <td>1.209102</td>\n",
" <td>0.051144</td>\n",
" <td>0.357143</td>\n",
" <td>0.142857</td>\n",
" <td>1.0</td>\n",
" <td>1.220217</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>1.560710</td>\n",
" <td>0.046296</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.804251e-34</td>\n",
" <td>2.356194</td>\n",
" <td>0.178820</td>\n",
" <td>7.0</td>\n",
" <td>0.500402</td>\n",
" <td>1.095155</td>\n",
" <td>0.513473</td>\n",
" <td>0.665110</td>\n",
" <td>-0.226934</td>\n",
" <td>-0.571429</td>\n",
" <td>0.428571</td>\n",
" <td>0.333333</td>\n",
" <td>0.699394</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560710</td>\n",
" <td>0.166667</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.980957e-33</td>\n",
" <td>0.785398</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>6304 rows × 159 columns</p>\n",
"</div>\n",
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]
},
"metadata": {},
"execution_count": 107
}
]
},
{
"cell_type": "markdown",
"source": [
"Let's add some date features"
],
"metadata": {
"id": "MIduAF4V6DwY"
}
},
{
"cell_type": "code",
"source": [
"def date_feats(df,date=\"Date\"):\n",
" df['year_date'] = df[date].dt.year\n",
" df['month_date'] = df[date].dt.month\n",
" df['quarter_date'] = df[date].dt.quarter\n",
" df['semester_date'] = np.where(df.quarter_date.isin([1,2]),1,2)\n",
" df['dayofweek_date'] = df[date].dt.dayofweek\n",
" df['dayofyear_date'] = df[date].dt.dayofyear\n",
" df['weekofyear_date'] = df[date].dt.weekofyear\n",
" df['sin_month_date'] = (np.sin(2 * np.pi * df.month_date/12))\n",
" df['cos_month_date'] = (np.cos(2 * np.pi * df.month_date/12))\n",
" df['sin_quarter_date'] = (np.sin(2 * np.pi * df.quarter_date/4))\n",
" df['cos_quarter_date'] = (np.cos(2 * np.pi * df.quarter_date/4))\n",
" df['sin_dayofweek_date'] = (np.sin(2 * np.pi * df.dayofweek_date/7))\n",
" df['cos_dayofweek_date'] = (np.cos(2 * np.pi * df.dayofweek_date/7))\n",
" df['sin_weekofyear_date'] = (np.sin(2 * np.pi * df.weekofyear_date/df['weekofyear_date'].nunique()))\n",
" df['cos_weekofyear_date'] = (np.cos(2 * np.pi * df.weekofyear_date/df['weekofyear_date'].nunique()))\n",
" return df"
],
"metadata": {
"id": "ozclk2N26Gx3"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_price_tranformed = date_feats(df_pricing_tech_and_rolling_and_signal)"
],
"metadata": {
"id": "hPhCKd0W8Re_"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Let's have a look at the memory usage"
],
"metadata": {
"id": "UJyccw32065-"
}
},
{
"cell_type": "code",
"source": [
"df_price_tranformed.info()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LF2ppvvC08m1",
"outputId": "cb56f30b-edf5-4b5e-950e-e26ef0db6dc2"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 6624 entries, 0 to 6623\n",
"Columns: 174 entries, Date to cos_weekofyear_date\n",
"dtypes: datetime64[ns](2), float64(164), int64(7), object(1)\n",
"memory usage: 8.8+ MB\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import gc\n",
"\n",
"def reduce_mem_usage(df):\n",
" \"\"\" iterate through all the columns of a dataframe and modify the data type\n",
" to reduce memory usage.\n",
" \"\"\"\n",
" start_mem = df.memory_usage().sum() / 1024**2\n",
" print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))\n",
"\n",
" for col in df.columns:\n",
" col_type = df[col].dtype\n",
" gc.collect()\n",
" if col_type not in [object,\"datetime64[ns]\"]:\n",
" c_min = df[col].min()\n",
" c_max = df[col].max()\n",
" if str(col_type)[:3] == 'int':\n",
" if c_min > np.iinfo(np.int8).min and c_max < np.iinfo(np.int8).max:\n",
" df[col] = df[col].astype(np.int8)\n",
" elif c_min > np.iinfo(np.int16).min and c_max < np.iinfo(np.int16).max:\n",
" df[col] = df[col].astype(np.int16)\n",
" elif c_min > np.iinfo(np.int32).min and c_max < np.iinfo(np.int32).max:\n",
" df[col] = df[col].astype(np.int32)\n",
" elif c_min > np.iinfo(np.int64).min and c_max < np.iinfo(np.int64).max:\n",
" df[col] = df[col].astype(np.int64)\n",
" else:\n",
" if c_min > np.finfo(np.float16).min and c_max < np.finfo(np.float16).max:\n",
" df[col] = df[col].astype(np.float16)\n",
" elif c_min > np.finfo(np.float32).min and c_max < np.finfo(np.float32).max:\n",
" df[col] = df[col].astype(np.float32)\n",
" else:\n",
" df[col] = df[col].astype(np.float64)\n",
" # else:\n",
" # df[col] = df[col].astype('category')\n",
"\n",
" end_mem = df.memory_usage().sum() / 1024**2\n",
" print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n",
" print('Decreased by {:.1f}%'.format(100 * (start_mem - end_mem) / start_mem))\n",
"\n",
" return df"
],
"metadata": {
"id": "pHSmkZ4_ybL_"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_price_tranformed = reduce_mem_usage(df_price_tranformed)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "j9OHm10J1Au9",
"outputId": "17ad5f5a-c61a-4d2c-c456-6853a249552b"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Memory usage of dataframe is 8.79 MB\n",
"Memory usage after optimization is: 2.29 MB\n",
"Decreased by 73.9%\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Why don't we create a target to set us up for a machine learning problem"
],
"metadata": {
"id": "-KWCH4xp866S"
}
},
{
"cell_type": "code",
"source": [
"df_price_tranformed = df_price_tranformed.dropna()"
],
"metadata": {
"id": "1HKlY3pL86VC"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def log_return_by_ticker(df, feature=\"price\", ticker=\"ticker\", name=\"return\"):\n",
" df[\"{}\".format(name)] = df[feature].groupby(df[ticker]).pct_change()\n",
" df[\"log_{}\".format(name)] = np.log(df[feature]).groupby(df[ticker]).diff()\n",
" return df"
],
"metadata": {
"id": "B3QdMIT29Acy"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_price_tranformed = log_return_by_ticker(df_price_tranformed, feature=\"Adj Close\", ticker=ticker, name=\"return\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "PEyb8iAL9QoR",
"outputId": "48702a38-729c-4e70-c32d-f3ad36460ec1"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"<ipython-input-114-91f862a87df4>:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df[\"{}\".format(name)] = df[feature].groupby(df[ticker]).pct_change()\n",
"<ipython-input-114-91f862a87df4>:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df[\"log_{}\".format(name)] = np.log(df[feature]).groupby(df[ticker]).diff()\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"df_price_tranformed[\"log_return\"]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Du5XRUON9s4V",
"outputId": "009de406-0aa3-4498-e140-fabe80ac6d1a"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"68 NaN\n",
"69 0.001953\n",
"70 -0.003906\n",
"71 -0.031250\n",
"72 -0.005859\n",
" ... \n",
"6619 -0.019531\n",
"6620 -0.042969\n",
"6621 -0.074219\n",
"6622 0.046875\n",
"6623 0.011719\n",
"Name: log_return, Length: 6304, dtype: float16"
]
},
"metadata": {},
"execution_count": 116
}
]
},
{
"cell_type": "code",
"source": [
"df_price_tranformed[\"Target\"] = df_price_tranformed.groupby(ticker)[\"log_return\"].shift(-1)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "WUc31VRcDPDy",
"outputId": "f6ab4c2f-1597-4b49-db5e-0466c6a8d51c"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"<ipython-input-135-bd43e38305d9>:1: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df_price_tranformed[\"Target\"] = df_price_tranformed.groupby(ticker)[\"log_return\"].shift(-1)\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Let's run a quick model"
],
"metadata": {
"id": "gvdUVBr4_E02"
}
},
{
"cell_type": "code",
"source": [
"!pip install flaml"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Je4_9ryN_wZY",
"outputId": "f2cd0376-7c75-4c36-a1c2-016b170b8a2b"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Collecting flaml\n",
" Downloading FLAML-1.1.2-py3-none-any.whl (222 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m222.3/222.3 KB\u001b[0m \u001b[31m10.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: pandas>=1.1.4 in /usr/local/lib/python3.8/dist-packages (from flaml) (1.3.5)\n",
"Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.8/dist-packages (from flaml) (1.7.3)\n",
"Requirement already satisfied: scikit-learn>=0.24 in /usr/local/lib/python3.8/dist-packages (from flaml) (1.0.2)\n",
"Requirement already satisfied: xgboost>=0.90 in /usr/local/lib/python3.8/dist-packages (from flaml) (0.90)\n",
"Collecting lightgbm>=2.3.1\n",
" Downloading lightgbm-3.3.5-py3-none-manylinux1_x86_64.whl (2.0 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m74.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: NumPy>=1.17.0rc1 in /usr/local/lib/python3.8/dist-packages (from flaml) (1.22.4)\n",
"Requirement already satisfied: wheel in /usr/local/lib/python3.8/dist-packages (from lightgbm>=2.3.1->flaml) (0.38.4)\n",
"Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=1.1.4->flaml) (2.8.2)\n",
"Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=1.1.4->flaml) (2022.7.1)\n",
"Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.8/dist-packages (from scikit-learn>=0.24->flaml) (1.2.0)\n",
"Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn>=0.24->flaml) (3.1.0)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas>=1.1.4->flaml) (1.15.0)\n",
"Installing collected packages: lightgbm, flaml\n",
" Attempting uninstall: lightgbm\n",
" Found existing installation: lightgbm 2.2.3\n",
" Uninstalling lightgbm-2.2.3:\n",
" Successfully uninstalled lightgbm-2.2.3\n",
"Successfully installed flaml-1.1.2 lightgbm-3.3.5\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from datetime import datetime\n",
"\n",
"test_date = \"2022-02-22\"\n",
"test_date = datetime.strptime(test_date, '%Y-%m-%d').date()\n",
"\n",
"train_df = df_price_tranformed[df_price_tranformed[\"Date\"]<pd.to_datetime(test_date)].copy()\n",
"test_df = df_price_tranformed[df_price_tranformed[\"Date\"]>=pd.to_datetime(test_date)].copy()"
],
"metadata": {
"id": "JXbefKPy_TnX"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"test_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 633
},
"id": "Is2yTJklAAPO",
"outputId": "0ad8c5cb-92fe-43ce-b197-027da0f911aa"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Date Ticker Adj Close Close High Low Open \\\n",
"1652 2022-02-22 AAPL 163.375 164.375 166.750 162.125 165.000 \n",
"1653 2022-02-23 AAPL 159.125 160.125 166.125 159.750 165.500 \n",
"1654 2022-02-24 AAPL 161.750 162.750 162.875 152.000 152.625 \n",
"1655 2022-02-25 AAPL 163.875 164.875 165.125 160.875 163.875 \n",
"3308 2022-02-22 JPM 147.000 151.875 153.250 150.375 150.625 \n",
"3309 2022-02-23 JPM 144.000 148.750 153.250 148.000 153.125 \n",
"3310 2022-02-24 JPM 139.875 144.500 145.000 139.750 143.000 \n",
"3311 2022-02-25 JPM 143.250 148.000 150.125 144.875 145.250 \n",
"4964 2022-02-22 MSFT 285.000 287.750 291.500 284.500 285.000 \n",
"4965 2022-02-23 MSFT 277.500 280.250 291.750 280.000 290.250 \n",
"4966 2022-02-24 MSFT 291.750 294.500 295.250 271.500 272.500 \n",
"4967 2022-02-25 MSFT 294.500 297.250 297.750 291.750 295.250 \n",
"6620 2022-02-22 TSLA 273.750 273.750 285.500 267.000 278.000 \n",
"6621 2022-02-23 TSLA 254.625 254.625 278.500 253.500 276.750 \n",
"6622 2022-02-24 TSLA 267.000 267.000 267.500 233.375 233.500 \n",
"6623 2022-02-25 TSLA 270.000 270.000 273.250 260.750 269.750 \n",
"\n",
" Volume date_old DCL_20_20 DCM_20_20 DCU_20_20 BBL_5_2.0 \\\n",
"1652 91162800.0 2019-03-31 154.750 166.000 177.125 170.375 \n",
"1653 90009200.0 2019-03-31 154.750 166.000 177.125 170.375 \n",
"1654 141147504.0 2019-03-31 154.750 166.000 177.125 170.250 \n",
"1655 91974200.0 2019-03-31 154.750 165.625 176.625 169.875 \n",
"3308 11333500.0 2019-03-31 139.625 154.750 169.750 142.750 \n",
"3309 11799000.0 2019-03-31 139.625 154.750 169.750 143.625 \n",
"3310 25655100.0 2019-03-31 139.625 154.750 169.750 143.875 \n",
"3311 18367700.0 2019-03-31 139.625 154.750 169.750 143.750 \n",
"4964 41736100.0 2019-03-31 310.000 327.250 344.250 304.250 \n",
