Code Snippet Demo.ipynb

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   "source": [
    "#Importing all dependencies\n",
    "import pandas as pd\n",
    "import numpy as np \n",
    "import os\n",
    "import math\n",
    "import itertools\n",
    "import json\n",
    "import time\n",
    "import datetime\n",
    "import requests\n",
    "from datetime import date, timedelta, datetime, time\n",
    "from calendar import monthrange"
   ]
  },
  {
   "cell_type": "code",
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  {
   "cell_type": "code",
   "execution_count": 101,
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   "source": [
    "#Ignore for now\n",
    "\n",
    "#https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/2021-03-24.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Ignore for now\n",
    "\n",
    "#df_shortsqueeze = pd.read_csv('https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/2021-03-24.csv')\n",
    "#df_shortsqueeze"
   ]
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  {
   "cell_type": "code",
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   "source": [
    "#S&P 500 Analysis using Quicksight\n",
    "#The S&P 500 Index contains 500 stocks/tickers/companies/symbols \n",
    "# Each day we process daily and minute data of these symbols"
   ]
  },
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   "cell_type": "code",
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   "source": [
    "# Raw Data comes in the form of daily data and minute e.g. 20210701_d.csv and 20210701_m.csv \n",
    "# Whereby the file name gives the data and d for daily and m for minute\n",
    "# Each csv contains initial data that comprises mainly Open, High, Low, Close Volume and other\n",
    "# Raw Daily Data comes from TDAmeritrade API \n",
    "# Raw Minute Data comes from Quandl API\n",
    "# Other data will come from financialmodelingprep, shortsqueeze, bloomberg \n",
    "# financialmodelingprep api provides all the profile data and others\n",
    "# shortsqueeze provides proprietary additional data calculated by shortsqueeze \n",
    "# bloomberg provides missing data we could not obtain from the above sources"
   ]
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  {
   "cell_type": "code",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>companyName</th>\n",
       "      <th>cik</th>\n",
       "      <th>industry</th>\n",
       "      <th>sector</th>\n",
       "      <th>exchangeShortName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MMM</td>\n",
       "      <td>3M Company</td>\n",
       "      <td>0000066740</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>Industrials</td>\n",
       "      <td>NYSE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "  symbol companyName         cik       industry       sector exchangeShortName\n",
       "0    MMM  3M Company  0000066740  Conglomerates  Industrials              NYSE"
      ]
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   "source": [
    "# An example of Profile data, this will makes sense in a little while\n",
    "\n",
    "url = \"https://financialmodelingprep.com/api/v3/profile/MMM?apikey=aa8b4631b2ad1b2704741d1a2d6a2611\"\n",
    "\n",
    "response = requests.get(url)\n",
    "data = response.json()\n",
    "df_MMM_profile_all_data = pd.DataFrame(data)\n",
    "df_MMM_profile = df_MMM_profile_all_data[[\"symbol\",\"companyName\",\"cik\",\"industry\",\"sector\",\"exchangeShortName\"]]\n",
    "df_MMM_profile\n",
    "\n",
    "#Note the cik number is unique to the company, even if the symbol changes or the name the cik will stay"
   ]
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   "cell_type": "code",
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    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticker</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>147.01</td>\n",
       "      <td>147.760</td>\n",
       "      <td>146.21</td>\n",
       "      <td>147.28</td>\n",
       "      <td>8445127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AA</td>\n",
       "      <td>36.95</td>\n",
       "      <td>37.110</td>\n",
       "      <td>35.78</td>\n",
       "      <td>35.80</td>\n",
       "      <td>32496825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAL</td>\n",
       "      <td>22.33</td>\n",
       "      <td>22.480</td>\n",
       "      <td>22.07</td>\n",
       "      <td>22.22</td>\n",
       "      <td>18738629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAP</td>\n",
       "      <td>202.17</td>\n",
       "      <td>205.460</td>\n",
       "      <td>202.00</td>\n",
       "      <td>204.43</td>\n",
       "      <td>675038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>133.46</td>\n",
       "      <td>133.890</td>\n",
       "      <td>132.81</td>\n",
       "      <td>133.11</td>\n",
       "      <td>70783746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>598</th>\n",
       "      <td>YUM</td>\n",
       "      <td>116.70</td>\n",
       "      <td>117.660</td>\n",
       "      <td>116.52</td>\n",
       "      <td>117.25</td>\n",
       "      <td>5229898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>599</th>\n",
       "      <td>ZBH</td>\n",
       "      <td>164.53</td>\n",
       "      <td>167.590</td>\n",
       "      <td>164.53</td>\n",
       "      <td>165.85</td>\n",
       "      <td>1072442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>ZBRA</td>\n",
       "      <td>513.17</td>\n",
       "      <td>514.595</td>\n",
       "      <td>506.47</td>\n",
       "      <td>510.65</td>\n",
       "      <td>251391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601</th>\n",
       "      <td>ZION</td>\n",
       "      <td>54.24</td>\n",
       "      <td>55.840</td>\n",
       "      <td>53.98</td>\n",
       "      <td>55.48</td>\n",
       "      <td>2221351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>602</th>\n",