"4965 37811200.0 2019-03-31 304.750 324.500 344.250 306.000 \n",
"4966 56989700.0 2019-03-31 304.750 324.500 344.250 313.000 \n",
"4967 32546700.0 2019-03-31 304.750 324.500 344.250 311.750 \n",
"6620 83288096.0 2019-03-31 295.250 343.250 391.000 283.000 \n",
"6621 95256896.0 2019-03-31 295.250 343.250 391.000 284.750 \n",
"6622 135322208.0 2019-03-31 295.250 343.250 391.000 307.250 \n",
"6623 76067696.0 2019-03-31 295.250 343.250 391.000 335.500 \n",
"\n",
" BBM_5_2.0 BBU_5_2.0 BBB_5_2.0 BBP_5_2.0 SMA_10 MACD_12_26_9 \\\n",
"1652 173.500 176.500 3.525391 0.202393 169.125 0.368652 \n",
"1653 173.500 176.625 3.603516 0.708984 170.625 0.678711 \n",
"1654 173.625 177.000 3.912109 0.893066 172.250 1.029297 \n",
"1655 173.500 177.000 4.125000 0.313232 173.625 0.960449 \n",
"3308 147.625 152.375 6.484375 0.225342 156.750 -3.431641 \n",
"3309 146.625 149.625 4.152344 0.483643 154.625 -3.802734 \n",
"3310 146.375 148.875 3.402344 0.799316 152.750 -3.941406 \n",
"3311 146.000 148.250 3.095703 0.356689 150.375 -4.210938 \n",
"4964 321.500 338.750 10.726562 0.280518 331.000 -2.666016 \n",
"4965 317.500 329.250 7.328125 0.360596 328.000 -3.462891 \n",
"4966 314.750 316.500 1.164062 0.573730 325.500 -3.990234 \n",
"4967 315.000 318.250 2.076172 0.986816 323.000 -4.093750 \n",
"6620 323.250 363.250 24.906250 0.904297 323.000 -6.429688 \n",
"6621 334.000 383.000 29.437500 0.812988 325.500 -3.265625 \n",
"6622 346.500 385.500 22.609375 0.708984 329.750 -0.894531 \n",
"6623 356.250 377.250 11.734375 0.637695 334.000 0.913086 \n",
"\n",
" MACDh_12_26_9 MACDs_12_26_9 High_mean_rolling_3 High_std_rolling_3 \\\n",
"1652 0.783691 -0.415283 169.75 2.707031 \n",
"1653 0.875000 -0.196411 167.75 2.394531 \n",
"1654 0.980469 0.048706 165.25 2.078125 \n",
"1655 0.729492 0.231079 164.75 1.688477 \n",
"3308 -2.289062 -1.142578 153.75 0.450684 \n",
"3309 -2.128906 -1.674805 153.50 0.503418 \n",
"3310 -1.812500 -2.128906 150.50 4.781250 \n",
"3311 -1.666992 -2.544922 149.50 4.195312 \n",
"4964 -2.703125 0.036133 294.00 2.636719 \n",
"4965 -2.798828 -0.663574 292.25 1.295898 \n",
"4966 -2.662109 -1.329102 292.75 2.044922 \n",
"4967 -2.212891 -1.881836 294.75 2.978516 \n",
"6620 -0.013664 -6.417969 295.75 10.296875 \n",
"6621 2.521484 -5.789062 286.50 8.632812 \n",
"6622 3.914062 -4.808594 277.25 9.109375 \n",
"6623 4.578125 -3.664062 273.00 5.472656 \n",
"\n",
" High_skew_rolling_3 High_max_rolling_3 High_min_rolling_3 \\\n",
"1652 -1.246094 171.875 166.750 \n",
"1653 1.633789 170.500 166.125 \n",
"1654 -1.601562 166.750 162.875 \n",
"1655 -1.035156 166.125 162.875 \n",
"3308 -0.265381 154.125 153.250 \n",
"3309 1.704102 154.125 153.250 \n",
"3310 -1.731445 153.250 145.000 \n",
"3311 -0.687500 153.250 145.000 \n",
"4964 0.350586 296.750 291.500 \n",
"4965 1.702148 293.750 291.500 \n",
"4966 1.719727 295.250 291.500 \n",
"4967 -0.492432 297.750 291.750 \n",
"6620 0.072327 306.250 285.500 \n",
"6621 0.498047 295.500 278.500 \n",
"6622 -0.613281 285.500 267.500 \n",
"6623 -0.111389 278.500 267.500 \n",
"\n",
" High_median_rolling_3 Low_mean_rolling_3 Low_std_rolling_3 \\\n",
"1652 170.500 165.625 3.201172 \n",
"1653 166.750 162.750 3.253906 \n",
"1654 166.125 158.000 5.304688 \n",
"1655 165.125 157.500 4.832031 \n",
"3308 153.750 150.750 0.364502 \n",
"3309 153.250 149.875 1.656250 \n",
"3310 153.250 146.000 5.566406 \n",
"3311 150.125 144.250 4.136719 \n",
"4964 293.750 287.000 2.802734 \n",
"4965 291.750 283.750 3.193359 \n",
"4966 291.750 278.750 6.601562 \n",
"4967 295.250 281.000 10.101562 \n",
"6620 295.500 279.250 12.164062 \n",
"6621 285.500 266.500 12.843750 \n",
"6622 278.500 251.250 16.953125 \n",
"6623 273.250 249.250 14.226562 \n",
"\n",
" Low_skew_rolling_3 Low_max_rolling_3 Low_min_rolling_3 \\\n",
"1652 -0.797363 168.500 162.125 \n",
"1653 0.734375 166.250 159.750 \n",
"1654 -1.341797 162.125 152.000 \n",
"1655 -1.627930 160.875 152.000 \n",
"3308 0.795410 151.125 150.375 \n",
"3309 -1.371094 151.125 148.000 \n",
"3310 -1.365234 150.375 139.750 \n",
"3311 -0.729492 148.000 139.750 \n",
"4964 0.955566 290.000 284.500 \n",
"4965 -1.127930 286.250 280.000 \n",
"4966 -0.907715 284.500 271.500 \n",
"4967 0.436768 291.750 271.500 \n",
"6620 -0.000824 291.250 267.000 \n",
"6621 -0.156616 279.250 253.500 \n",
"6622 -0.580078 267.000 233.375 \n",
"6623 -1.236328 260.750 233.375 \n",
"\n",
" Low_median_rolling_3 High_mean_rolling_4 High_std_rolling_4 \\\n",
"1652 166.250 170.625 2.859375 \n",
"1653 162.125 168.875 2.837891 \n",
"1654 159.750 166.500 3.150391 \n",
"1655 159.750 165.250 1.698242 \n",
"3308 150.625 154.250 1.253906 \n",
"3309 150.375 153.625 0.419434 \n",
"3310 148.000 151.375 4.304688 \n",
"3311 144.875 150.375 3.908203 \n",
"4964 286.250 295.750 4.027344 \n",
"4965 284.500 293.500 2.457031 \n",
"4966 280.000 293.000 1.751953 \n",
"4967 280.000 294.000 2.935547 \n",
"6620 279.250 299.000 10.632812 \n",
"6621 267.000 291.500 12.085938 \n",
"6622 253.500 281.750 11.851562 \n",
"6623 253.500 276.250 7.699219 \n",
"\n",
" High_skew_rolling_4 High_max_rolling_4 High_min_rolling_4 \\\n",
"1652 -1.096680 173.375 166.750 \n",
"1653 0.166504 171.875 166.125 \n",
"1654 0.258545 170.500 162.875 \n",
"1655 -1.208984 166.750 162.875 \n",
"3308 1.495117 156.125 153.250 \n",
"3309 0.740723 154.125 153.250 \n",
"3310 -1.944336 154.125 145.000 \n",
"3311 -1.263672 153.250 145.000 \n",
"4964 0.525879 300.750 291.500 \n",
"4965 1.079102 296.750 291.500 \n",
"4966 0.447021 295.250 291.500 \n",
"4967 0.573242 297.750 291.500 \n",
"6620 -0.660156 308.750 285.500 \n",
"6621 0.322021 306.250 278.500 \n",
"6622 -0.099304 295.500 267.500 \n",
"6623 0.240845 285.500 267.500 \n",
"\n",
" High_median_rolling_4 Low_mean_rolling_4 Low_std_rolling_4 \\\n",
"1652 171.250 166.750 3.431641 \n",
"1653 168.625 164.125 3.923828 \n",
"1654 166.375 160.000 5.972656 \n",
"1655 165.625 158.750 4.566406 \n",
"3308 153.875 151.500 1.531250 \n",
"3309 153.500 150.000 1.415039 \n",
"3310 153.250 147.375 5.207031 \n",
"3311 151.625 145.750 4.582031 \n",
"4964 295.250 288.500 4.074219 \n",
"4965 292.750 285.250 4.113281 \n",
"4966 292.750 280.500 6.597656 \n",
"4967 293.500 282.000 8.421875 \n",
"6620 301.000 284.500 14.531250 \n",
"6621 290.500 272.750 16.234375 \n",
"6622 282.000 258.250 19.656250 \n",
"6623 275.750 253.625 14.640625 \n",
"\n",
" Low_skew_rolling_4 Low_max_rolling_4 Low_min_rolling_4 \\\n",
"1652 -0.871094 170.000 162.125 \n",
"1653 -0.029663 168.500 159.750 \n",
"1654 -0.851562 166.250 152.000 \n",
"1655 -1.726562 162.125 152.000 \n",
"3308 1.781250 153.750 150.375 \n",
"3309 -1.732422 151.125 148.000 \n",
"3310 -1.625000 151.125 139.750 \n",
"3311 -0.724609 150.375 139.750 \n",
"4964 0.488037 293.750 284.500 \n",
"4965 -0.241577 290.000 280.000 \n",
"4966 -1.175781 286.250 271.500 \n",
"4967 -0.230957 291.750 271.500 \n",
"6620 -0.246704 300.500 267.000 \n",
"6621 -0.101318 291.250 253.500 \n",
"6622 -0.506836 279.250 233.375 \n",
"6623 -1.203125 267.000 233.375 \n",
"\n",
" Low_median_rolling_4 High_mean_rolling_6 High_std_rolling_6 \\\n",
"1652 167.375 170.875 2.480469 \n",
"1653 164.125 170.250 3.134766 \n",
"1654 161.000 168.625 3.998047 \n",
"1655 160.250 167.250 3.404297 \n",
"3308 150.875 154.500 1.233398 \n",
"3309 150.500 154.375 1.291016 \n",
"3310 149.250 152.625 3.865234 \n",
"3311 146.500 151.625 3.533203 \n",
"4964 288.250 296.750 3.710938 \n",
"4965 285.500 296.000 4.250000 \n",
"4966 282.250 295.000 3.517578 \n",
"4967 282.250 294.500 2.550781 \n",
"6620 285.250 300.500 8.937500 \n",
"6621 273.000 297.000 12.765625 \n",
"6622 260.250 290.250 16.156250 \n",
"6623 257.250 284.500 14.484375 \n",
"\n",
" High_skew_rolling_6 High_max_rolling_6 High_min_rolling_6 \\\n",
"1652 -0.920410 173.375 166.750 \n",
"1653 -0.605469 173.375 166.125 \n",
"1654 -0.267334 173.375 162.875 \n",
"1655 0.360352 171.875 162.875 \n",
"3308 0.746582 156.125 153.250 \n",
"3309 0.717773 156.125 153.250 \n",
"3310 -2.017578 156.125 145.000 \n",
"3311 -1.730469 154.125 145.000 \n",
"4964 -0.197632 300.750 291.500 \n",
"4965 0.265625 300.750 291.500 \n",
"4966 0.905762 300.750 291.500 \n",
"4967 0.000213 297.750 291.500 \n",
"6620 -1.011719 308.750 285.500 \n",
"6621 -0.631348 308.750 278.500 \n",
"6622 -0.238037 308.750 267.500 \n",
"6623 0.517090 306.250 267.500 \n",
"\n",
" High_median_rolling_6 Low_mean_rolling_6 Low_std_rolling_6 \\\n",
"1652 171.250 167.250 3.031250 \n",
"1653 171.250 166.125 4.343750 \n",
"1654 168.625 163.125 6.664062 \n",
"1655 166.375 161.625 5.738281 \n",
"3308 153.875 151.625 1.657227 \n",
"3309 153.875 151.250 2.224609 \n",
"3310 153.500 149.000 4.855469 \n",
"3311 153.250 147.500 4.433594 \n",
"4964 296.750 290.500 4.628906 \n",
"4965 295.250 288.500 6.210938 \n",
"4966 294.500 284.250 7.816406 \n",
"4967 294.500 284.000 7.363281 \n",
"6620 303.000 286.750 12.500000 \n",
"6621 301.000 281.500 18.531250 \n",
"6622 290.500 270.750 24.843750 \n",
"6623 282.000 264.250 20.250000 \n",
"\n",
" Low_skew_rolling_6 Low_max_rolling_6 Low_min_rolling_6 \\\n",
"1652 -0.940430 170.250 162.125 \n",
"1653 -0.671387 170.250 159.750 \n",
"1654 -0.899414 170.000 152.000 \n",
"1655 -0.724121 168.500 152.000 \n",
"3308 0.851562 153.875 150.375 \n",
"3309 -0.174316 153.875 148.000 \n",
"3310 -1.687500 153.750 139.750 \n",
"3311 -1.263672 151.125 139.750 \n",
"4964 0.083923 297.000 284.500 \n",
"4965 0.043518 297.000 280.000 \n",
"4966 -0.747559 293.750 271.500 \n",
"4967 -1.005859 291.750 271.500 \n",
"6620 -0.613770 300.500 267.000 \n",
"6621 -0.621094 300.500 253.500 \n",
"6622 -0.443359 300.500 233.375 \n",
"6623 -0.262939 291.250 233.375 \n",
"\n",
" Low_median_rolling_6 High_mean_rolling_8 High_std_rolling_8 \\\n",
"1652 167.500 171.750 2.710938 \n",
"1653 167.375 170.500 2.853516 \n",
"1654 164.125 169.250 3.710938 \n",
"1655 161.500 168.750 3.980469 \n",
"3308 150.875 155.500 2.193359 \n",
"3309 150.875 154.750 1.772461 \n",
"3310 150.500 153.125 3.478516 \n",
"3311 149.250 152.750 3.623047 \n",
"4964 290.750 299.250 5.714844 \n",
"4965 288.250 297.000 4.636719 \n",
"4966 285.500 296.000 3.617188 \n",
"4967 285.500 296.000 3.658203 \n",
"6620 288.000 303.000 9.062500 \n",
"6621 285.250 298.500 11.179688 \n",
"6622 273.000 293.750 15.132812 \n",
"6623 264.000 290.250 16.484375 \n",
"\n",
" High_skew_rolling_8 High_max_rolling_8 High_min_rolling_8 \\\n",
"1652 -0.700684 175.500 166.750 \n",
"1653 -0.704590 173.375 166.125 \n",
"1654 -0.629883 173.375 162.875 \n",
"1655 -0.159424 173.375 162.875 \n",
"3308 0.677246 159.000 153.250 \n",
"3309 1.135742 158.250 153.250 \n",
"3310 -2.226562 156.125 145.000 \n",
"3311 -1.587891 156.125 145.000 \n",
"4964 0.458496 309.000 291.500 \n",
"4965 0.234619 304.250 291.500 \n",
"4966 0.265381 300.750 291.500 \n",
"4967 0.154297 300.750 291.500 \n",
"6620 -0.945312 314.500 285.500 \n",
"6621 -1.004883 308.750 278.500 \n",
"6622 -0.749512 308.750 267.500 \n",
"6623 -0.141602 308.750 267.500 \n",
"\n",
" High_median_rolling_8 Low_mean_rolling_8 Low_std_rolling_8 \\\n",
"1652 172.375 167.875 2.966797 \n",
"1653 171.250 166.375 3.732422 \n",
"1654 170.000 164.375 6.222656 \n",
"1655 168.625 163.750 6.269531 \n",
"3308 155.000 152.250 1.888672 \n",
"3309 153.875 151.375 2.015625 \n",
"3310 153.750 149.750 4.453125 \n",
"3311 153.500 149.000 4.753906 \n",
"4964 298.750 292.250 5.363281 \n",
"4965 296.750 289.750 5.648438 \n",
"4966 296.000 286.750 8.164062 \n",
"4967 296.000 286.750 8.187500 \n",
"6620 305.750 287.750 11.523438 \n",
"6621 302.500 282.250 15.703125 \n",
"6622 297.500 276.000 23.281250 \n",
"6623 290.500 273.000 23.546875 \n",
"\n",
" Low_skew_rolling_8 Low_max_rolling_8 Low_min_rolling_8 \\\n",
"1652 -0.928223 171.500 162.125 \n",
"1653 -0.958496 170.250 159.750 \n",
"1654 -1.247070 170.250 152.000 \n",
"1655 -0.805664 170.250 152.000 \n",
"3308 0.347900 155.250 150.375 \n",
"3309 -0.234863 153.875 148.000 \n",
"3310 -1.840820 153.875 139.750 \n",
"3311 -1.140625 153.875 139.750 \n",
"4964 0.064087 300.750 284.500 \n",
"4965 -0.504395 297.000 280.000 \n",
"4966 -0.831055 297.000 271.500 \n",
"4967 -0.834961 297.000 271.500 \n",
"6620 -0.669922 300.500 267.000 \n",
"6621 -0.800781 300.500 253.500 \n",
"6622 -0.894531 300.500 233.375 \n",
"6623 -0.420410 300.500 233.375 \n",
"\n",
" Low_median_rolling_8 log_return log_volume \\\n",
"1652 168.250 -0.015625 0.096558 \n",
"1653 167.250 -0.027344 -0.012733 \n",
"1654 166.375 0.015625 0.449951 \n",
"1655 164.125 0.011719 -0.428223 \n",
"3308 152.000 0.000000 -0.034668 \n",
"3309 150.875 -0.023438 0.040253 \n",
"3310 150.500 -0.027344 0.776855 \n",
"3311 150.500 0.023438 -0.334229 \n",
"4964 292.500 0.000000 0.197266 \n",
"4965 290.750 -0.027344 -0.098755 \n",
"4966 288.250 0.050781 0.410156 \n",
"4967 288.250 0.007812 -0.560059 \n",
"6620 288.000 -0.042969 0.195435 \n",
"6621 284.000 -0.074219 0.134277 \n",
"6622 281.750 0.046875 0.351074 \n",
"6623 273.000 0.011719 -0.576172 \n",
"\n",
" log_return__co_embed2_dist_tau_d_expfit_meandiff__w=30_catch \\\n",
"1652 0.112061 \n",
"1653 0.130859 \n",
"1654 0.115295 \n",
"1655 0.095398 \n",
"3308 0.070435 \n",
"3309 0.069885 \n",
"3310 0.129761 \n",
"3311 0.135376 \n",
"4964 0.177734 \n",
"4965 0.082703 \n",
"4966 0.103821 \n",
"4967 0.148315 \n",
"6620 0.098145 \n",
"6621 0.097839 \n",
"6622 0.094177 \n",
"6623 0.089844 \n",
"\n",
" log_return__co_firstmin_ac__w=30_catch \\\n",
"1652 3.0 \n",
"1653 4.0 \n",
"1654 4.0 \n",
"1655 4.0 \n",
"3308 2.0 \n",
"3309 2.0 \n",
"3310 2.0 \n",
"3311 2.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 1.0 \n",
"4967 1.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_return__co_histogramami_even_2_5__w=30_catch \\\n",
"1652 0.116821 \n",
"1653 0.107971 \n",
"1654 0.111206 \n",
"1655 0.095520 \n",
"3308 0.293457 \n",
"3309 0.233643 \n",
"3310 0.196411 \n",
"3311 0.219849 \n",
"4964 0.343018 \n",
"4965 0.358643 \n",
"4966 0.316406 \n",
"4967 0.255859 \n",
"6620 0.235352 \n",
"6621 0.245972 \n",
"6622 0.225220 \n",
"6623 0.230713 \n",
"\n",
" log_return__co_f1ecac__w=30_catch \\\n",
"1652 0.863281 \n",
"1653 0.871094 \n",
"1654 0.893555 \n",
"1655 0.834473 \n",
"3308 0.981445 \n",
"3309 0.983398 \n",
"3310 0.959961 \n",
"3311 0.984863 \n",
"4964 0.500000 \n",
"4965 0.499023 \n",
"4966 0.500977 \n",
"4967 0.486816 \n",
"6620 0.559570 \n",
"6621 0.575684 \n",
"6622 0.594238 \n",
"6623 0.556152 \n",
"\n",
" log_return__co_trev_1_num__w=30_catch \\\n",
"1652 1.189453 \n",
"1653 1.137695 \n",
"1654 1.022461 \n",
"1655 1.411133 \n",
"3308 -1.008789 \n",
"3309 -1.033203 \n",
"3310 -1.028320 \n",
"3311 -0.951172 \n",
"4964 0.134155 \n",
"4965 0.137451 \n",
"4966 0.058441 \n",
"4967 1.397461 \n",
"6620 -0.480225 \n",
"6621 -0.610840 \n",
"6622 -0.575195 \n",
"6623 0.132080 \n",
"\n",
" log_return__dn_histogrammode_10__w=30_catch \\\n",
"1652 -0.009048 \n",
"1653 0.024734 \n",
"1654 -0.990723 \n",
"1655 -0.990723 \n",
"3308 0.337891 \n",
"3309 0.362061 \n",
"3310 0.154663 \n",
"3311 -0.033569 \n",
"4964 0.301270 \n",
"4965 0.303467 \n",
"4966 -1.076172 \n",
"4967 0.035828 \n",
"6620 -0.348877 \n",
"6621 -0.342773 \n",
"6622 -0.255615 \n",
"6623 -0.279541 \n",
"\n",
" log_return__dn_histogrammode_5__w=30_catch \\\n",
"1652 0.237549 \n",
"1653 0.267822 \n",
"1654 -0.748535 \n",
"1655 -0.748535 \n",
"3308 0.094055 \n",
"3309 0.116333 \n",
"3310 0.154663 \n",
"3311 0.202271 \n",
"4964 0.482422 \n",
"4965 0.484863 \n",
"4966 0.518555 \n",
"4967 0.243896 \n",
"6620 -0.081726 \n",
"6621 -0.076538 \n",
"6622 0.004406 \n",
"6623 -0.026581 \n",
"\n",
" log_return__dn_outlierinclude_n_001_mdrmd__w=30_catch \\\n",
"1652 -0.033325 \n",
"1653 0.000000 \n",
"1654 0.466553 \n",
"1655 0.399902 \n",
"3308 -0.533203 \n",
"3309 -0.600098 \n",
"3310 -0.683105 \n",
"3311 -0.733398 \n",
"4964 0.266602 \n",
"4965 0.199951 \n",
"4966 0.199951 \n",
"4967 0.133301 \n",
"6620 -0.066650 \n",
"6621 -0.133301 \n",
"6622 0.166626 \n",
"6623 0.099976 \n",
"\n",
" log_return__dn_outlierinclude_p_001_mdrmd__w=30_catch \\\n",
"1652 0.066650 \n",
"1653 0.000000 \n",
"1654 -0.066650 \n",
"1655 0.133301 \n",
"3308 0.133301 \n",
"3309 0.166626 \n",
"3310 0.099976 \n",
"3311 0.033325 \n",
"4964 0.000000 \n",
"4965 -0.033325 \n",
"4966 -0.066650 \n",
"4967 -0.066650 \n",
"6620 0.066650 \n",
"6621 0.000000 \n",
"6622 0.066650 \n",
"6623 0.133301 \n",
"\n",
" log_return__fc_localsimple_mean1_tauresrat__w=30_catch \\\n",
"1652 0.500000 \n",
"1653 0.500000 \n",
"1654 0.500000 \n",
"1655 0.500000 \n",
"3308 0.199951 \n",
"3309 0.199951 \n",
"3310 0.500000 \n",
"3311 0.500000 \n",
"4964 1.000000 \n",
"4965 1.000000 \n",
"4966 1.000000 \n",
"4967 1.000000 \n",
"6620 1.000000 \n",
"6621 1.000000 \n",
"6622 1.000000 \n",
"6623 1.000000 \n",
"\n",
" log_return__fc_localsimple_mean3_stderr__w=30_catch \\\n",
"1652 1.224609 \n",
"1653 1.208984 \n",
"1654 1.152344 \n",
"1655 1.205078 \n",
"3308 1.151367 \n",
"3309 1.161133 \n",
"3310 1.153320 \n",
"3311 0.924805 \n",
"4964 1.262695 \n",
"4965 1.266602 \n",
"4966 1.156250 \n",
"4967 1.146484 \n",
"6620 1.287109 \n",
"6621 1.268555 \n",
"6622 1.175781 \n",
"6623 1.210938 \n",
"\n",
" log_return__in_automutualinfostats_40_gaussian_fmmi__w=30_catch \\\n",
"1652 1.0 \n",
"1653 1.0 \n",
"1654 1.0 \n",
"1655 1.0 \n",
"3308 1.0 \n",
"3309 1.0 \n",
"3310 1.0 \n",
"3311 1.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 2.0 \n",
"4967 1.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_return__md_hrv_classic_pnn40__w=30_catch \\\n",
"1652 1.000000 \n",
"1653 1.000000 \n",
"1654 1.000000 \n",
"1655 1.000000 \n",
"3308 0.931152 \n",
"3309 0.931152 \n",
"3310 0.965332 \n",
"3311 0.965332 \n",
"4964 0.965332 \n",
"4965 1.000000 \n",
"4966 1.000000 \n",
"4967 1.000000 \n",
"6620 1.000000 \n",
"6621 1.000000 \n",
"6622 1.000000 \n",
"6623 1.000000 \n",
"\n",
" log_return__pd_periodicitywang_th0_01__w=30_catch \\\n",
"1652 4.0 \n",
"1653 4.0 \n",
"1654 4.0 \n",
"1655 6.0 \n",
"3308 3.0 \n",
"3309 3.0 \n",
"3310 3.0 \n",
"3311 3.0 \n",
"4964 4.0 \n",
"4965 4.0 \n",
"4966 4.0 \n",
"4967 4.0 \n",
"6620 3.0 \n",
"6621 3.0 \n",
"6622 3.0 \n",
"6623 3.0 \n",
"\n",
" log_return__sb_binarystats_diff_longstretch0__w=30_catch \\\n",
"1652 3.0 \n",
"1653 3.0 \n",
"1654 3.0 \n",
"1655 3.0 \n",
"3308 4.0 \n",
"3309 4.0 \n",
"3310 4.0 \n",
"3311 4.0 \n",
"4964 3.0 \n",
"4965 3.0 \n",
"4966 3.0 \n",
"4967 3.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_return__sb_binarystats_mean_longstretch1__w=30_catch \\\n",
"1652 4.0 \n",
"1653 5.0 \n",
"1654 5.0 \n",
"1655 5.0 \n",
"3308 5.0 \n",
"3309 5.0 \n",
"3310 5.0 \n",
"3311 6.0 \n",
"4964 5.0 \n",
"4965 5.0 \n",
"4966 5.0 \n",
"4967 5.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_return__sb_motifthree_quantile_hh__w=30_catch \\\n",
"1652 2.154297 \n",
"1653 2.132812 \n",
"1654 2.166016 \n",
"1655 2.177734 \n",
"3308 2.091797 \n",
"3309 2.062500 \n",
"3310 2.062500 \n",
"3311 2.091797 \n",
"4964 2.156250 \n",
"4965 2.156250 \n",
"4966 2.126953 \n",
"4967 2.107422 \n",
"6620 2.080078 \n",
"6621 2.091797 \n",
"6622 2.126953 \n",
"6623 2.080078 \n",
"\n",
" log_return__sb_transitionmatrix_3ac_sumdiagcov__w=30_catch \\\n",
"1652 0.010201 \n",
"1653 0.015305 \n",
"1654 0.020401 \n",
"1655 0.010201 \n",
"3308 0.040009 \n",
"3309 0.040009 \n",
"3310 0.020401 \n",
"3311 0.015305 \n",
"4964 0.004360 \n",
"4965 0.004360 \n",
"4966 0.006737 \n",
"4967 0.009117 \n",
"6620 0.012680 \n",
"6621 0.011497 \n",
"6622 0.006737 \n",
"6623 0.012680 \n",
"\n",
" log_return__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=30_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=30_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sp_summaries_welch_rect_area_5_1__w=30_catch \\\n",
"1652 0.190674 \n",
"1653 0.176025 \n",
"1654 0.166626 \n",
"1655 0.176514 \n",
"3308 0.284424 \n",
"3309 0.287598 \n",
"3310 0.280029 \n",
"3311 0.299072 \n",
"4964 0.067871 \n",
"4965 0.068054 \n",
"4966 0.071899 \n",
"4967 0.057617 \n",
"6620 0.049835 \n",
"6621 0.054047 \n",
"6622 0.059448 \n",
"6623 0.047638 \n",
"\n",
" log_return__sp_summaries_welch_rect_centroid__w=30_catch \\\n",
"1652 1.177734 \n",
"1653 0.981934 \n",
"1654 0.981934 \n",
"1655 0.981934 \n",
"3308 0.981934 \n",
"3309 0.981934 \n",
"3310 0.981934 \n",
"3311 0.981934 \n",
"4964 2.355469 \n",
"4965 2.355469 \n",
"4966 2.355469 \n",
"4967 2.355469 \n",
"6620 1.767578 \n",
"6621 1.767578 \n",
"6622 1.767578 \n",
"6623 1.767578 \n",
"\n",
" log_volume__co_embed2_dist_tau_d_expfit_meandiff__w=30_catch \\\n",
"1652 0.092834 \n",
"1653 0.091125 \n",
"1654 0.093323 \n",
"1655 0.076111 \n",
"3308 0.094604 \n",
"3309 0.123474 \n",
"3310 0.099670 \n",
"3311 0.092590 \n",
"4964 0.133545 \n",
"4965 0.119934 \n",
"4966 0.119202 \n",
"4967 0.119263 \n",
"6620 0.094482 \n",
"6621 0.077637 \n",
"6622 0.075928 \n",
"6623 0.092163 \n",
"\n",
" log_volume__co_firstmin_ac__w=30_catch \\\n",
"1652 2.0 \n",
"1653 2.0 \n",
"1654 2.0 \n",
"1655 2.0 \n",
"3308 1.0 \n",
"3309 1.0 \n",
"3310 1.0 \n",
"3311 1.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 1.0 \n",
"4967 1.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_volume__co_histogramami_even_2_5__w=30_catch \\\n",
"1652 0.381348 \n",
"1653 0.447021 \n",
"1654 0.447021 \n",
"1655 0.327881 \n",
"3308 0.262695 \n",
"3309 0.236328 \n",
"3310 0.217773 \n",
"3311 0.233398 \n",
"4964 0.216187 \n",
"4965 0.167725 \n",
"4966 0.193970 \n",
"4967 0.206787 \n",
"6620 0.364502 \n",
"6621 0.354736 \n",
"6622 0.350098 \n",
"6623 0.316650 \n",
"\n",
" log_volume__co_f1ecac__w=30_catch \\\n",
"1652 0.617676 \n",
"1653 0.639160 \n",
"1654 0.681641 \n",
"1655 0.668457 \n",
"3308 0.486328 \n",
"3309 0.486328 \n",
"3310 0.485352 \n",
"3311 0.503906 \n",
"4964 0.500977 \n",
"4965 0.518066 \n",
"4966 0.541992 \n",
"4967 0.546875 \n",
"6620 0.613281 \n",
"6621 0.633789 \n",
"6622 0.655762 \n",
"6623 0.710938 \n",
"\n",
" log_volume__co_trev_1_num__w=30_catch \\\n",
"1652 -3.189453 \n",
"1653 -3.335938 \n",
"1654 -2.818359 \n",
"1655 -2.291016 \n",
"3308 -0.307373 \n",
"3309 -0.307129 \n",
"3310 -0.307129 \n",
"3311 -0.016632 \n",
"4964 -0.451416 \n",
"4965 -0.740723 \n",
"4966 0.089844 \n",
"4967 -0.043274 \n",
"6620 -0.955078 \n",
"6621 -0.934082 \n",
"6622 -0.739258 \n",
"6623 -1.185547 \n",
"\n",
" log_volume__dn_histogrammode_10__w=30_catch \\\n",
"1652 -0.313232 \n",
"1653 -0.347656 \n",
"1654 -0.317139 \n",
"1655 -0.301514 \n",
"3308 0.137939 \n",
"3309 0.140259 \n",
"3310 0.129883 \n",
"3311 0.047058 \n",
"4964 -0.677734 \n",
"4965 -0.520508 \n",
"4966 -0.260254 \n",
"4967 -0.377930 \n",
"6620 0.065491 \n",
"6621 0.027206 \n",
"6622 0.617188 \n",
"6623 0.521973 \n",
"\n",
" log_volume__dn_histogrammode_5__w=30_catch \\\n",
"1652 -0.107544 \n",
"1653 -0.141846 \n",
"1654 -0.107483 \n",
"1655 -0.083557 \n",
"3308 0.397949 \n",
"3309 0.400146 \n",
"3310 0.389893 \n",
"3311 0.289307 \n",
"4964 -0.466797 \n",
"4965 -0.098267 \n",
"4966 -0.043884 \n",
"4967 -0.160645 \n",
"6620 -0.338135 \n",
"6621 0.027206 \n",
"6622 0.020462 \n",
"6623 0.322754 \n",
"\n",
" log_volume__dn_outlierinclude_n_001_mdrmd__w=30_catch \\\n",
"1652 0.066650 \n",
"1653 0.000000 \n",
"1654 -0.066650 \n",
"1655 -0.099976 \n",
"3308 -0.033325 \n",
"3309 -0.099976 \n",
"3310 -0.133301 \n",
"3311 -0.099976 \n",
"4964 -0.066650 \n",
"4965 -0.133301 \n",
"4966 -0.199951 \n",
"4967 0.000000 \n",
"6620 0.066650 \n",
"6621 0.000000 \n",
"6622 -0.066650 \n",
"6623 -0.066650 \n",
"\n",
" log_volume__dn_outlierinclude_p_001_mdrmd__w=30_catch \\\n",
"1652 -0.133301 \n",
"1653 -0.199951 \n",
"1654 -0.166626 \n",
"1655 0.000000 \n",
"3308 0.233276 \n",
"3309 0.166626 \n",
"3310 0.183350 \n",
"3311 0.199951 \n",
"4964 -0.266602 \n",
"4965 -0.333252 \n",
"4966 -0.333252 \n",
"4967 -0.133301 \n",
"6620 -0.166626 \n",
"6621 -0.199951 \n",
"6622 -0.233276 \n",
"6623 -0.266602 \n",
"\n",
" log_volume__fc_localsimple_mean1_tauresrat__w=30_catch \\\n",