       "      <td>ZTS</td>\n",
       "      <td>185.50</td>\n",
       "      <td>187.290</td>\n",
       "      <td>184.50</td>\n",
       "      <td>187.23</td>\n",
       "      <td>1994898</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>603 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Ticker    open     high     low   close    volume\n",
       "0        A  147.01  147.760  146.21  147.28   8445127\n",
       "1       AA   36.95   37.110   35.78   35.80  32496825\n",
       "2      AAL   22.33   22.480   22.07   22.22  18738629\n",
       "3      AAP  202.17  205.460  202.00  204.43    675038\n",
       "4     AAPL  133.46  133.890  132.81  133.11  70783746\n",
       "..     ...     ...      ...     ...     ...       ...\n",
       "598    YUM  116.70  117.660  116.52  117.25   5229898\n",
       "599    ZBH  164.53  167.590  164.53  165.85   1072442\n",
       "600   ZBRA  513.17  514.595  506.47  510.65    251391\n",
       "601   ZION   54.24   55.840   53.98   55.48   2221351\n",
       "602    ZTS  185.50  187.290  184.50  187.23   1994898\n",
       "\n",
       "[603 rows x 6 columns]"
      ]
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   "source": [
    "# While preparing teh files for this Code Snippet I accidental names daily - m and minute - d \n",
    "# However I will apply the correct letter when naming the dataframe\n",
    "\n",
    "# Example of Raw daily data\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210625_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210628_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210629_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210630_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210701_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210702_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210706_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210707_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210708_d.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210709_d.csv\n",
    "\n",
    "#Dataframe of 20210625_m.csv == df_20210625_d\n",
    "df_20210625_d = pd.read_csv('https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210625_m.csv')\n",
    "df_20210625_d\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Ticker</th>\n",
       "      <th>OpenPrice</th>\n",
       "      <th>HighPrice</th>\n",
       "      <th>LowPrice</th>\n",
       "      <th>ClosePrice</th>\n",
       "      <th>TotalVolume</th>\n",
       "      <th>TotalQuantity</th>\n",
       "      <th>TotalTradeCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20210625</td>\n",
       "      <td>04:28:00</td>\n",
       "      <td>MS</td>\n",
       "      <td>87.53</td>\n",
       "      <td>87.53</td>\n",
       "      <td>87.53</td>\n",
       "      <td>87.53</td>\n",
       "      <td>1.750600e+04</td>\n",
       "      <td>200</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20210625</td>\n",
       "      <td>04:43:00</td>\n",
       "      <td>MS</td>\n",
       "      <td>87.54</td>\n",
       "      <td>87.54</td>\n",
       "      <td>87.54</td>\n",
       "      <td>87.54</td>\n",
       "      <td>8.754000e+03</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20210625</td>\n",
       "      <td>06:40:00</td>\n",
       "      <td>MS</td>\n",
       "      <td>87.60</td>\n",
       "      <td>87.60</td>\n",
       "      <td>87.60</td>\n",
       "      <td>87.60</td>\n",
       "      <td>9.636000e+04</td>\n",
       "      <td>1100</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20210625</td>\n",
       "      <td>07:00:00</td>\n",
       "      <td>MS</td>\n",
       "      <td>87.49</td>\n",
       "      <td>87.50</td>\n",
       "      <td>87.49</td>\n",
       "      <td>87.50</td>\n",
       "      <td>5.092400e+04</td>\n",
       "      <td>582</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20210625</td>\n",
       "      <td>07:01:00</td>\n",
       "      <td>MS</td>\n",
       "      <td>87.68</td>\n",
       "      <td>87.76</td>\n",
       "      <td>87.68</td>\n",
       "      <td>87.76</td>\n",
       "      <td>6.036128e+04</td>\n",
       "      <td>688</td>\n",
       "      <td>3</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180465</th>\n",
       "      <td>20210625</td>\n",
       "      <td>16:04:00</td>\n",
       "      <td>BLK</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>8.431767e+06</td>\n",
       "      <td>9647</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180466</th>\n",
       "      <td>20210625</td>\n",
       "      <td>16:05:00</td>\n",
       "      <td>BLK</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>9.614330e+05</td>\n",
       "      <td>1100</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180467</th>\n",
       "      <td>20210625</td>\n",
       "      <td>16:11:00</td>\n",
       "      <td>BLK</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>4.676060e+05</td>\n",
       "      <td>535</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180468</th>\n",
       "      <td>20210625</td>\n",
       "      <td>16:41:00</td>\n",
       "      <td>BLK</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>1.076272e+08</td>\n",
       "      <td>123139</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180469</th>\n",
       "      <td>20210625</td>\n",
       "      <td>17:33:00</td>\n",
       "      <td>BLK</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>874.03</td>\n",
       "      <td>1.960449e+06</td>\n",
       "      <td>2243</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>180470 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date Timestamp Ticker  OpenPrice  HighPrice  LowPrice  ClosePrice  \\\n",
       "0       20210625  04:28:00     MS      87.53      87.53     87.53       87.53   \n",
       "1       20210625  04:43:00     MS      87.54      87.54     87.54       87.54   \n",