"1652 1.0 \n",
"1653 0.5 \n",
"1654 0.5 \n",
"1655 0.5 \n",
"3308 1.0 \n",
"3309 1.0 \n",
"3310 1.0 \n",
"3311 1.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 1.0 \n",
"4967 1.0 \n",
"6620 1.0 \n",
"6621 0.5 \n",
"6622 0.5 \n",
"6623 0.5 \n",
"\n",
" log_volume__fc_localsimple_mean3_stderr__w=30_catch \\\n",
"1652 1.254883 \n",
"1653 1.255859 \n",
"1654 1.279297 \n",
"1655 1.283203 \n",
"3308 1.345703 \n",
"3309 1.344727 \n",
"3310 1.344727 \n",
"3311 1.196289 \n",
"4964 1.119141 \n",
"4965 1.104492 \n",
"4966 1.125000 \n",
"4967 1.163086 \n",
"6620 1.259766 \n",
"6621 1.219727 \n",
"6622 1.210938 \n",
"6623 1.189453 \n",
"\n",
" log_volume__in_automutualinfostats_40_gaussian_fmmi__w=30_catch \\\n",
"1652 2.0 \n",
"1653 2.0 \n",
"1654 2.0 \n",
"1655 2.0 \n",
"3308 1.0 \n",
"3309 1.0 \n",
"3310 1.0 \n",
"3311 1.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 2.0 \n",
"4967 2.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_volume__md_hrv_classic_pnn40__w=30_catch \\\n",
"1652 1.000000 \n",
"1653 1.000000 \n",
"1654 1.000000 \n",
"1655 1.000000 \n",
"3308 0.896484 \n",
"3309 0.896484 \n",
"3310 0.931152 \n",
"3311 0.931152 \n",
"4964 0.965332 \n",
"4965 0.965332 \n",
"4966 0.965332 \n",
"4967 0.965332 \n",
"6620 0.896484 \n",
"6621 0.896484 \n",
"6622 0.896484 \n",
"6623 0.896484 \n",
"\n",
" log_volume__pd_periodicitywang_th0_01__w=30_catch \\\n",
"1652 3.0 \n",
"1653 3.0 \n",
"1654 3.0 \n",
"1655 3.0 \n",
"3308 3.0 \n",
"3309 3.0 \n",
"3310 3.0 \n",
"3311 3.0 \n",
"4964 5.0 \n",
"4965 5.0 \n",
"4966 5.0 \n",
"4967 4.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 5.0 \n",
"6623 5.0 \n",
"\n",
" log_volume__sb_binarystats_diff_longstretch0__w=30_catch \\\n",
"1652 4.0 \n",
"1653 4.0 \n",
"1654 4.0 \n",
"1655 4.0 \n",
"3308 4.0 \n",
"3309 4.0 \n",
"3310 4.0 \n",
"3311 4.0 \n",
"4964 3.0 \n",
"4965 3.0 \n",
"4966 3.0 \n",
"4967 3.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_volume__sb_binarystats_mean_longstretch1__w=30_catch \\\n",
"1652 3.0 \n",
"1653 3.0 \n",
"1654 3.0 \n",
"1655 4.0 \n",
"3308 4.0 \n",
"3309 4.0 \n",
"3310 4.0 \n",
"3311 3.0 \n",
"4964 3.0 \n",
"4965 3.0 \n",
"4966 4.0 \n",
"4967 5.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 4.0 \n",
"6623 4.0 \n",
"\n",
" log_volume__sb_motifthree_quantile_hh__w=30_catch \\\n",
"1652 2.156250 \n",
"1653 2.166016 \n",
"1654 2.166016 \n",
"1655 2.189453 \n",
"3308 2.156250 \n",
"3309 2.156250 \n",
"3310 2.156250 \n",
"3311 2.144531 \n",
"4964 2.042969 \n",
"4965 2.062500 \n",
"4966 2.119141 \n",
"4967 2.144531 \n",
"6620 2.166016 \n",
"6621 2.154297 \n",
"6622 2.154297 \n",
"6623 2.126953 \n",
"\n",
" log_volume__sb_transitionmatrix_3ac_sumdiagcov__w=30_catch \\\n",
"1652 0.004360 \n",
"1653 0.045929 \n",
"1654 0.015305 \n",
"1655 0.025513 \n",
"3308 0.004360 \n",
"3309 0.004360 \n",
"3310 0.004360 \n",
"3311 0.005550 \n",
"4964 0.017441 \n",
"4965 0.013870 \n",
"4966 0.007927 \n",
"4967 0.005550 \n",
"6620 0.003170 \n",
"6621 0.045929 \n",
"6622 0.035706 \n",
"6623 0.035706 \n",
"\n",
" log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=30_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=30_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sp_summaries_welch_rect_area_5_1__w=30_catch \\\n",
"1652 0.054443 \n",
"1653 0.050598 \n",
"1654 0.059052 \n",
"1655 0.082153 \n",
"3308 0.032135 \n",
"3309 0.032562 \n",
"3310 0.035736 \n",
"3311 0.078064 \n",
"4964 0.067932 \n",
"4965 0.062683 \n",
"4966 0.068359 \n",
"4967 0.097412 \n",
"6620 0.058044 \n",
"6621 0.059479 \n",
"6622 0.063110 \n",
"6623 0.096191 \n",
"\n",
" log_volume__sp_summaries_welch_rect_centroid__w=30_catch \\\n",
"1652 1.374023 \n",
"1653 1.374023 \n",
"1654 1.374023 \n",
"1655 1.374023 \n",
"3308 1.963867 \n",
"3309 1.963867 \n",
"3310 1.963867 \n",
"3311 1.767578 \n",
"4964 2.160156 \n",
"4965 2.160156 \n",
"4966 2.160156 \n",
"4967 2.160156 \n",
"6620 1.374023 \n",
"6621 1.374023 \n",
"6622 1.374023 \n",
"6623 1.374023 \n",
"\n",
" log_return__co_embed2_dist_tau_d_expfit_meandiff__w=7_catch \\\n",
"1652 0.260986 \n",
"1653 0.243774 \n",
"1654 0.222046 \n",
"1655 0.295410 \n",
"3308 0.282959 \n",
"3309 0.281250 \n",
"3310 0.284180 \n",
"3311 0.238647 \n",
"4964 0.423828 \n",
"4965 0.267334 \n",
"4966 0.263184 \n",
"4967 0.318848 \n",
"6620 0.269531 \n",
"6621 0.259766 \n",
"6622 0.183350 \n",
"6623 0.308350 \n",
"\n",
" log_return__co_firstmin_ac__w=7_catch \\\n",
"1652 2.0 \n",
"1653 2.0 \n",
"1654 2.0 \n",
"1655 2.0 \n",
"3308 2.0 \n",
"3309 2.0 \n",
"3310 2.0 \n",
"3311 2.0 \n",
"4964 2.0 \n",
"4965 2.0 \n",
"4966 2.0 \n",
"4967 1.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 2.0 \n",
"\n",
" log_return__co_histogramami_even_2_5__w=7_catch \\\n",
"1652 0.777832 \n",
"1653 0.777832 \n",
"1654 0.672852 \n",
"1655 0.672852 \n",
"3308 1.054688 \n",
"3309 1.054688 \n",
"3310 0.777832 \n",
"3311 0.291016 \n",
"4964 1.054688 \n",
"4965 0.672852 \n",
"4966 0.395752 \n",
"4967 0.395752 \n",
"6620 1.609375 \n",
"6621 1.054688 \n",
"6622 0.777832 \n",
"6623 1.054688 \n",
"\n",
" log_return__co_f1ecac__w=7_catch log_return__co_trev_1_num__w=7_catch \\\n",
"1652 0.895996 -0.011047 \n",
"1653 0.773438 -0.040894 \n",
"1654 0.988770 -0.418457 \n",
"1655 0.624512 1.369141 \n",
"3308 0.510742 1.448242 \n",
"3309 0.519043 1.475586 \n",
"3310 0.509766 0.633301 \n",
"3311 0.691895 -0.146240 \n",
"4964 0.847168 -0.048431 \n",
"4965 0.679199 -0.039703 \n",
"4966 0.678711 -1.169922 \n",
"4967 0.519531 3.271484 \n",
"6620 0.843750 0.292725 \n",
"6621 0.794922 0.268311 \n",
"6622 1.108398 -0.517090 \n",
"6623 0.598145 2.082031 \n",
"\n",
" log_return__dn_histogrammode_10__w=7_catch \\\n",
"1652 -0.842285 \n",
"1653 -0.797363 \n",
"1654 -0.239258 \n",
"1655 -0.972168 \n",
"3308 0.000479 \n",
"3309 -0.026718 \n",
"3310 -1.191406 \n",
"3311 -0.082703 \n",
"4964 -0.919922 \n",
"4965 0.511719 \n",
"4966 -0.351807 \n",
"4967 -0.508301 \n",
"6620 -0.647949 \n",
"6621 -0.847656 \n",
"6622 0.008385 \n",
"6623 1.208984 \n",
"\n",
" log_return__dn_histogrammode_5__w=7_catch \\\n",
"1652 -0.702148 \n",
"1653 -0.657227 \n",
"1654 -0.822754 \n",
"1655 -0.842773 \n",
"3308 -0.021149 \n",
"3309 -0.048309 \n",
"3310 -0.234131 \n",
"3311 -0.212891 \n",
"4964 -0.786133 \n",
"4965 -0.127197 \n",
"4966 -0.110596 \n",
"4967 -0.217529 \n",
"6620 -0.511230 \n",
"6621 -0.715332 \n",
"6622 -0.421631 \n",
"6623 0.051147 \n",
"\n",
" log_return__dn_outlierinclude_n_001_mdrmd__w=7_catch \\\n",
"1652 -0.428467 \n",
"1653 0.428467 \n",
"1654 0.714355 \n",
"1655 0.428467 \n",
"3308 -0.142822 \n",
"3309 -0.428467 \n",
"3310 0.571289 \n",
"3311 0.714355 \n",
"4964 -0.428467 \n",
"4965 -0.142822 \n",
"4966 0.571289 \n",
"4967 0.285645 \n",
"6620 0.142822 \n",
"6621 0.428467 \n",
"6622 0.714355 \n",
"6623 0.357178 \n",
"\n",
" log_return__dn_outlierinclude_p_001_mdrmd__w=7_catch \\\n",
"1652 0.142822 \n",
"1653 -0.142822 \n",
"1654 -0.428467 \n",
"1655 0.142822 \n",
"3308 0.428467 \n",
"3309 0.285645 \n",
"3310 0.000000 \n",
"3311 -0.285645 \n",
"4964 0.142822 \n",
"4965 0.000000 \n",
"4966 -0.285645 \n",
"4967 0.142822 \n",
"6620 0.000000 \n",
"6621 -0.285645 \n",
"6622 -0.428467 \n",
"6623 0.142822 \n",
"\n",
" log_return__fc_localsimple_mean1_tauresrat__w=7_catch \\\n",
"1652 1.0 \n",
"1653 1.0 \n",
"1654 0.5 \n",
"1655 1.0 \n",
"3308 1.0 \n",
"3309 1.0 \n",
"3310 1.0 \n",
"3311 0.5 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 0.5 \n",
"4967 1.0 \n",
"6620 1.0 \n",
"6621 1.0 \n",
"6622 0.5 \n",
"6623 1.0 \n",
"\n",
" log_return__fc_localsimple_mean3_stderr__w=7_catch \\\n",
"1652 1.665039 \n",
"1653 0.736816 \n",
"1654 0.606934 \n",
"1655 1.140625 \n",
"3308 1.635742 \n",
"3309 1.232422 \n",
"3310 1.116211 \n",
"3311 0.857910 \n",
"4964 1.638672 \n",
"4965 1.258789 \n",
"4966 1.200195 \n",
"4967 1.233398 \n",
"6620 1.615234 \n",
"6621 0.793945 \n",
"6622 0.610840 \n",
"6623 1.220703 \n",
"\n",
" log_return__in_automutualinfostats_40_gaussian_fmmi__w=7_catch \\\n",
"1652 4.0 \n",
"1653 4.0 \n",
"1654 1.0 \n",
"1655 2.0 \n",
"3308 2.0 \n",
"3309 4.0 \n",
"3310 4.0 \n",
"3311 4.0 \n",
"4964 4.0 \n",
"4965 2.0 \n",
"4966 2.0 \n",
"4967 2.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 1.0 \n",
"6623 2.0 \n",
"\n",
" log_return__md_hrv_classic_pnn40__w=7_catch \\\n",
"1652 1.0 \n",
"1653 1.0 \n",
"1654 1.0 \n",
"1655 1.0 \n",
"3308 1.0 \n",
"3309 1.0 \n",
"3310 1.0 \n",
"3311 1.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 1.0 \n",
"4967 1.0 \n",
"6620 1.0 \n",
"6621 1.0 \n",
"6622 1.0 \n",
"6623 1.0 \n",
"\n",
" log_return__pd_periodicitywang_th0_01__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sb_binarystats_diff_longstretch0__w=7_catch \\\n",
"1652 3.0 \n",
"1653 3.0 \n",
"1654 3.0 \n",
"1655 3.0 \n",
"3308 3.0 \n",
"3309 3.0 \n",
"3310 3.0 \n",
"3311 3.0 \n",
"4964 3.0 \n",
"4965 3.0 \n",
"4966 3.0 \n",
"4967 2.0 \n",
"6620 3.0 \n",
"6621 3.0 \n",
"6622 3.0 \n",
"6623 3.0 \n",
"\n",
" log_return__sb_binarystats_mean_longstretch1__w=7_catch \\\n",
"1652 4.0 \n",
"1653 4.0 \n",
"1654 3.0 \n",
"1655 2.0 \n",
"3308 3.0 \n",
"3309 3.0 \n",
"3310 3.0 \n",
"3311 3.0 \n",
"4964 4.0 \n",
"4965 4.0 \n",
"4966 3.0 \n",
"4967 1.0 \n",
"6620 4.0 \n",
"6621 4.0 \n",
"6622 3.0 \n",
"6623 2.0 \n",
"\n",
" log_return__sb_motifthree_quantile_hh__w=7_catch \\\n",
"1652 1.560547 \n",
"1653 1.791992 \n",
"1654 1.560547 \n",
"1655 1.560547 \n",
"3308 1.560547 \n",
"3309 1.560547 \n",
"3310 1.330078 \n",
"3311 1.330078 \n",
"4964 1.560547 \n",
"4965 1.791992 \n",
"4966 1.560547 \n",
"4967 1.560547 \n",
"6620 1.560547 \n",
"6621 1.791992 \n",
"6622 1.560547 \n",
"6623 1.560547 \n",
"\n",
" log_return__sb_transitionmatrix_3ac_sumdiagcov__w=7_catch \\\n",
"1652 0.074097 \n",
"1653 0.111084 \n",
"1654 0.074097 \n",
"1655 0.046295 \n",
"3308 0.055542 \n",
"3309 0.046295 \n",
"3310 0.083313 \n",
"3311 0.074097 \n",
"4964 0.074097 \n",
"4965 0.111084 \n",
"4966 0.074097 \n",
"4967 0.046295 \n",
"6620 0.074097 \n",
"6621 0.111084 \n",
"6622 0.074097 \n",
"6623 0.046295 \n",
"\n",
" log_return__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sp_summaries_welch_rect_area_5_1__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_return__sp_summaries_welch_rect_centroid__w=7_catch \\\n",
"1652 1.570312 \n",
"1653 1.570312 \n",
"1654 0.785156 \n",
"1655 1.570312 \n",
"3308 1.570312 \n",
"3309 1.570312 \n",
"3310 1.570312 \n",
"3311 1.570312 \n",
"4964 1.570312 \n",
"4965 1.570312 \n",
"4966 1.570312 \n",
"4967 2.355469 \n",
"6620 1.570312 \n",
"6621 1.570312 \n",
"6622 0.785156 \n",
"6623 2.355469 \n",
"\n",
" log_volume__co_embed2_dist_tau_d_expfit_meandiff__w=7_catch \\\n",
"1652 0.183594 \n",
"1653 0.214355 \n",
"1654 0.219116 \n",
"1655 0.235718 \n",
"3308 0.180176 \n",
"3309 0.255859 \n",
"3310 0.283447 \n",
"3311 0.210205 \n",
"4964 0.267822 \n",
"4965 0.264648 \n",
"4966 0.272949 \n",
"4967 0.255127 \n",
"6620 0.189941 \n",
"6621 0.201294 \n",
"6622 0.102417 \n",
"6623 0.178833 \n",
"\n",
" log_volume__co_firstmin_ac__w=7_catch \\\n",
"1652 3.0 \n",
"1653 3.0 \n",
"1654 3.0 \n",
"1655 2.0 \n",
"3308 3.0 \n",
"3309 2.0 \n",
"3310 2.0 \n",
"3311 2.0 \n",
"4964 1.0 \n",
"4965 1.0 \n",
"4966 2.0 \n",
"4967 1.0 \n",
"6620 3.0 \n",
"6621 3.0 \n",
"6622 4.0 \n",
"6623 7.0 \n",
"\n",
" log_volume__co_histogramami_even_2_5__w=7_catch \\\n",
"1652 1.609375 \n",
"1653 0.950195 \n",
"1654 0.672852 \n",
"1655 0.672852 \n",
"3308 0.568359 \n",
"3309 0.568359 \n",
"3310 0.500488 \n",
"3311 0.050537 \n",
"4964 0.672852 \n",
"4965 0.672852 \n",
"4966 0.291016 \n",
"4967 0.672852 \n",
"6620 0.291016 \n",
"6621 0.395752 \n",
"6622 0.395752 \n",
"6623 0.500488 \n",
"\n",
" log_volume__co_f1ecac__w=7_catch log_volume__co_trev_1_num__w=7_catch \\\n",
"1652 0.993652 0.208130 \n",
"1653 1.058594 0.404541 \n",
"1654 1.183594 0.728516 \n",
"1655 0.643555 1.667969 \n",
"3308 0.670898 -0.875977 \n",
"3309 0.622070 -0.454590 \n",