       "2       20210625  06:40:00     MS      87.60      87.60     87.60       87.60   \n",
       "3       20210625  07:00:00     MS      87.49      87.50     87.49       87.50   \n",
       "4       20210625  07:01:00     MS      87.68      87.76     87.68       87.76   \n",
       "...          ...       ...    ...        ...        ...       ...         ...   \n",
       "180465  20210625  16:04:00    BLK     874.03     874.03    874.03      874.03   \n",
       "180466  20210625  16:05:00    BLK     874.03     874.03    874.03      874.03   \n",
       "180467  20210625  16:11:00    BLK     874.03     874.03    874.03      874.03   \n",
       "180468  20210625  16:41:00    BLK     874.03     874.03    874.03      874.03   \n",
       "180469  20210625  17:33:00    BLK     874.03     874.03    874.03      874.03   \n",
       "\n",
       "         TotalVolume  TotalQuantity  TotalTradeCount  \n",
       "0       1.750600e+04            200                2  \n",
       "1       8.754000e+03            100                1  \n",
       "2       9.636000e+04           1100                2  \n",
       "3       5.092400e+04            582                3  \n",
       "4       6.036128e+04            688                3  \n",
       "...              ...            ...              ...  \n",
       "180465  8.431767e+06           9647                3  \n",
       "180466  9.614330e+05           1100                3  \n",
       "180467  4.676060e+05            535                1  \n",
       "180468  1.076272e+08         123139                1  \n",
       "180469  1.960449e+06           2243                1  \n",
       "\n",
       "[180470 rows x 10 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example of Raw daily data\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210625_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210628_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210629_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210630_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210701_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210702_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210706_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210707_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210708_m.csv\n",
    "# https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210709_m.csv\n",
    "\n",
    "# Dataframe of 20210625_d.csv == df_20210625_m\n",
    "# This is for one day\n",
    "df_20210625_m = pd.read_csv('https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/20210625_d.csv')\n",
    "df_20210625_m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The data is then extracted by symbol and columns renamed keeping all that we need.\n",
    "# A lot of cleaning is done at this stage which involves:\n",
    "# a.) Applying Name symbols when a company is bought or changes a name\n",
    "# e.g. Recently Facebook with the symbol FB changed to Meta with the symbol META.\n",
    "# This means all previous data FB data needs to be re-symboled from FB to META\n",
    "# b.) Applying stock spilts - A company can announce a stock spilt\n",
    "# A stock split is when the price of a company is divided, lets say Facebook FB has a 2 to 1 split applied tomorrow\n",
    "# This means that if the price of Facebook was 100 and volume traded was 15000...\n",
    "#... Tomorrow the 2 to 1 split means Facebook's price is 50 (halved) but the volume is 30000 (doubled)\n",
    "# As a result all previous data needs to be adjusted.\n",
    "# c.) The S&P 500 is a strict index sometimes a company is kicked out and replaced.\n",
    "# This is why our data may have more than 500 stocks, financialmodelingprep api provides the correct list daily.\n",
    "# Stock spilts and Name changes rarely happen but we have a script that checks for a, b and c situations.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We will use MMM in the example below.\n",
    "# MMM is the Symbol for a company listed in the S&P 500, the formal name is called 3M Co\n",
    "#MMM_ALLDATADAILY.csv https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/ALLDAILYDATA.csv\n",
    "\n",
    "# This function is an example of some cleaning. \n",
    "# It takes raw data contain many stocks and allows us to extract the symbol we want.\n",
    "def get_all_data_for_symobol_daily(symbol):\n",
    "    \"\"\"Gets all  daily data for a given ticker\n",
    "    \n",
    "    Arguments : \n",
    "    symbol : what symbol to get data for \n",
    "    \"\"\"\n",
    "    big_df = pd.read_csv(\"https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/ALLDAILYDATA.csv\")\n",
    "    big_df = big_df[big_df['Ticker'] == symbol]  # filtering\n",
    "    big_df = big_df.dropna(how = 'all',subset = ['Date',\"Ticker\"])\n",
    "    big_df.to_csv(f\"{symbol}_ALLDATADAILY.csv\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>Ticker</th>\n",
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       "      <th>low</th>\n",
       "      <th>close</th>\n",
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       "      <th>0</th>\n",
       "      <td>384</td>\n",
       "      <td>384</td>\n",
       "      <td>MMM</td>\n",
       "      <td>86.410</td>\n",
       "      <td>86.900</td>\n",
       "      <td>85.83</td>\n",
       "      <td>86.72</td>\n",
       "      <td>2396791</td>\n",
       "      <td>20101222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1007</td>\n",
       "      <td>374</td>\n",
       "      <td>MMM</td>\n",
       "      <td>70.870</td>\n",
       "      <td>70.990</td>\n",
       "      <td>69.39</td>\n",
       "      <td>69.63</td>\n",
       "      <td>4832600</td>\n",
       "      <td>20080728</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1635</td>\n",
       "      <td>381</td>\n",
       "      <td>MMM</td>\n",
       "      <td>79.880</td>\n",
       "      <td>80.590</td>\n",
       "      <td>78.93</td>\n",
       "      <td>79.02</td>\n",
       "      <td>4022482</td>\n",
       "      <td>20111031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2263</td>\n",
       "      <td>379</td>\n",
       "      <td>MMM</td>\n",
       "      <td>178.120</td>\n",
       "      <td>178.850</td>\n",
       "      <td>177.85</td>\n",
       "      <td>178.82</td>\n",
       "      <td>1226260</td>\n",
       "      <td>20160810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2846</td>\n",
       "      <td>332</td>\n",
       "      <td>MMM</td>\n",
       "      <td>53.275</td>\n",
       "      <td>54.445</td>\n",
       "      <td>53.01</td>\n",
       "      <td>54.35</td>\n",
       "      <td>3485800</td>\n",
       "      <td>20011025</td>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>5945</th>\n",
       "      <td>3562502</td>\n",
       "      <td>379</td>\n",
       "      <td>MMM</td>\n",
       "      <td>178.370</td>\n",
       "      <td>178.900</td>\n",
       "      <td>177.94</td>\n",
       "      <td>178.39</td>\n",
       "      <td>1098851</td>\n",
       "      <td>20160809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5946</th>\n",
       "      <td>3563128</td>\n",
       "      <td>375</td>\n",
       "      <td>MMM</td>\n",
       "      <td>70.840</td>\n",
       "      <td>71.250</td>\n",
       "      <td>70.29</td>\n",
       "      <td>70.39</td>\n",
       "      <td>4254180</td>\n",
       "      <td>20080731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5947</th>\n",
       "      <td>3563756</td>\n",
       "      <td>381</td>\n",
       "      <td>MMM</td>\n",
       "      <td>81.530</td>\n",
       "      <td>81.840</td>\n",
       "      <td>80.50</td>\n",
       "      <td>81.00</td>\n",
       "      <td>5252021</td>\n",
       "      <td>20111028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5948</th>\n",
       "      <td>3564389</td>\n",
       "      <td>385</td>\n",
       "      <td>MMM</td>\n",
       "      <td>139.500</td>\n",
       "      <td>141.490</td>\n",
       "      <td>139.12</td>\n",
       "      <td>140.81</td>\n",
       "      <td>3997985</td>\n",
       "      <td>20140501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5949</th>\n",
       "      <td>3565022</td>\n",
       "      <td>376</td>\n",
       "      <td>MMM</td>\n",
       "      <td>56.820</td>\n",
       "      <td>56.990</td>\n",
       "      <td>55.99</td>\n",
       "      <td>56.07</td>\n",
       "      <td>3773900</td>\n",
       "      <td>20090522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5950 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1 Ticker     open     high     low   close  \\\n",
       "0            384           384    MMM   86.410   86.900   85.83   86.72   \n",
       "1           1007           374    MMM   70.870   70.990   69.39   69.63   \n",
       "2           1635           381    MMM   79.880   80.590   78.93   79.02   \n",
       "3           2263           379    MMM  178.120  178.850  177.85  178.82   \n",
       "4           2846           332    MMM   53.275   54.445   53.01   54.35   \n",
       "...          ...           ...    ...      ...      ...     ...     ...   \n",
       "5945     3562502           379    MMM  178.370  178.900  177.94  178.39   \n",
       "5946     3563128           375    MMM   70.840   71.250   70.29   70.39   \n",
       "5947     3563756           381    MMM   81.530   81.840   80.50   81.00   \n",
       "5948     3564389           385    MMM  139.500  141.490  139.12  140.81   \n",
       "5949     3565022           376    MMM   56.820   56.990   55.99   56.07   \n",
       "\n",
       "       volume      Date  \n",
       "0     2396791  20101222  \n",
       "1     4832600  20080728  \n",
       "2     4022482  20111031  \n",
       "3     1226260  20160810  \n",
       "4     3485800  20011025  \n",
       "...       ...       ...  \n",
       "5945  1098851  20160809  \n",
       "5946  4254180  20080731  \n",
       "5947  5252021  20111028  \n",
       "5948  3997985  20140501  \n",
       "5949  3773900  20090522  \n",
       "\n",
       "[5950 rows x 9 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting MMM daily data\n",
    "get_all_data_for_symobol_daily(\"MMM\")\n",
    "\n",
    "#Dataframe of MMM_ALLDATADAILY.csv == df_MMM_d after applying get_data_presentation_type_1 function\n",
    "df_MMM_d = pd.read_csv('MMM_ALLDATADAILY.csv')\n",
    "df_MMM_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <td>47725</td>\n",
       "      <td>20210709</td>\n",
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       "      <td>MMM</td>\n",
       "      <td>198.98</td>\n",
       "      <td>198.98</td>\n",
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       "      <td>20210709</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.25</td>\n",
       "      <td>199.90</td>\n",
       "      <td>199.25</td>\n",
       "      <td>199.82</td>\n",
       "      <td>1400854.69</td>\n",
       "      <td>7015</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>47727</td>\n",
       "      <td>47727</td>\n",
       "      <td>20210709</td>\n",
       "      <td>09:32:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.51</td>\n",
       "      <td>199.90</td>\n",
       "      <td>199.35</td>\n",
       "      <td>199.69</td>\n",
       "      <td>829554.45</td>\n",
       "      <td>4156</td>\n",
       "      <td>34</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47728</td>\n",
       "      <td>47728</td>\n",
       "      <td>20210709</td>\n",
       "      <td>09:33:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.84</td>\n",
       "      <td>199.90</td>\n",
       "      <td>199.56</td>\n",
       "      <td>199.89</td>\n",
       "      <td>1652102.89</td>\n",
       "      <td>8274</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>47729</td>\n",