"3310 0.617676 -0.444824 \n",
"3311 0.656250 1.441406 \n",
"4964 0.559082 -1.511719 \n",
"4965 0.734863 1.906250 \n",
"4966 0.616699 1.108398 \n",
"4967 0.480957 2.625000 \n",
"6620 0.997559 -0.912109 \n",
"6621 1.018555 -1.017578 \n",
"6622 1.550781 0.316162 \n",
"6623 1.094727 0.513672 \n",
"\n",
" log_volume__dn_histogrammode_10__w=7_catch \\\n",
"1652 0.410156 \n",
"1653 0.704590 \n",
"1654 0.511230 \n",
"1655 -0.190552 \n",
"3308 0.073120 \n",
"3309 0.304443 \n",
"3310 0.292969 \n",
"3311 -0.074280 \n",
"4964 0.275879 \n",
"4965 0.507812 \n",
"4966 0.482910 \n",
"4967 0.128418 \n",
"6620 -0.027039 \n",
"6621 0.937500 \n",
"6622 -0.008049 \n",
"6623 0.665039 \n",
"\n",
" log_volume__dn_histogrammode_5__w=7_catch \\\n",
"1652 0.553711 \n",
"1653 0.704590 \n",
"1654 0.799316 \n",
"1655 -0.355713 \n",
"3308 -0.094604 \n",
"3309 0.142944 \n",
"3310 0.132202 \n",
"3311 0.094360 \n",
"4964 0.119019 \n",
"4965 0.653320 \n",
"4966 0.633301 \n",
"4967 -0.030655 \n",
"6620 -0.027039 \n",
"6621 -0.049988 \n",
"6622 -0.920410 \n",
"6623 -0.226929 \n",
"\n",
" log_volume__dn_outlierinclude_n_001_mdrmd__w=7_catch \\\n",
"1652 0.000000 \n",
"1653 -0.285645 \n",
"1654 -0.571289 \n",
"1655 -0.428467 \n",
"3308 0.285645 \n",
"3309 -0.142822 \n",
"3310 -0.428467 \n",
"3311 -0.428467 \n",
"4964 -0.142822 \n",
"4965 -0.428467 \n",
"4966 -0.428467 \n",
"4967 0.000000 \n",
"6620 0.142822 \n",
"6621 -0.142822 \n",
"6622 -0.428467 \n",
"6623 -0.571289 \n",
"\n",
" log_volume__dn_outlierinclude_p_001_mdrmd__w=7_catch \\\n",
"1652 0.142822 \n",
"1653 0.571289 \n",
"1654 0.428467 \n",
"1655 0.285645 \n",
"3308 0.000000 \n",
"3309 0.000000 \n",
"3310 0.285645 \n",
"3311 0.428467 \n",
"4964 0.428467 \n",
"4965 0.571289 \n",
"4966 0.285645 \n",
"4967 0.714355 \n",
"6620 -0.428467 \n",
"6621 0.714355 \n",
"6622 0.571289 \n",
"6623 0.428467 \n",
"\n",
" log_volume__fc_localsimple_mean1_tauresrat__w=7_catch \\\n",
"1652 1.000000 \n",
"1653 1.000000 \n",
"1654 0.500000 \n",
"1655 0.500000 \n",
"3308 0.500000 \n",
"3309 1.000000 \n",
"3310 1.000000 \n",
"3311 1.000000 \n",
"4964 1.000000 \n",
"4965 0.333252 \n",
"4966 1.000000 \n",
"4967 1.000000 \n",
"6620 1.000000 \n",
"6621 1.000000 \n",
"6622 0.666504 \n",
"6623 0.333252 \n",
"\n",
" log_volume__fc_localsimple_mean3_stderr__w=7_catch \\\n",
"1652 1.572266 \n",
"1653 0.747070 \n",
"1654 1.194336 \n",
"1655 0.986816 \n",
"3308 1.530273 \n",
"3309 0.875488 \n",
"3310 0.955078 \n",
"3311 0.978516 \n",
"4964 1.281250 \n",
"4965 0.477295 \n",
"4966 1.041992 \n",
"4967 1.049805 \n",
"6620 1.381836 \n",
"6621 0.861816 \n",
"6622 0.800781 \n",
"6623 0.699219 \n",
"\n",
" log_volume__in_automutualinfostats_40_gaussian_fmmi__w=7_catch \\\n",
"1652 4.0 \n",
"1653 1.0 \n",
"1654 1.0 \n",
"1655 1.0 \n",
"3308 4.0 \n",
"3309 2.0 \n",
"3310 2.0 \n",
"3311 1.0 \n",
"4964 1.0 \n",
"4965 4.0 \n",
"4966 2.0 \n",
"4967 4.0 \n",
"6620 4.0 \n",
"6621 1.0 \n",
"6622 2.0 \n",
"6623 1.0 \n",
"\n",
" log_volume__md_hrv_classic_pnn40__w=7_catch \\\n",
"1652 1.000000 \n",
"1653 1.000000 \n",
"1654 1.000000 \n",
"1655 1.000000 \n",
"3308 0.833496 \n",
"3309 1.000000 \n",
"3310 1.000000 \n",
"3311 1.000000 \n",
"4964 1.000000 \n",
"4965 1.000000 \n",
"4966 1.000000 \n",
"4967 1.000000 \n",
"6620 0.833496 \n",
"6621 0.833496 \n",
"6622 0.833496 \n",
"6623 1.000000 \n",
"\n",
" log_volume__pd_periodicitywang_th0_01__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sb_binarystats_diff_longstretch0__w=7_catch \\\n",
"1652 3.0 \n",
"1653 2.0 \n",
"1654 2.0 \n",
"1655 3.0 \n",
"3308 3.0 \n",
"3309 2.0 \n",
"3310 3.0 \n",
"3311 3.0 \n",
"4964 2.0 \n",
"4965 3.0 \n",
"4966 3.0 \n",
"4967 3.0 \n",
"6620 3.0 \n",
"6621 2.0 \n",
"6622 2.0 \n",
"6623 3.0 \n",
"\n",
" log_volume__sb_binarystats_mean_longstretch1__w=7_catch \\\n",
"1652 2.0 \n",
"1653 2.0 \n",
"1654 3.0 \n",
"1655 4.0 \n",
"3308 1.0 \n",
"3309 3.0 \n",
"3310 4.0 \n",
"3311 2.0 \n",
"4964 2.0 \n",
"4965 3.0 \n",
"4966 4.0 \n",
"4967 3.0 \n",
"6620 2.0 \n",
"6621 2.0 \n",
"6622 3.0 \n",
"6623 3.0 \n",
"\n",
" log_volume__sb_motifthree_quantile_hh__w=7_catch \\\n",
"1652 1.791992 \n",
"1653 1.791992 \n",
"1654 1.791992 \n",
"1655 1.560547 \n",
"3308 1.560547 \n",
"3309 1.791992 \n",
"3310 1.791992 \n",
"3311 1.560547 \n",
"4964 1.791992 \n",
"4965 1.791992 \n",
"4966 1.791992 \n",
"4967 1.560547 \n",
"6620 1.791992 \n",
"6621 1.791992 \n",
"6622 1.791992 \n",
"6623 1.560547 \n",
"\n",
" log_volume__sb_transitionmatrix_3ac_sumdiagcov__w=7_catch \\\n",
"1652 0.074097 \n",
"1653 0.111084 \n",
"1654 0.074097 \n",
"1655 0.074097 \n",
"3308 0.074097 \n",
"3309 0.027771 \n",
"3310 0.027771 \n",
"3311 0.074097 \n",
"4964 0.018524 \n",
"4965 0.166626 \n",
"4966 0.027771 \n",
"4967 0.046295 \n",
"6620 0.074097 \n",
"6621 0.111084 \n",
"6622 0.166626 \n",
"6623 0.166626 \n",
"\n",
" log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sp_summaries_welch_rect_area_5_1__w=7_catch \\\n",
"1652 0.0 \n",
"1653 0.0 \n",
"1654 0.0 \n",
"1655 0.0 \n",
"3308 0.0 \n",
"3309 0.0 \n",
"3310 0.0 \n",
"3311 0.0 \n",
"4964 0.0 \n",
"4965 0.0 \n",
"4966 0.0 \n",
"4967 0.0 \n",
"6620 0.0 \n",
"6621 0.0 \n",
"6622 0.0 \n",
"6623 0.0 \n",
"\n",
" log_volume__sp_summaries_welch_rect_centroid__w=7_catch year_date \\\n",
"1652 0.785156 2022 \n",
"1653 0.785156 2022 \n",
"1654 0.785156 2022 \n",
"1655 1.570312 2022 \n",
"3308 1.570312 2022 \n",
"3309 1.570312 2022 \n",
"3310 1.570312 2022 \n",
"3311 1.570312 2022 \n",
"4964 1.570312 2022 \n",
"4965 0.785156 2022 \n",
"4966 1.570312 2022 \n",
"4967 2.355469 2022 \n",
"6620 0.785156 2022 \n",
"6621 0.785156 2022 \n",
"6622 0.785156 2022 \n",
"6623 0.785156 2022 \n",
"\n",
" month_date quarter_date semester_date dayofweek_date dayofyear_date \\\n",
"1652 2 1 1 1 53 \n",
"1653 2 1 1 2 54 \n",
"1654 2 1 1 3 55 \n",
"1655 2 1 1 4 56 \n",
"3308 2 1 1 1 53 \n",
"3309 2 1 1 2 54 \n",
"3310 2 1 1 3 55 \n",
"3311 2 1 1 4 56 \n",
"4964 2 1 1 1 53 \n",
"4965 2 1 1 2 54 \n",
"4966 2 1 1 3 55 \n",
"4967 2 1 1 4 56 \n",
"6620 2 1 1 1 53 \n",
"6621 2 1 1 2 54 \n",
"6622 2 1 1 3 55 \n",
"6623 2 1 1 4 56 \n",
"\n",
" weekofyear_date sin_month_date cos_month_date sin_quarter_date \\\n",
"1652 8 0.866211 0.5 1.0 \n",
"1653 8 0.866211 0.5 1.0 \n",
"1654 8 0.866211 0.5 1.0 \n",
"1655 8 0.866211 0.5 1.0 \n",
"3308 8 0.866211 0.5 1.0 \n",
"3309 8 0.866211 0.5 1.0 \n",
"3310 8 0.866211 0.5 1.0 \n",
"3311 8 0.866211 0.5 1.0 \n",
"4964 8 0.866211 0.5 1.0 \n",
"4965 8 0.866211 0.5 1.0 \n",
"4966 8 0.866211 0.5 1.0 \n",
"4967 8 0.866211 0.5 1.0 \n",
"6620 8 0.866211 0.5 1.0 \n",
"6621 8 0.866211 0.5 1.0 \n",
"6622 8 0.866211 0.5 1.0 \n",
"6623 8 0.866211 0.5 1.0 \n",
"\n",
" cos_quarter_date sin_dayofweek_date cos_dayofweek_date \\\n",
"1652 0.0 0.781738 0.623535 \n",
"1653 0.0 0.975098 -0.222534 \n",
"1654 0.0 0.433838 -0.900879 \n",
"1655 0.0 -0.433838 -0.900879 \n",
"3308 0.0 0.781738 0.623535 \n",
"3309 0.0 0.975098 -0.222534 \n",
"3310 0.0 0.433838 -0.900879 \n",
"3311 0.0 -0.433838 -0.900879 \n",
"4964 0.0 0.781738 0.623535 \n",
"4965 0.0 0.975098 -0.222534 \n",
"4966 0.0 0.433838 -0.900879 \n",
"4967 0.0 -0.433838 -0.900879 \n",
"6620 0.0 0.781738 0.623535 \n",
"6621 0.0 0.975098 -0.222534 \n",
"6622 0.0 0.433838 -0.900879 \n",
"6623 0.0 -0.433838 -0.900879 \n",
"\n",
" sin_weekofyear_date cos_weekofyear_date return Target \n",
"1652 0.8125 0.583008 -0.017090 -0.027344 \n",
"1653 0.8125 0.583008 -0.025879 0.015625 \n",
"1654 0.8125 0.583008 0.016602 0.011719 \n",
"1655 0.8125 0.583008 0.012695 NaN \n",
"3308 0.8125 0.583008 -0.001465 -0.023438 \n",
"3309 0.8125 0.583008 -0.020508 -0.027344 \n",
"3310 0.8125 0.583008 -0.028809 0.023438 \n",
"3311 0.8125 0.583008 0.024414 NaN \n",
"4964 0.8125 0.583008 -0.000977 -0.027344 \n",
"4965 0.8125 0.583008 -0.026367 0.050781 \n",
"4966 0.8125 0.583008 0.051758 0.007812 \n",
"4967 0.8125 0.583008 0.009766 NaN \n",
"6620 0.8125 0.583008 -0.041992 -0.074219 \n",
"6621 0.8125 0.583008 -0.069824 0.046875 \n",
"6622 0.8125 0.583008 0.048828 0.011719 \n",
"6623 0.8125 0.583008 0.011719 NaN "
],
"text/html": [
"\n",
" <div id=\"df-51402608-1917-476f-876c-97304e08e650\">\n",
" <div class=\"colab-df-container\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>Ticker</th>\n",
" <th>Adj Close</th>\n",
" <th>Close</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Open</th>\n",
" <th>Volume</th>\n",
" <th>date_old</th>\n",
" <th>DCL_20_20</th>\n",
" <th>DCM_20_20</th>\n",
" <th>DCU_20_20</th>\n",
" <th>BBL_5_2.0</th>\n",
" <th>BBM_5_2.0</th>\n",
" <th>BBU_5_2.0</th>\n",
" <th>BBB_5_2.0</th>\n",
" <th>BBP_5_2.0</th>\n",
" <th>SMA_10</th>\n",
" <th>MACD_12_26_9</th>\n",
" <th>MACDh_12_26_9</th>\n",
" <th>MACDs_12_26_9</th>\n",
" <th>High_mean_rolling_3</th>\n",
" <th>High_std_rolling_3</th>\n",
" <th>High_skew_rolling_3</th>\n",
" <th>High_max_rolling_3</th>\n",
" <th>High_min_rolling_3</th>\n",
" <th>High_median_rolling_3</th>\n",
" <th>Low_mean_rolling_3</th>\n",
" <th>Low_std_rolling_3</th>\n",
" <th>Low_skew_rolling_3</th>\n",
" <th>Low_max_rolling_3</th>\n",
" <th>Low_min_rolling_3</th>\n",
" <th>Low_median_rolling_3</th>\n",
" <th>High_mean_rolling_4</th>\n",
" <th>High_std_rolling_4</th>\n",
" <th>High_skew_rolling_4</th>\n",
" <th>High_max_rolling_4</th>\n",
" <th>High_min_rolling_4</th>\n",
" <th>High_median_rolling_4</th>\n",
" <th>Low_mean_rolling_4</th>\n",
" <th>Low_std_rolling_4</th>\n",
" <th>Low_skew_rolling_4</th>\n",
" <th>Low_max_rolling_4</th>\n",
" <th>Low_min_rolling_4</th>\n",
" <th>Low_median_rolling_4</th>\n",
" <th>High_mean_rolling_6</th>\n",
" <th>High_std_rolling_6</th>\n",
" <th>High_skew_rolling_6</th>\n",
" <th>High_max_rolling_6</th>\n",
" <th>High_min_rolling_6</th>\n",
" <th>High_median_rolling_6</th>\n",
" <th>Low_mean_rolling_6</th>\n",
" <th>Low_std_rolling_6</th>\n",
" <th>Low_skew_rolling_6</th>\n",
" <th>Low_max_rolling_6</th>\n",
" <th>Low_min_rolling_6</th>\n",
" <th>Low_median_rolling_6</th>\n",
" <th>High_mean_rolling_8</th>\n",
" <th>High_std_rolling_8</th>\n",
" <th>High_skew_rolling_8</th>\n",
" <th>High_max_rolling_8</th>\n",
" <th>High_min_rolling_8</th>\n",
" <th>High_median_rolling_8</th>\n",
" <th>Low_mean_rolling_8</th>\n",
" <th>Low_std_rolling_8</th>\n",
" <th>Low_skew_rolling_8</th>\n",
" <th>Low_max_rolling_8</th>\n",
" <th>Low_min_rolling_8</th>\n",
" <th>Low_median_rolling_8</th>\n",
" <th>log_return</th>\n",
" <th>log_volume</th>\n",
" <th>log_return__co_embed2_dist_tau_d_expfit_meandiff__w=30_catch</th>\n",
" <th>log_return__co_firstmin_ac__w=30_catch</th>\n",
" <th>log_return__co_histogramami_even_2_5__w=30_catch</th>\n",
" <th>log_return__co_f1ecac__w=30_catch</th>\n",
" <th>log_return__co_trev_1_num__w=30_catch</th>\n",
" <th>log_return__dn_histogrammode_10__w=30_catch</th>\n",
" <th>log_return__dn_histogrammode_5__w=30_catch</th>\n",
" <th>log_return__dn_outlierinclude_n_001_mdrmd__w=30_catch</th>\n",
" <th>log_return__dn_outlierinclude_p_001_mdrmd__w=30_catch</th>\n",
" <th>log_return__fc_localsimple_mean1_tauresrat__w=30_catch</th>\n",
" <th>log_return__fc_localsimple_mean3_stderr__w=30_catch</th>\n",
" <th>log_return__in_automutualinfostats_40_gaussian_fmmi__w=30_catch</th>\n",
" <th>log_return__md_hrv_classic_pnn40__w=30_catch</th>\n",
" <th>log_return__pd_periodicitywang_th0_01__w=30_catch</th>\n",
" <th>log_return__sb_binarystats_diff_longstretch0__w=30_catch</th>\n",
" <th>log_return__sb_binarystats_mean_longstretch1__w=30_catch</th>\n",
" <th>log_return__sb_motifthree_quantile_hh__w=30_catch</th>\n",
" <th>log_return__sb_transitionmatrix_3ac_sumdiagcov__w=30_catch</th>\n",
" <th>log_return__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=30_catch</th>\n",
" <th>log_return__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=30_catch</th>\n",
" <th>log_return__sp_summaries_welch_rect_area_5_1__w=30_catch</th>\n",
" <th>log_return__sp_summaries_welch_rect_centroid__w=30_catch</th>\n",