       "      <td>47729</td>\n",
       "      <td>20210709</td>\n",
       "      <td>09:34:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.91</td>\n",
       "      <td>200.17</td>\n",
       "      <td>199.75</td>\n",
       "      <td>200.16</td>\n",
       "      <td>1580288.29</td>\n",
       "      <td>7901</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>25173</th>\n",
       "      <td>11443755</td>\n",
       "      <td>86793</td>\n",
       "      <td>20210412</td>\n",
       "      <td>16:39:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.47</td>\n",
       "      <td>197.50</td>\n",
       "      <td>197.47</td>\n",
       "      <td>197.50</td>\n",
       "      <td>122246.50</td>\n",
       "      <td>619</td>\n",
       "      <td>6</td>\n",
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       "      <th>25174</th>\n",
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       "      <td>86794</td>\n",
       "      <td>20210412</td>\n",
       "      <td>16:40:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>79060.00</td>\n",
       "      <td>400</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>25175</th>\n",
       "      <td>11443757</td>\n",
       "      <td>86795</td>\n",
       "      <td>20210412</td>\n",
       "      <td>16:55:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>19765.00</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25176</th>\n",
       "      <td>11443758</td>\n",
       "      <td>86796</td>\n",
       "      <td>20210412</td>\n",
       "      <td>18:07:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>197.65</td>\n",
       "      <td>73921.10</td>\n",
       "      <td>374</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>25177</th>\n",
       "      <td>11443759</td>\n",
       "      <td>86797</td>\n",
       "      <td>20210412</td>\n",
       "      <td>19:58:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.41</td>\n",
       "      <td>197.41</td>\n",
       "      <td>197.41</td>\n",
       "      <td>197.41</td>\n",
       "      <td>19741.00</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25178 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0  Unnamed: 0.1      Date Timestamp Ticker  OpenPrice  \\\n",
       "0           47725         47725  20210709  08:31:00    MMM     198.98   \n",
       "1           47726         47726  20210709  09:31:00    MMM     199.25   \n",
       "2           47727         47727  20210709  09:32:00    MMM     199.51   \n",
       "3           47728         47728  20210709  09:33:00    MMM     199.84   \n",
       "4           47729         47729  20210709  09:34:00    MMM     199.91   \n",
       "...           ...           ...       ...       ...    ...        ...   \n",
       "25173    11443755         86793  20210412  16:39:00    MMM     197.47   \n",
       "25174    11443756         86794  20210412  16:40:00    MMM     197.65   \n",
       "25175    11443757         86795  20210412  16:55:00    MMM     197.65   \n",
       "25176    11443758         86796  20210412  18:07:00    MMM     197.65   \n",
       "25177    11443759         86797  20210412  19:58:00    MMM     197.41   \n",
       "\n",
       "       HighPrice  LowPrice  ClosePrice  TotalVolume  TotalQuantity  \\\n",
       "0         198.98    198.98      198.98     19898.00            100   \n",
       "1         199.90    199.25      199.82   1400854.69           7015   \n",
       "2         199.90    199.35      199.69    829554.45           4156   \n",
       "3         199.90    199.56      199.89   1652102.89           8274   \n",
       "4         200.17    199.75      200.16   1580288.29           7901   \n",
       "...          ...       ...         ...          ...            ...   \n",
       "25173     197.50    197.47      197.50    122246.50            619   \n",
       "25174     197.65    197.65      197.65     79060.00            400   \n",
       "25175     197.65    197.65      197.65     19765.00            100   \n",
       "25176     197.65    197.65      197.65     73921.10            374   \n",
       "25177     197.41    197.41      197.41     19741.00            100   \n",
       "\n",
       "       TotalTradeCount  \n",
       "0                    1  \n",
       "1                   48  \n",
       "2                   34  \n",
       "3                   20  \n",
       "4                   37  \n",
       "...                ...  \n",
       "25173                6  \n",
       "25174                2  \n",
       "25175                1  \n",
       "25176                2  \n",
       "25177                1  \n",
       "\n",
       "[25178 rows x 12 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Dataframe of MMM_ALLDATADAILY.csv == df_MMM_m after applying get_data_presentation_type_1 function\n",
    "df_MMM_m = pd.read_csv('https://0-source-principal-administrative.s3.amazonaws.com/0-public-data/MMM_ALLDATAMINUTE.csv')\n",
    "df_MMM_m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Because the data is ordered from oldest to newest we call this Type_1 data. newest to oldest would be Type_2 data\n",
    "#Type_1 data is the format we will use to apply all the indicators e.g. Moving averages.\n",
    "\n",
    "def get_data_presentation_type_1(data,ascending = True):\n",
    "\t\"\"\"Convert the DataFrame into type1(order by Symbol then Date then Timestamp)\n",
    "\tIf ascending is passed as False automatically converts to type 2 instead \n",
    "\n",
    "\tArgs:\n",
    "\tdata :The data to convert\"\"\"\n",
    "\tif \"Timestamp\" in data.columns : \n",
    "\t\t\tdata[\"Time\"] = data['Timestamp']\n",
    "\t\t\tdel data['Timestamp']\n",
    "\t\t\tdata['Symbol'] = data['Ticker']\n",
    "\t\t\tdel data['Ticker']\n",
    "\t\t\tdata['Symbol'] = data.Symbol.astype(str).str.upper()\n",
    "\t\t\tdata['Open'] = data['OpenPrice']\n",