" <th>log_volume__co_embed2_dist_tau_d_expfit_meandiff__w=30_catch</th>\n",
" <th>log_volume__co_firstmin_ac__w=30_catch</th>\n",
" <th>log_volume__co_histogramami_even_2_5__w=30_catch</th>\n",
" <th>log_volume__co_f1ecac__w=30_catch</th>\n",
" <th>log_volume__co_trev_1_num__w=30_catch</th>\n",
" <th>log_volume__dn_histogrammode_10__w=30_catch</th>\n",
" <th>log_volume__dn_histogrammode_5__w=30_catch</th>\n",
" <th>log_volume__dn_outlierinclude_n_001_mdrmd__w=30_catch</th>\n",
" <th>log_volume__dn_outlierinclude_p_001_mdrmd__w=30_catch</th>\n",
" <th>log_volume__fc_localsimple_mean1_tauresrat__w=30_catch</th>\n",
" <th>log_volume__fc_localsimple_mean3_stderr__w=30_catch</th>\n",
" <th>log_volume__in_automutualinfostats_40_gaussian_fmmi__w=30_catch</th>\n",
" <th>log_volume__md_hrv_classic_pnn40__w=30_catch</th>\n",
" <th>log_volume__pd_periodicitywang_th0_01__w=30_catch</th>\n",
" <th>log_volume__sb_binarystats_diff_longstretch0__w=30_catch</th>\n",
" <th>log_volume__sb_binarystats_mean_longstretch1__w=30_catch</th>\n",
" <th>log_volume__sb_motifthree_quantile_hh__w=30_catch</th>\n",
" <th>log_volume__sb_transitionmatrix_3ac_sumdiagcov__w=30_catch</th>\n",
" <th>log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=30_catch</th>\n",
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" <th>log_volume__sp_summaries_welch_rect_area_5_1__w=30_catch</th>\n",
" <th>log_volume__sp_summaries_welch_rect_centroid__w=30_catch</th>\n",
" <th>log_return__co_embed2_dist_tau_d_expfit_meandiff__w=7_catch</th>\n",
" <th>log_return__co_firstmin_ac__w=7_catch</th>\n",
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" <th>log_return__dn_outlierinclude_p_001_mdrmd__w=7_catch</th>\n",
" <th>log_return__fc_localsimple_mean1_tauresrat__w=7_catch</th>\n",
" <th>log_return__fc_localsimple_mean3_stderr__w=7_catch</th>\n",
" <th>log_return__in_automutualinfostats_40_gaussian_fmmi__w=7_catch</th>\n",
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" <th>log_volume__co_firstmin_ac__w=7_catch</th>\n",
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" <th>log_volume__fc_localsimple_mean3_stderr__w=7_catch</th>\n",
" <th>log_volume__in_automutualinfostats_40_gaussian_fmmi__w=7_catch</th>\n",
" <th>log_volume__md_hrv_classic_pnn40__w=7_catch</th>\n",
" <th>log_volume__pd_periodicitywang_th0_01__w=7_catch</th>\n",
" <th>log_volume__sb_binarystats_diff_longstretch0__w=7_catch</th>\n",
" <th>log_volume__sb_binarystats_mean_longstretch1__w=7_catch</th>\n",
" <th>log_volume__sb_motifthree_quantile_hh__w=7_catch</th>\n",
" <th>log_volume__sb_transitionmatrix_3ac_sumdiagcov__w=7_catch</th>\n",
" <th>log_volume__sc_fluctanal_2_dfa_50_1_2_logi_prop_r1__w=7_catch</th>\n",
" <th>log_volume__sc_fluctanal_2_rsrangefit_50_1_logi_prop_r1__w=7_catch</th>\n",
" <th>log_volume__sp_summaries_welch_rect_area_5_1__w=7_catch</th>\n",
" <th>log_volume__sp_summaries_welch_rect_centroid__w=7_catch</th>\n",
" <th>year_date</th>\n",
" <th>month_date</th>\n",
" <th>quarter_date</th>\n",
" <th>semester_date</th>\n",
" <th>dayofweek_date</th>\n",
" <th>dayofyear_date</th>\n",
" <th>weekofyear_date</th>\n",
" <th>sin_month_date</th>\n",
" <th>cos_month_date</th>\n",
" <th>sin_quarter_date</th>\n",
" <th>cos_quarter_date</th>\n",
" <th>sin_dayofweek_date</th>\n",
" <th>cos_dayofweek_date</th>\n",
" <th>sin_weekofyear_date</th>\n",
" <th>cos_weekofyear_date</th>\n",
" <th>return</th>\n",
" <th>Target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1652</th>\n",
" <td>2022-02-22</td>\n",
" <td>AAPL</td>\n",
" <td>163.375</td>\n",
" <td>164.375</td>\n",
" <td>166.750</td>\n",
" <td>162.125</td>\n",
" <td>165.000</td>\n",
" <td>91162800.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>154.750</td>\n",
" <td>166.000</td>\n",
" <td>177.125</td>\n",
" <td>170.375</td>\n",
" <td>173.500</td>\n",
" <td>176.500</td>\n",
" <td>3.525391</td>\n",
" <td>0.202393</td>\n",
" <td>169.125</td>\n",
" <td>0.368652</td>\n",
" <td>0.783691</td>\n",
" <td>-0.415283</td>\n",
" <td>169.75</td>\n",
" <td>2.707031</td>\n",
" <td>-1.246094</td>\n",
" <td>171.875</td>\n",
" <td>166.750</td>\n",
" <td>170.500</td>\n",
" <td>165.625</td>\n",
" <td>3.201172</td>\n",
" <td>-0.797363</td>\n",
" <td>168.500</td>\n",
" <td>162.125</td>\n",
" <td>166.250</td>\n",
" <td>170.625</td>\n",
" <td>2.859375</td>\n",
" <td>-1.096680</td>\n",
" <td>173.375</td>\n",
" <td>166.750</td>\n",
" <td>171.250</td>\n",
" <td>166.750</td>\n",
" <td>3.431641</td>\n",
" <td>-0.871094</td>\n",
" <td>170.000</td>\n",
" <td>162.125</td>\n",
" <td>167.375</td>\n",
" <td>170.875</td>\n",
" <td>2.480469</td>\n",
" <td>-0.920410</td>\n",
" <td>173.375</td>\n",
" <td>166.750</td>\n",
" <td>171.250</td>\n",
" <td>167.250</td>\n",
" <td>3.031250</td>\n",
" <td>-0.940430</td>\n",
" <td>170.250</td>\n",
" <td>162.125</td>\n",
" <td>167.500</td>\n",
" <td>171.750</td>\n",
" <td>2.710938</td>\n",
" <td>-0.700684</td>\n",
" <td>175.500</td>\n",
" <td>166.750</td>\n",
" <td>172.375</td>\n",
" <td>167.875</td>\n",
" <td>2.966797</td>\n",
" <td>-0.928223</td>\n",
" <td>171.500</td>\n",
" <td>162.125</td>\n",
" <td>168.250</td>\n",
" <td>-0.015625</td>\n",
" <td>0.096558</td>\n",
" <td>0.112061</td>\n",
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" <td>-0.009048</td>\n",
" <td>0.237549</td>\n",
" <td>-0.033325</td>\n",
" <td>0.066650</td>\n",
" <td>0.500000</td>\n",
" <td>1.224609</td>\n",
" <td>1.0</td>\n",
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" <td>2.154297</td>\n",
" <td>0.010201</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.190674</td>\n",
" <td>1.177734</td>\n",
" <td>0.092834</td>\n",
" <td>2.0</td>\n",
" <td>0.381348</td>\n",
" <td>0.617676</td>\n",
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" <td>-0.313232</td>\n",
" <td>-0.107544</td>\n",
" <td>0.066650</td>\n",
" <td>-0.133301</td>\n",
" <td>1.0</td>\n",
" <td>1.254883</td>\n",
" <td>2.0</td>\n",
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" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
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" <td>0.004360</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.054443</td>\n",
" <td>1.374023</td>\n",
" <td>0.260986</td>\n",
" <td>2.0</td>\n",
" <td>0.777832</td>\n",
" <td>0.895996</td>\n",
" <td>-0.011047</td>\n",
" <td>-0.842285</td>\n",
" <td>-0.702148</td>\n",
" <td>-0.428467</td>\n",
" <td>0.142822</td>\n",
" <td>1.0</td>\n",
" <td>1.665039</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.183594</td>\n",
" <td>3.0</td>\n",
" <td>1.609375</td>\n",
" <td>0.993652</td>\n",
" <td>0.208130</td>\n",
" <td>0.410156</td>\n",
" <td>0.553711</td>\n",
" <td>0.000000</td>\n",
" <td>0.142822</td>\n",
" <td>1.000000</td>\n",
" <td>1.572266</td>\n",
" <td>4.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.785156</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>53</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.781738</td>\n",
" <td>0.623535</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>-0.017090</td>\n",
" <td>-0.027344</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1653</th>\n",
" <td>2022-02-23</td>\n",
" <td>AAPL</td>\n",
" <td>159.125</td>\n",
" <td>160.125</td>\n",
" <td>166.125</td>\n",
" <td>159.750</td>\n",
" <td>165.500</td>\n",
" <td>90009200.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>154.750</td>\n",
" <td>166.000</td>\n",
" <td>177.125</td>\n",
" <td>170.375</td>\n",
" <td>173.500</td>\n",
" <td>176.625</td>\n",
" <td>3.603516</td>\n",
" <td>0.708984</td>\n",
" <td>170.625</td>\n",
" <td>0.678711</td>\n",
" <td>0.875000</td>\n",
" <td>-0.196411</td>\n",
" <td>167.75</td>\n",
" <td>2.394531</td>\n",
" <td>1.633789</td>\n",
" <td>170.500</td>\n",
" <td>166.125</td>\n",
" <td>166.750</td>\n",
" <td>162.750</td>\n",
" <td>3.253906</td>\n",
" <td>0.734375</td>\n",
" <td>166.250</td>\n",
" <td>159.750</td>\n",
" <td>162.125</td>\n",
" <td>168.875</td>\n",
" <td>2.837891</td>\n",
" <td>0.166504</td>\n",
" <td>171.875</td>\n",
" <td>166.125</td>\n",
" <td>168.625</td>\n",
" <td>164.125</td>\n",
" <td>3.923828</td>\n",
" <td>-0.029663</td>\n",
" <td>168.500</td>\n",
" <td>159.750</td>\n",
" <td>164.125</td>\n",
" <td>170.250</td>\n",
" <td>3.134766</td>\n",
" <td>-0.605469</td>\n",
" <td>173.375</td>\n",
" <td>166.125</td>\n",
" <td>171.250</td>\n",
" <td>166.125</td>\n",
" <td>4.343750</td>\n",
" <td>-0.671387</td>\n",
" <td>170.250</td>\n",
" <td>159.750</td>\n",
" <td>167.375</td>\n",
" <td>170.500</td>\n",
" <td>2.853516</td>\n",
" <td>-0.704590</td>\n",
" <td>173.375</td>\n",
" <td>166.125</td>\n",
" <td>171.250</td>\n",
" <td>166.375</td>\n",
" <td>3.732422</td>\n",
" <td>-0.958496</td>\n",
" <td>170.250</td>\n",
" <td>159.750</td>\n",
" <td>167.250</td>\n",
" <td>-0.027344</td>\n",
" <td>-0.012733</td>\n",
" <td>0.130859</td>\n",
" <td>4.0</td>\n",
" <td>0.107971</td>\n",
" <td>0.871094</td>\n",
" <td>1.137695</td>\n",
" <td>0.024734</td>\n",
" <td>0.267822</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.500000</td>\n",
" <td>1.208984</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>5.0</td>\n",
" <td>2.132812</td>\n",
" <td>0.015305</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.176025</td>\n",
" <td>0.981934</td>\n",
" <td>0.091125</td>\n",
" <td>2.0</td>\n",
" <td>0.447021</td>\n",
" <td>0.639160</td>\n",
" <td>-3.335938</td>\n",
" <td>-0.347656</td>\n",
" <td>-0.141846</td>\n",
" <td>0.000000</td>\n",
" <td>-0.199951</td>\n",
" <td>0.5</td>\n",
" <td>1.255859</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>2.166016</td>\n",
" <td>0.045929</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.050598</td>\n",
" <td>1.374023</td>\n",
" <td>0.243774</td>\n",
" <td>2.0</td>\n",
" <td>0.777832</td>\n",
" <td>0.773438</td>\n",
" <td>-0.040894</td>\n",
" <td>-0.797363</td>\n",
" <td>-0.657227</td>\n",
" <td>0.428467</td>\n",
" <td>-0.142822</td>\n",
" <td>1.0</td>\n",
" <td>0.736816</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.111084</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.214355</td>\n",
" <td>3.0</td>\n",
" <td>0.950195</td>\n",
" <td>1.058594</td>\n",
" <td>0.404541</td>\n",
" <td>0.704590</td>\n",
" <td>0.704590</td>\n",
" <td>-0.285645</td>\n",
" <td>0.571289</td>\n",
" <td>1.000000</td>\n",
" <td>0.747070</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.111084</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.785156</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>54</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.975098</td>\n",
" <td>-0.222534</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>-0.025879</td>\n",
" <td>0.015625</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1654</th>\n",
" <td>2022-02-24</td>\n",
" <td>AAPL</td>\n",
" <td>161.750</td>\n",
" <td>162.750</td>\n",
" <td>162.875</td>\n",
" <td>152.000</td>\n",
" <td>152.625</td>\n",
" <td>141147504.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>154.750</td>\n",
" <td>166.000</td>\n",
" <td>177.125</td>\n",
" <td>170.250</td>\n",
" <td>173.625</td>\n",
" <td>177.000</td>\n",
" <td>3.912109</td>\n",
" <td>0.893066</td>\n",
" <td>172.250</td>\n",
" <td>1.029297</td>\n",
" <td>0.980469</td>\n",
" <td>0.048706</td>\n",
" <td>165.25</td>\n",
" <td>2.078125</td>\n",
" <td>-1.601562</td>\n",
" <td>166.750</td>\n",
" <td>162.875</td>\n",
" <td>166.125</td>\n",
" <td>158.000</td>\n",
" <td>5.304688</td>\n",
" <td>-1.341797</td>\n",
" <td>162.125</td>\n",
" <td>152.000</td>\n",
" <td>159.750</td>\n",
" <td>166.500</td>\n",
" <td>3.150391</td>\n",
" <td>0.258545</td>\n",
" <td>170.500</td>\n",
" <td>162.875</td>\n",
" <td>166.375</td>\n",
" <td>160.000</td>\n",
" <td>5.972656</td>\n",
" <td>-0.851562</td>\n",
" <td>166.250</td>\n",
" <td>152.000</td>\n",
" <td>161.000</td>\n",
" <td>168.625</td>\n",
" <td>3.998047</td>\n",
" <td>-0.267334</td>\n",
" <td>173.375</td>\n",
" <td>162.875</td>\n",
" <td>168.625</td>\n",
" <td>163.125</td>\n",
" <td>6.664062</td>\n",
" <td>-0.899414</td>\n",
" <td>170.000</td>\n",
" <td>152.000</td>\n",
" <td>164.125</td>\n",
" <td>169.250</td>\n",
" <td>3.710938</td>\n",
" <td>-0.629883</td>\n",
" <td>173.375</td>\n",
" <td>162.875</td>\n",
" <td>170.000</td>\n",
" <td>164.375</td>\n",
" <td>6.222656</td>\n",
" <td>-1.247070</td>\n",
" <td>170.250</td>\n",
" <td>152.000</td>\n",
" <td>166.375</td>\n",
" <td>0.015625</td>\n",
" <td>0.449951</td>\n",
" <td>0.115295</td>\n",
" <td>4.0</td>\n",
" <td>0.111206</td>\n",
" <td>0.893555</td>\n",
" <td>1.022461</td>\n",
" <td>-0.990723</td>\n",
" <td>-0.748535</td>\n",
" <td>0.466553</td>\n",
" <td>-0.066650</td>\n",
" <td>0.500000</td>\n",
" <td>1.152344</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>5.0</td>\n",
" <td>2.166016</td>\n",
" <td>0.020401</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.166626</td>\n",
" <td>0.981934</td>\n",
" <td>0.093323</td>\n",
" <td>2.0</td>\n",
" <td>0.447021</td>\n",
" <td>0.681641</td>\n",
" <td>-2.818359</td>\n",
" <td>-0.317139</td>\n",
" <td>-0.107483</td>\n",
" <td>-0.066650</td>\n",
" <td>-0.166626</td>\n",
" <td>0.5</td>\n",
" <td>1.279297</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>2.166016</td>\n",
" <td>0.015305</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.059052</td>\n",
" <td>1.374023</td>\n",
" <td>0.222046</td>\n",
" <td>2.0</td>\n",
" <td>0.672852</td>\n",
" <td>0.988770</td>\n",
" <td>-0.418457</td>\n",
" <td>-0.239258</td>\n",
" <td>-0.822754</td>\n",
" <td>0.714355</td>\n",
" <td>-0.428467</td>\n",
" <td>0.5</td>\n",
" <td>0.606934</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.785156</td>\n",
" <td>0.219116</td>\n",
" <td>3.0</td>\n",
" <td>0.672852</td>\n",
" <td>1.183594</td>\n",
" <td>0.728516</td>\n",
" <td>0.511230</td>\n",
" <td>0.799316</td>\n",
" <td>-0.571289</td>\n",
" <td>0.428467</td>\n",
" <td>0.500000</td>\n",
" <td>1.194336</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.785156</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>55</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.433838</td>\n",
" <td>-0.900879</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>0.016602</td>\n",
" <td>0.011719</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1655</th>\n",
" <td>2022-02-25</td>\n",
" <td>AAPL</td>\n",
" <td>163.875</td>\n",
" <td>164.875</td>\n",
" <td>165.125</td>\n",
" <td>160.875</td>\n",
" <td>163.875</td>\n",
" <td>91974200.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>154.750</td>\n",
" <td>165.625</td>\n",
" <td>176.625</td>\n",
" <td>169.875</td>\n",
" <td>173.500</td>\n",
" <td>177.000</td>\n",
" <td>4.125000</td>\n",
" <td>0.313232</td>\n",
" <td>173.625</td>\n",
" <td>0.960449</td>\n",
" <td>0.729492</td>\n",
" <td>0.231079</td>\n",
" <td>164.75</td>\n",
" <td>1.688477</td>\n",
" <td>-1.035156</td>\n",
" <td>166.125</td>\n",
" <td>162.875</td>\n",
" <td>165.125</td>\n",
" <td>157.500</td>\n",
" <td>4.832031</td>\n",
" <td>-1.627930</td>\n",
" <td>160.875</td>\n",
" <td>152.000</td>\n",
" <td>159.750</td>\n",
" <td>165.250</td>\n",
" <td>1.698242</td>\n",
" <td>-1.208984</td>\n",
" <td>166.750</td>\n",
" <td>162.875</td>\n",
" <td>165.625</td>\n",
" <td>158.750</td>\n",
" <td>4.566406</td>\n",
" <td>-1.726562</td>\n",
" <td>162.125</td>\n",
" <td>152.000</td>\n",
" <td>160.250</td>\n",
" <td>167.250</td>\n",
" <td>3.404297</td>\n",
" <td>0.360352</td>\n",
" <td>171.875</td>\n",
" <td>162.875</td>\n",
" <td>166.375</td>\n",
" <td>161.625</td>\n",
" <td>5.738281</td>\n",
" <td>-0.724121</td>\n",
" <td>168.500</td>\n",
" <td>152.000</td>\n",
" <td>161.500</td>\n",
" <td>168.750</td>\n",
" <td>3.980469</td>\n",
" <td>-0.159424</td>\n",
" <td>173.375</td>\n",
" <td>162.875</td>\n",
" <td>168.625</td>\n",
" <td>163.750</td>\n",
" <td>6.269531</td>\n",
" <td>-0.805664</td>\n",
" <td>170.250</td>\n",
" <td>152.000</td>\n",
" <td>164.125</td>\n",
" <td>0.011719</td>\n",
" <td>-0.428223</td>\n",
" <td>0.095398</td>\n",
" <td>4.0</td>\n",
" <td>0.095520</td>\n",
" <td>0.834473</td>\n",
" <td>1.411133</td>\n",
" <td>-0.990723</td>\n",
" <td>-0.748535</td>\n",
" <td>0.399902</td>\n",
" <td>0.133301</td>\n",
" <td>0.500000</td>\n",
" <td>1.205078</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>6.0</td>\n",
" <td>3.0</td>\n",
" <td>5.0</td>\n",
" <td>2.177734</td>\n",
" <td>0.010201</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.176514</td>\n",
" <td>0.981934</td>\n",
" <td>0.076111</td>\n",
" <td>2.0</td>\n",
" <td>0.327881</td>\n",
" <td>0.668457</td>\n",
" <td>-2.291016</td>\n",
" <td>-0.301514</td>\n",
" <td>-0.083557</td>\n",
" <td>-0.099976</td>\n",
" <td>0.000000</td>\n",
" <td>0.5</td>\n",
" <td>1.283203</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.189453</td>\n",
" <td>0.025513</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.082153</td>\n",
" <td>1.374023</td>\n",
" <td>0.295410</td>\n",
" <td>2.0</td>\n",
" <td>0.672852</td>\n",
" <td>0.624512</td>\n",
" <td>1.369141</td>\n",
" <td>-0.972168</td>\n",
" <td>-0.842773</td>\n",
" <td>0.428467</td>\n",
" <td>0.142822</td>\n",
" <td>1.0</td>\n",
" <td>1.140625</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.046295</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.235718</td>\n",
" <td>2.0</td>\n",
" <td>0.672852</td>\n",
" <td>0.643555</td>\n",
" <td>1.667969</td>\n",
" <td>-0.190552</td>\n",
" <td>-0.355713</td>\n",
" <td>-0.428467</td>\n",
" <td>0.285645</td>\n",
" <td>0.500000</td>\n",
" <td>0.986816</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>56</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.433838</td>\n",
" <td>-0.900879</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>0.012695</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3308</th>\n",
" <td>2022-02-22</td>\n",
" <td>JPM</td>\n",
" <td>147.000</td>\n",
" <td>151.875</td>\n",
" <td>153.250</td>\n",
" <td>150.375</td>\n",
" <td>150.625</td>\n",
" <td>11333500.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>139.625</td>\n",
" <td>154.750</td>\n",
" <td>169.750</td>\n",
" <td>142.750</td>\n",
" <td>147.625</td>\n",
" <td>152.375</td>\n",
" <td>6.484375</td>\n",
" <td>0.225342</td>\n",
" <td>156.750</td>\n",
" <td>-3.431641</td>\n",
" <td>-2.289062</td>\n",
" <td>-1.142578</td>\n",
" <td>153.75</td>\n",
" <td>0.450684</td>\n",
" <td>-0.265381</td>\n",
" <td>154.125</td>\n",
" <td>153.250</td>\n",
" <td>153.750</td>\n",
" <td>150.750</td>\n",
" <td>0.364502</td>\n",
" <td>0.795410</td>\n",
" <td>151.125</td>\n",
" <td>150.375</td>\n",
" <td>150.625</td>\n",
" <td>154.250</td>\n",
" <td>1.253906</td>\n",
" <td>1.495117</td>\n",
" <td>156.125</td>\n",
" <td>153.250</td>\n",
" <td>153.875</td>\n",
" <td>151.500</td>\n",
" <td>1.531250</td>\n",
" <td>1.781250</td>\n",
" <td>153.750</td>\n",
" <td>150.375</td>\n",
" <td>150.875</td>\n",
" <td>154.500</td>\n",
" <td>1.233398</td>\n",
" <td>0.746582</td>\n",
" <td>156.125</td>\n",
" <td>153.250</td>\n",
" <td>153.875</td>\n",
" <td>151.625</td>\n",
" <td>1.657227</td>\n",
" <td>0.851562</td>\n",
" <td>153.875</td>\n",
" <td>150.375</td>\n",
" <td>150.875</td>\n",
" <td>155.500</td>\n",
" <td>2.193359</td>\n",
" <td>0.677246</td>\n",
" <td>159.000</td>\n",
" <td>153.250</td>\n",
" <td>155.000</td>\n",
" <td>152.250</td>\n",
" <td>1.888672</td>\n",
" <td>0.347900</td>\n",
" <td>155.250</td>\n",
" <td>150.375</td>\n",
" <td>152.000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.034668</td>\n",
" <td>0.070435</td>\n",
" <td>2.0</td>\n",
" <td>0.293457</td>\n",
" <td>0.981445</td>\n",
" <td>-1.008789</td>\n",
" <td>0.337891</td>\n",
" <td>0.094055</td>\n",
" <td>-0.533203</td>\n",
" <td>0.133301</td>\n",
" <td>0.199951</td>\n",
" <td>1.151367</td>\n",
" <td>1.0</td>\n",
" <td>0.931152</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>2.091797</td>\n",
" <td>0.040009</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.284424</td>\n",
" <td>0.981934</td>\n",
" <td>0.094604</td>\n",
" <td>1.0</td>\n",
" <td>0.262695</td>\n",
" <td>0.486328</td>\n",
" <td>-0.307373</td>\n",
" <td>0.137939</td>\n",
" <td>0.397949</td>\n",
" <td>-0.033325</td>\n",
" <td>0.233276</td>\n",
" <td>1.0</td>\n",
" <td>1.345703</td>\n",
" <td>1.0</td>\n",
" <td>0.896484</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.156250</td>\n",
" <td>0.004360</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.032135</td>\n",
" <td>1.963867</td>\n",
" <td>0.282959</td>\n",
" <td>2.0</td>\n",
" <td>1.054688</td>\n",
" <td>0.510742</td>\n",
" <td>1.448242</td>\n",
" <td>0.000479</td>\n",
" <td>-0.021149</td>\n",
" <td>-0.142822</td>\n",
" <td>0.428467</td>\n",
" <td>1.0</td>\n",
" <td>1.635742</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.055542</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.180176</td>\n",
" <td>3.0</td>\n",
" <td>0.568359</td>\n",
" <td>0.670898</td>\n",
" <td>-0.875977</td>\n",
" <td>0.073120</td>\n",
" <td>-0.094604</td>\n",
" <td>0.285645</td>\n",
" <td>0.000000</td>\n",
" <td>0.500000</td>\n",
" <td>1.530273</td>\n",
" <td>4.0</td>\n",
" <td>0.833496</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>53</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.781738</td>\n",
" <td>0.623535</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>-0.001465</td>\n",
" <td>-0.023438</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3309</th>\n",
" <td>2022-02-23</td>\n",
" <td>JPM</td>\n",
" <td>144.000</td>\n",
" <td>148.750</td>\n",
" <td>153.250</td>\n",
" <td>148.000</td>\n",
" <td>153.125</td>\n",
" <td>11799000.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>139.625</td>\n",
" <td>154.750</td>\n",
" <td>169.750</td>\n",
" <td>143.625</td>\n",
" <td>146.625</td>\n",
" <td>149.625</td>\n",
" <td>4.152344</td>\n",
" <td>0.483643</td>\n",
" <td>154.625</td>\n",
" <td>-3.802734</td>\n",
" <td>-2.128906</td>\n",
" <td>-1.674805</td>\n",
" <td>153.50</td>\n",
" <td>0.503418</td>\n",
" <td>1.704102</td>\n",
" <td>154.125</td>\n",
" <td>153.250</td>\n",
" <td>153.250</td>\n",
" <td>149.875</td>\n",
" <td>1.656250</td>\n",
" <td>-1.371094</td>\n",
" <td>151.125</td>\n",
" <td>148.000</td>\n",
" <td>150.375</td>\n",
" <td>153.625</td>\n",
" <td>0.419434</td>\n",
" <td>0.740723</td>\n",
" <td>154.125</td>\n",
" <td>153.250</td>\n",
" <td>153.500</td>\n",
" <td>150.000</td>\n",
" <td>1.415039</td>\n",
" <td>-1.732422</td>\n",
" <td>151.125</td>\n",
" <td>148.000</td>\n",
" <td>150.500</td>\n",
" <td>154.375</td>\n",
" <td>1.291016</td>\n",
" <td>0.717773</td>\n",
" <td>156.125</td>\n",
" <td>153.250</td>\n",
" <td>153.875</td>\n",
" <td>151.250</td>\n",
" <td>2.224609</td>\n",
" <td>-0.174316</td>\n",
" <td>153.875</td>\n",
" <td>148.000</td>\n",
" <td>150.875</td>\n",
" <td>154.750</td>\n",
" <td>1.772461</td>\n",
" <td>1.135742</td>\n",
" <td>158.250</td>\n",
" <td>153.250</td>\n",
" <td>153.875</td>\n",
" <td>151.375</td>\n",
" <td>2.015625</td>\n",
" <td>-0.234863</td>\n",
" <td>153.875</td>\n",
" <td>148.000</td>\n",
" <td>150.875</td>\n",
" <td>-0.023438</td>\n",
" <td>0.040253</td>\n",
" <td>0.069885</td>\n",
" <td>2.0</td>\n",
" <td>0.233643</td>\n",
" <td>0.983398</td>\n",
" <td>-1.033203</td>\n",
" <td>0.362061</td>\n",
" <td>0.116333</td>\n",
" <td>-0.600098</td>\n",
" <td>0.166626</td>\n",
" <td>0.199951</td>\n",
" <td>1.161133</td>\n",
" <td>1.0</td>\n",
" <td>0.931152</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>2.062500</td>\n",
" <td>0.040009</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.287598</td>\n",
" <td>0.981934</td>\n",
" <td>0.123474</td>\n",
" <td>1.0</td>\n",
" <td>0.236328</td>\n",
" <td>0.486328</td>\n",
" <td>-0.307129</td>\n",
" <td>0.140259</td>\n",
" <td>0.400146</td>\n",
" <td>-0.099976</td>\n",
" <td>0.166626</td>\n",
" <td>1.0</td>\n",
" <td>1.344727</td>\n",
" <td>1.0</td>\n",
" <td>0.896484</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.156250</td>\n",