    "\t\t\tdel data['OpenPrice']\n",
    "\t\t\tdata['Close'] = data['ClosePrice']\n",
    "\t\t\tdel data['ClosePrice']\n",
    "\t\t\tdata['High'] = data['HighPrice']\n",
    "\t\t\tdel data['HighPrice']\n",
    "\t\t\tdata['Low'] = data['LowPrice']\n",
    "\t\t\tdel data['LowPrice']\n",
    "\t\t\tdata['Volume'] = data['TotalVolume']\n",
    "\t\t\tdel data['TotalVolume']\n",
    "\t\t\tdata = data.sort_values(by = ['Symbol',\"Date\",\"Time\"], ascending= ascending)\n",
    "\n",
    "\telse : \n",
    "\t\t\tdata['Symbol'] = data['Ticker']\n",
    "\t\t\tdel data['Ticker']\n",
    "\t\t\tdata['Symbol'] = data.Symbol.astype(str).str.upper()\n",
    "\t\t\tdata['Open'] = data['open']\n",
    "\t\t\tdel data['open']\n",
    "\t\t\tdata['Close'] = data['close']\n",
    "\t\t\tdel data['close']\n",
    "\t\t\tdata['High'] = data['high']\n",
    "\t\t\tdel data['high']\n",
    "\t\t\tdata['Low'] = data['low']\n",
    "\t\t\tdel data['low']\n",
    "\t\t\tdata['Volume'] = data['volume']\n",
    "\t\t\tdel data['volume']\n",
    "\t\t\tdata = data.sort_values(by = ['Symbol',\"Date\"],ascending = ascending)\t\n",
    "\n",
    "\treturn data \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Converting df_MMM_d amd df_MMM_m to type_1 data\n",
    "df_MMM_m_type_1 = get_data_presentation_type_1(df_MMM_m,ascending = True)\n",
    "df_MMM_d_type_1 = get_data_presentation_type_1(df_MMM_d,ascending = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>Date</th>\n",
       "      <th>TotalQuantity</th>\n",
       "      <th>TotalTradeCount</th>\n",
       "      <th>Time</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24774</th>\n",
       "      <td>11443356</td>\n",
       "      <td>86394</td>\n",
       "      <td>20210412</td>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "      <td>04:42:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>39600.00</td>\n",
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       "    <tr>\n",
       "      <th>24775</th>\n",
       "      <td>11443357</td>\n",
       "      <td>86395</td>\n",
       "      <td>20210412</td>\n",
       "      <td>200</td>\n",
       "      <td>2</td>\n",
       "      <td>06:14:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>39600.00</td>\n",
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       "    <tr>\n",
       "      <th>24776</th>\n",
       "      <td>11443358</td>\n",
       "      <td>86396</td>\n",
       "      <td>20210412</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>08:44:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.87</td>\n",
       "      <td>197.87</td>\n",
       "      <td>197.87</td>\n",
       "      <td>197.87</td>\n",
       "      <td>19787.00</td>\n",
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       "    <tr>\n",
       "      <th>24777</th>\n",
       "      <td>11443359</td>\n",
       "      <td>86397</td>\n",
       "      <td>20210412</td>\n",
       "      <td>126</td>\n",
       "      <td>1</td>\n",
       "      <td>08:56:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.70</td>\n",
       "      <td>198.70</td>\n",
       "      <td>198.70</td>\n",
       "      <td>198.70</td>\n",
       "      <td>25036.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24778</th>\n",
       "      <td>11443360</td>\n",
       "      <td>86398</td>\n",
       "      <td>20210412</td>\n",
       "      <td>12547</td>\n",
       "      <td>56</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.25</td>\n",
       "      <td>197.63</td>\n",
       "      <td>198.34</td>\n",
       "      <td>197.54</td>\n",
       "      <td>2485331.41</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>48114</td>\n",
       "      <td>48114</td>\n",
       "      <td>20210709</td>\n",
       "      <td>14470</td>\n",
       "      <td>108</td>\n",
       "      <td>15:59:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.11</td>\n",
       "      <td>200.99</td>\n",
       "      <td>2909039.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>48115</td>\n",
       "      <td>48115</td>\n",
       "      <td>20210709</td>\n",
       "      <td>24579</td>\n",
       "      <td>175</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.02</td>\n",
       "      <td>200.98</td>\n",
       "      <td>201.08</td>\n",
       "      <td>200.95</td>\n",
       "      <td>4940895.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>48116</td>\n",
       "      <td>48116</td>\n",
       "      <td>20210709</td>\n",
       "      <td>345187</td>\n",
       "      <td>26</td>\n",
       "      <td>16:04:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>69382587.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>48117</td>\n",
       "      <td>48117</td>\n",
       "      <td>20210709</td>\n",
       "      <td>133</td>\n",
       "      <td>1</td>\n",
       "      <td>16:59:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>26733.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>48118</td>\n",
       "      <td>48118</td>\n",
       "      <td>20210709</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>17:09:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>20100.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25178 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0  Unnamed: 0.1      Date  TotalQuantity  TotalTradeCount  \\\n",
       "24774    11443356         86394  20210412            200                1   \n",
       "24775    11443357         86395  20210412            200                2   \n",
       "24776    11443358         86396  20210412            100                1   \n",
       "24777    11443359         86397  20210412            126                1   \n",
       "24778    11443360         86398  20210412          12547               56   \n",
       "...           ...           ...       ...            ...              ...   \n",
       "389         48114         48114  20210709          14470              108   \n",
       "390         48115         48115  20210709          24579              175   \n",
       "391         48116         48116  20210709         345187               26   \n",
       "392         48117         48117  20210709            133                1   \n",
       "393         48118         48118  20210709            100                1   \n",
       "\n",
       "           Time Symbol    Open   Close    High     Low       Volume  \n",
       "24774  04:42:00    MMM  198.00  198.00  198.00  198.00     39600.00  \n",
       "24775  06:14:00    MMM  198.00  198.00  198.00  198.00     39600.00  \n",
       "24776  08:44:00    MMM  197.87  197.87  197.87  197.87     19787.00  \n",
       "24777  08:56:00    MMM  198.70  198.70  198.70  198.70     25036.20  \n",
       "24778  09:31:00    MMM  198.25  197.63  198.34  197.54   2485331.41  \n",
       "...         ...    ...     ...     ...     ...     ...          ...  \n",
       "389    15:59:00    MMM  201.11  201.04  201.11  200.99   2909039.61  \n",
       "390    16:00:00    MMM  201.02  200.98  201.08  200.95   4940895.48  \n",
       "391    16:04:00    MMM  201.00  201.00  201.00  201.00  69382587.00  \n",
       "392    16:59:00    MMM  201.00  201.00  201.00  201.00     26733.00  \n",
       "393    17:09:00    MMM  201.00  201.00  201.00  201.00     20100.00  \n",
       "\n",
       "[25178 rows x 12 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Showing df_MMM_m_type_1\n",
    "df_MMM_m_type_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Date</th>\n",
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       "      <th>4439</th>\n",
       "      <td>2661673</td>\n",
       "      <td>289</td>\n",
       "      <td>19980102</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>41.8125</td>\n",
       "      <td>40.87500</td>\n",
       "      <td>2573000</td>\n",
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       "      <th>5523</th>\n",
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       "      <td>MMM</td>\n",
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       "      <td>42.6250</td>\n",
       "      <td>41.34375</td>\n",
       "      <td>2505600</td>\n",
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       "      <th>5907</th>\n",
       "      <td>3539823</td>\n",
       "      <td>289</td>\n",
       "      <td>19980106</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>41.81250</td>\n",
       "      <td>42.8750</td>\n",
       "      <td>41.50000</td>\n",
       "      <td>3620200</td>\n",
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       "    <tr>\n",
       "      <th>5603</th>\n",
       "      <td>3357216</td>\n",
       "      <td>289</td>\n",
       "      <td>19980107</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.90625</td>\n",
       "      <td>42.15625</td>\n",
       "      <td>42.3125</td>\n",
       "      <td>41.37500</td>\n",
       "      <td>2494800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>257054</td>\n",
       "      <td>289</td>\n",
       "      <td>19980108</td>\n",
       "      <td>MMM</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>41.65625</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>41.12500</td>\n",
       "      <td>1951400</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>45370</td>\n",
       "      <td>364</td>\n",
       "      <td>20210817</td>\n",
       "      <td>MMM</td>\n",
       "      <td>202.00000</td>\n",
       "      <td>199.55000</td>\n",
       "      <td>202.0000</td>\n",
       "      <td>197.60000</td>\n",
       "      <td>2287954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5245</th>\n",
       "      <td>3144218</td>\n",
       "      <td>364</td>\n",
       "      <td>20210818</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.57000</td>\n",
       "      <td>196.51000</td>\n",
       "      <td>198.8100</td>\n",
       "      <td>196.31000</td>\n",
       "      <td>2116228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5502</th>\n",
       "      <td>3297044</td>\n",
       "      <td>364</td>\n",
       "      <td>20210819</td>\n",
       "      <td>MMM</td>\n",
       "      <td>195.00000</td>\n",
       "      <td>195.36000</td>\n",
       "      <td>196.2300</td>\n",
       "      <td>194.30700</td>\n",
       "      <td>2312780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5118</th>\n",
       "      <td>3068265</td>\n",
       "      <td>364</td>\n",
       "      <td>20210820</td>\n",
       "      <td>MMM</td>\n",
       "      <td>194.34000</td>\n",
       "      <td>194.16000</td>\n",
       "      <td>195.1300</td>\n",
       "      <td>193.36500</td>\n",
       "      <td>2397425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4725</th>\n",
       "      <td>2832836</td>\n",
       "      <td>364</td>\n",
       "      <td>20210823</td>\n",
       "      <td>MMM</td>\n",
       "      <td>195.00000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>196.2400</td>\n",
       "      <td>193.68000</td>\n",
       "      <td>1974289</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5950 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1      Date Symbol       Open      Close  \\\n",
       "4439     2661673           289  19980102    MMM   41.09375   41.75000   \n",
       "5523     3309465           289  19980105    MMM   41.50000   41.68750   \n",
       "5907     3539823           289  19980106    MMM   41.62500   41.81250   \n",
       "5603     3357216           289  19980107    MMM   41.90625   42.15625   \n",
       "431       257054           289  19980108    MMM   42.00000   41.65625   \n",
       "...          ...           ...       ...    ...        ...        ...   \n",
       "76         45370           364  20210817    MMM  202.00000  199.55000   \n",
       "5245     3144218           364  20210818    MMM  198.57000  196.51000   \n",