" <td>0.004360</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.032562</td>\n",
" <td>1.963867</td>\n",
" <td>0.281250</td>\n",
" <td>2.0</td>\n",
" <td>1.054688</td>\n",
" <td>0.519043</td>\n",
" <td>1.475586</td>\n",
" <td>-0.026718</td>\n",
" <td>-0.048309</td>\n",
" <td>-0.428467</td>\n",
" <td>0.285645</td>\n",
" <td>1.0</td>\n",
" <td>1.232422</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.046295</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.255859</td>\n",
" <td>2.0</td>\n",
" <td>0.568359</td>\n",
" <td>0.622070</td>\n",
" <td>-0.454590</td>\n",
" <td>0.304443</td>\n",
" <td>0.142944</td>\n",
" <td>-0.142822</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.875488</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.027771</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>54</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.975098</td>\n",
" <td>-0.222534</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>-0.020508</td>\n",
" <td>-0.027344</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3310</th>\n",
" <td>2022-02-24</td>\n",
" <td>JPM</td>\n",
" <td>139.875</td>\n",
" <td>144.500</td>\n",
" <td>145.000</td>\n",
" <td>139.750</td>\n",
" <td>143.000</td>\n",
" <td>25655100.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>139.625</td>\n",
" <td>154.750</td>\n",
" <td>169.750</td>\n",
" <td>143.875</td>\n",
" <td>146.375</td>\n",
" <td>148.875</td>\n",
" <td>3.402344</td>\n",
" <td>0.799316</td>\n",
" <td>152.750</td>\n",
" <td>-3.941406</td>\n",
" <td>-1.812500</td>\n",
" <td>-2.128906</td>\n",
" <td>150.50</td>\n",
" <td>4.781250</td>\n",
" <td>-1.731445</td>\n",
" <td>153.250</td>\n",
" <td>145.000</td>\n",
" <td>153.250</td>\n",
" <td>146.000</td>\n",
" <td>5.566406</td>\n",
" <td>-1.365234</td>\n",
" <td>150.375</td>\n",
" <td>139.750</td>\n",
" <td>148.000</td>\n",
" <td>151.375</td>\n",
" <td>4.304688</td>\n",
" <td>-1.944336</td>\n",
" <td>154.125</td>\n",
" <td>145.000</td>\n",
" <td>153.250</td>\n",
" <td>147.375</td>\n",
" <td>5.207031</td>\n",
" <td>-1.625000</td>\n",
" <td>151.125</td>\n",
" <td>139.750</td>\n",
" <td>149.250</td>\n",
" <td>152.625</td>\n",
" <td>3.865234</td>\n",
" <td>-2.017578</td>\n",
" <td>156.125</td>\n",
" <td>145.000</td>\n",
" <td>153.500</td>\n",
" <td>149.000</td>\n",
" <td>4.855469</td>\n",
" <td>-1.687500</td>\n",
" <td>153.750</td>\n",
" <td>139.750</td>\n",
" <td>150.500</td>\n",
" <td>153.125</td>\n",
" <td>3.478516</td>\n",
" <td>-2.226562</td>\n",
" <td>156.125</td>\n",
" <td>145.000</td>\n",
" <td>153.750</td>\n",
" <td>149.750</td>\n",
" <td>4.453125</td>\n",
" <td>-1.840820</td>\n",
" <td>153.875</td>\n",
" <td>139.750</td>\n",
" <td>150.500</td>\n",
" <td>-0.027344</td>\n",
" <td>0.776855</td>\n",
" <td>0.129761</td>\n",
" <td>2.0</td>\n",
" <td>0.196411</td>\n",
" <td>0.959961</td>\n",
" <td>-1.028320</td>\n",
" <td>0.154663</td>\n",
" <td>0.154663</td>\n",
" <td>-0.683105</td>\n",
" <td>0.099976</td>\n",
" <td>0.500000</td>\n",
" <td>1.153320</td>\n",
" <td>1.0</td>\n",
" <td>0.965332</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>2.062500</td>\n",
" <td>0.020401</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.280029</td>\n",
" <td>0.981934</td>\n",
" <td>0.099670</td>\n",
" <td>1.0</td>\n",
" <td>0.217773</td>\n",
" <td>0.485352</td>\n",
" <td>-0.307129</td>\n",
" <td>0.129883</td>\n",
" <td>0.389893</td>\n",
" <td>-0.133301</td>\n",
" <td>0.183350</td>\n",
" <td>1.0</td>\n",
" <td>1.344727</td>\n",
" <td>1.0</td>\n",
" <td>0.931152</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.156250</td>\n",
" <td>0.004360</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.035736</td>\n",
" <td>1.963867</td>\n",
" <td>0.284180</td>\n",
" <td>2.0</td>\n",
" <td>0.777832</td>\n",
" <td>0.509766</td>\n",
" <td>0.633301</td>\n",
" <td>-1.191406</td>\n",
" <td>-0.234131</td>\n",
" <td>0.571289</td>\n",
" <td>0.000000</td>\n",
" <td>1.0</td>\n",
" <td>1.116211</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.330078</td>\n",
" <td>0.083313</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.283447</td>\n",
" <td>2.0</td>\n",
" <td>0.500488</td>\n",
" <td>0.617676</td>\n",
" <td>-0.444824</td>\n",
" <td>0.292969</td>\n",
" <td>0.132202</td>\n",
" <td>-0.428467</td>\n",
" <td>0.285645</td>\n",
" <td>1.000000</td>\n",
" <td>0.955078</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.027771</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>55</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.433838</td>\n",
" <td>-0.900879</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>-0.028809</td>\n",
" <td>0.023438</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3311</th>\n",
" <td>2022-02-25</td>\n",
" <td>JPM</td>\n",
" <td>143.250</td>\n",
" <td>148.000</td>\n",
" <td>150.125</td>\n",
" <td>144.875</td>\n",
" <td>145.250</td>\n",
" <td>18367700.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>139.625</td>\n",
" <td>154.750</td>\n",
" <td>169.750</td>\n",
" <td>143.750</td>\n",
" <td>146.000</td>\n",
" <td>148.250</td>\n",
" <td>3.095703</td>\n",
" <td>0.356689</td>\n",
" <td>150.375</td>\n",
" <td>-4.210938</td>\n",
" <td>-1.666992</td>\n",
" <td>-2.544922</td>\n",
" <td>149.50</td>\n",
" <td>4.195312</td>\n",
" <td>-0.687500</td>\n",
" <td>153.250</td>\n",
" <td>145.000</td>\n",
" <td>150.125</td>\n",
" <td>144.250</td>\n",
" <td>4.136719</td>\n",
" <td>-0.729492</td>\n",
" <td>148.000</td>\n",
" <td>139.750</td>\n",
" <td>144.875</td>\n",
" <td>150.375</td>\n",
" <td>3.908203</td>\n",
" <td>-1.263672</td>\n",
" <td>153.250</td>\n",
" <td>145.000</td>\n",
" <td>151.625</td>\n",
" <td>145.750</td>\n",
" <td>4.582031</td>\n",
" <td>-0.724609</td>\n",
" <td>150.375</td>\n",
" <td>139.750</td>\n",
" <td>146.500</td>\n",
" <td>151.625</td>\n",
" <td>3.533203</td>\n",
" <td>-1.730469</td>\n",
" <td>154.125</td>\n",
" <td>145.000</td>\n",
" <td>153.250</td>\n",
" <td>147.500</td>\n",
" <td>4.433594</td>\n",
" <td>-1.263672</td>\n",
" <td>151.125</td>\n",
" <td>139.750</td>\n",
" <td>149.250</td>\n",
" <td>152.750</td>\n",
" <td>3.623047</td>\n",
" <td>-1.587891</td>\n",
" <td>156.125</td>\n",
" <td>145.000</td>\n",
" <td>153.500</td>\n",
" <td>149.000</td>\n",
" <td>4.753906</td>\n",
" <td>-1.140625</td>\n",
" <td>153.875</td>\n",
" <td>139.750</td>\n",
" <td>150.500</td>\n",
" <td>0.023438</td>\n",
" <td>-0.334229</td>\n",
" <td>0.135376</td>\n",
" <td>2.0</td>\n",
" <td>0.219849</td>\n",
" <td>0.984863</td>\n",
" <td>-0.951172</td>\n",
" <td>-0.033569</td>\n",
" <td>0.202271</td>\n",
" <td>-0.733398</td>\n",
" <td>0.033325</td>\n",
" <td>0.500000</td>\n",
" <td>0.924805</td>\n",
" <td>1.0</td>\n",
" <td>0.965332</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>6.0</td>\n",
" <td>2.091797</td>\n",
" <td>0.015305</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.299072</td>\n",
" <td>0.981934</td>\n",
" <td>0.092590</td>\n",
" <td>1.0</td>\n",
" <td>0.233398</td>\n",
" <td>0.503906</td>\n",
" <td>-0.016632</td>\n",
" <td>0.047058</td>\n",
" <td>0.289307</td>\n",
" <td>-0.099976</td>\n",
" <td>0.199951</td>\n",
" <td>1.0</td>\n",
" <td>1.196289</td>\n",
" <td>1.0</td>\n",
" <td>0.931152</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>2.144531</td>\n",
" <td>0.005550</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.078064</td>\n",
" <td>1.767578</td>\n",
" <td>0.238647</td>\n",
" <td>2.0</td>\n",
" <td>0.291016</td>\n",
" <td>0.691895</td>\n",
" <td>-0.146240</td>\n",
" <td>-0.082703</td>\n",
" <td>-0.212891</td>\n",
" <td>0.714355</td>\n",
" <td>-0.285645</td>\n",
" <td>0.5</td>\n",
" <td>0.857910</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.330078</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.210205</td>\n",
" <td>2.0</td>\n",
" <td>0.050537</td>\n",
" <td>0.656250</td>\n",
" <td>1.441406</td>\n",
" <td>-0.074280</td>\n",
" <td>0.094360</td>\n",
" <td>-0.428467</td>\n",
" <td>0.428467</td>\n",
" <td>1.000000</td>\n",
" <td>0.978516</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>56</td>\n",
" <td>8</td>\n",
" <td>0.866211</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.433838</td>\n",
" <td>-0.900879</td>\n",
" <td>0.8125</td>\n",
" <td>0.583008</td>\n",
" <td>0.024414</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4964</th>\n",
" <td>2022-02-22</td>\n",
" <td>MSFT</td>\n",
" <td>285.000</td>\n",
" <td>287.750</td>\n",
" <td>291.500</td>\n",
" <td>284.500</td>\n",
" <td>285.000</td>\n",
" <td>41736100.0</td>\n",
" <td>2019-03-31</td>\n",
" <td>310.000</td>\n",
" <td>327.250</td>\n",
" <td>344.250</td>\n",
" <td>304.250</td>\n",
" <td>321.500</td>\n",
" <td>338.750</td>\n",
" <td>10.726562</td>\n",
" <td>0.280518</td>\n",
" <td>331.000</td>\n",
" <td>-2.666016</td>\n",
" <td>-2.703125</td>\n",
" <td>0.036133</td>\n",
" <td>294.00</td>\n",
" <td>2.636719</td>\n",
" <td>0.350586</td>\n",
" <td>296.750</td>\n",
" <td>291.500</td>\n",
" <td>293.750</td>\n",
" <td>287.000</td>\n",
" <td>2.802734</td>\n",
" <td>0.955566</td>\n",
" <td>290.000</td>\n",
" <td>284.500</td>\n",
" <td>286.250</td>\n",
" <td>295.750</td>\n",
" <td>4.027344</td>\n",
" <td>0.525879</td>\n",
" <td>300.750</td>\n",
" <td>291.500</td>\n",
" <td>295.250</td>\n",
" <td>288.500</td>\n",
" <td>4.074219</td>\n",
" <td>0.488037</td>\n",
" <td>293.750</td>\n",
" <td>284.500</td>\n",
" <td>288.250</td>\n",
" <td>296.750</td>\n",
" <td>3.710938</td>\n",
" <td>-0.197632</td>\n",
" <td>300.750</td>\n",
" <td>291.500</td>\n",
" <td>296.750</td>\n",
" <td>290.500</td>\n",
" <td>4.628906</td>\n",
" <td>0.083923</td>\n",
" <td>297.000</td>\n",
" <td>284.500</td>\n",
" <td>290.750</td>\n",
" <td>299.250</td>\n",
" <td>5.714844</td>\n",
" <td>0.458496</td>\n",
" <td>309.000</td>\n",
" <td>291.500</td>\n",
" <td>298.750</td>\n",
" <td>292.250</td>\n",
" <td>5.363281</td>\n",
" <td>0.064087</td>\n",
" <td>300.750</td>\n",
" <td>284.500</td>\n",
" <td>292.500</td>\n",
" <td>0.000000</td>\n",
" <td>0.197266</td>\n",
" <td>0.177734</td>\n",
" <td>1.0</td>\n",
" <td>0.343018</td>\n",
" <td>0.500000</td>\n",
" <td>0.134155</td>\n",
" <td>0.301270</td>\n",
" <td>0.482422</td>\n",
" <td>0.266602</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.262695</td>\n",
" <td>1.0</td>\n",
" <td>0.965332</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>5.0</td>\n",
" <td>2.156250</td>\n",
" <td>0.004360</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.067871</td>\n",
" <td>2.355469</td>\n",
" <td>0.133545</td>\n",
" <td>1.0</td>\n",
" <td>0.216187</td>\n",
" <td>0.500977</td>\n",
" <td>-0.451416</td>\n",
" <td>-0.677734</td>\n",
" <td>-0.466797</td>\n",
" <td>-0.066650</td>\n",
" <td>-0.266602</td>\n",
" <td>1.0</td>\n",
" <td>1.119141</td>\n",
" <td>1.0</td>\n",
" <td>0.965332</td>\n",
" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>2.042969</td>\n",
" <td>0.017441</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.067932</td>\n",
" <td>2.160156</td>\n",
" <td>0.423828</td>\n",
" <td>2.0</td>\n",
" <td>1.054688</td>\n",
" <td>0.847168</td>\n",
" <td>-0.048431</td>\n",
" <td>-0.919922</td>\n",
" <td>-0.786133</td>\n",
" <td>-0.428467</td>\n",
" <td>0.142822</td>\n",
" <td>1.0</td>\n",
" <td>1.638672</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.560547</td>\n",
" <td>0.074097</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>0.267822</td>\n",
" <td>1.0</td>\n",
" <td>0.672852</td>\n",
" <td>0.559082</td>\n",
" <td>-1.511719</td>\n",
" <td>0.275879</td>\n",
" <td>0.119019</td>\n",
" <td>-0.142822</td>\n",
" <td>0.428467</td>\n",
" <td>1.000000</td>\n",
" <td>1.281250</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.791992</td>\n",
" <td>0.018524</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.570312</td>\n",
" <td>2022</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</t
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