       "5502     3297044           364  20210819    MMM  195.00000  195.36000   \n",
       "5118     3068265           364  20210820    MMM  194.34000  194.16000   \n",
       "4725     2832836           364  20210823    MMM  195.00000  194.68000   \n",
       "\n",
       "          High        Low   Volume  \n",
       "4439   41.8125   40.87500  2573000  \n",
       "5523   42.6250   41.34375  2505600  \n",
       "5907   42.8750   41.50000  3620200  \n",
       "5603   42.3125   41.37500  2494800  \n",
       "431    42.0000   41.12500  1951400  \n",
       "...        ...        ...      ...  \n",
       "76    202.0000  197.60000  2287954  \n",
       "5245  198.8100  196.31000  2116228  \n",
       "5502  196.2300  194.30700  2312780  \n",
       "5118  195.1300  193.36500  2397425  \n",
       "4725  196.2400  193.68000  1974289  \n",
       "\n",
       "[5950 rows x 9 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Showing df_MMM_d_type_1\n",
    "df_MMM_d_type_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A good practice that will later be implimented is to have all columns in lower case\n",
    "# The current type_1 data does not by this will help when writing new code and consistency.\n",
    "# Another good practice is to have all data rounded off to 2 decimal places."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let us remove columns we do not want\n",
    "# For Minute Data\n",
    "df_MMM_m_type_1.drop(['Unnamed: 0'], axis=1, inplace=True)\n",
    "df_MMM_m_type_1.drop(['Unnamed: 0.1'], axis=1, inplace=True)\n",
    "df_MMM_m_type_1.drop(['TotalQuantity'], axis=1, inplace=True)\n",
    "df_MMM_m_type_1.drop(['TotalTradeCount'], axis=1, inplace=True)\n",
    "\n",
    "# For Daily Data\n",
    "df_MMM_d_type_1.drop(['Unnamed: 0'], axis=1, inplace=True)\n",
    "df_MMM_d_type_1.drop(['Unnamed: 0.1'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let us now take stock of the column types, \n",
    "# this is important because indicator code is written in a way that respects these types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date        int64\n",
       "Symbol     object\n",
       "Open      float64\n",
       "Close     float64\n",
       "High      float64\n",
       "Low       float64\n",
       "Volume      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_MMM_d_type_1.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date        int64\n",
       "Time       object\n",
       "Symbol     object\n",
       "Open      float64\n",
       "Close     float64\n",
       "High      float64\n",
       "Low       float64\n",
       "Volume    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_MMM_m_type_1.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now that our data is clean we will create different timeframes.\n",
    "# All data is derived from minute data and the standard time frames are as follows:\n",
    "# 1 min, 5 min, 15 min, 30 min, 409 mins, 1 hour, 4 hours, \n",
    "# 1 day or daily, 2 day, 1 week, monthly, quaterly, yearly, 5 years and 10 years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import date, timedelta, datetime\n",
    "from dateutil.parser import parse\n",
    " \t \n",
    "def get_start_end_only_data_custom(data,start_date_, end_date_=None):\n",
    "\t\"\"\"Gets all data between two given dates \n",
    "\n",
    "\tArgs: \n",
    "\tdata :What data to perform the calculations on \n",
    "\tstart_date : The start date for the data \n",
    "\tend_date : the end date for the data\"\"\"\n",
    "\tif start_date_:\n",
    "\t\tstart_date = datetime(start_date_.year,start_date_.month,start_date_.day)\n",
    "\tif end_date_:\n",
    "\t\tend_date = \tdatetime(end_date_.year,end_date_.month,end_date_.day)\n",
    "\tif \"Time\" not in data.columns : \n",
    "\t\tDate =list(data.Date)\n",
    "\t\tdate = []\n",
    "\t\tfor _ in Date: \n",
    "\t\t\t_ = str(_)\n",
    "\t\t\tdate.append(f'{_[:4]}-{_[4:6]}-{_[6:]}')\n",
    "\t\ttry :\n",
    "\t\t\tdata.Date  = pd.to_datetime(date) \n",
    "\t\texcept: \n",
    "\t\t\tpass\n",
    "\t\tif end_date :\n",
    "\t\t\tmask = (data['Date'] >= start_date) & (data['Date'] <= end_date)\n",
    "\t\telse: \n",
    "\t\t\tmask = (data['Date'] >= start_date)\n",
    "\t\treturn data.loc[mask]\n",
    "\telse: \n",
    "\t\ttry : \n",
    "\t\t\tdata.Time = data.Time.map(lambda x: datetime.strptime(x,\"%H:%M:%S\").time())\n",
    "\t\texcept: pass\n",
    "\t\tDate =list(data.Date)\n",
    "\t\tstart_time  = start_date_.time()\n",
    "\t\tdate = []\n",
    "\t\tfor _ in Date: \n",
    "\t\t\t_ = str(_)\n",
    "\t\t\tdate.append(f'{_[:4]}-{_[4:6]}-{_[6:]}')\n",
    "\t\ttry: \n",
    "\t\t\tdata.Date  = pd.to_datetime(date) \n",
    "\t\texcept:pass\n",
    "\t\tif end_date :\n",
    "\t\t\tend_time  = end_date_.time()\n",
    "\t\t\tmask = (data['Date'] >= start_date) & (data['Date'] <= end_date ) &( data['Time'] >= start_time) & (data['Time'] <  end_time)\n",
    "\t\telse: \n",
    "\t\t\tmask = (data['Date'] >= start_date) & ( data['Time'] >= start_time)\n",
    "\t\treturn data.loc[mask]\n",
    "    \n",
    "def get_time_with_given_interval(date,interval,last_hour=None,last_minute=None):\n",
    "\t\"\"\"Gets time from 9:00:00 to 16:00:00 with given interval\"\"\"\n",
    "\n",
    "\tdate  = parse(str(date))\n",
    "\tstart_time =  datetime(date.year,date.month,date.day,9,30)\n",
    "\tif  last_hour==None : \n",
    "\t\tend_time  =datetime(date.year,date.month,date.day,16)\n",
    "\telse :\n",
    "\t\tend_time  =datetime(date.year,date.month,date.day,16,last_hour,last_minute)\n",
    "\tlist_of_times = []\n",
    "\twhile start_time!=end_time :\n",
    "\t\tlist_of_times.append([start_time,start_time+ timedelta(minutes = interval)])\n",
    "\t\tstart_time  = start_time+ timedelta(minutes = interval)\n",
    "\t\tif start_time <=end_time :\n",
    "\t\t\tcontinue\n",
    "\t\telse: \n",
    "\t\t\tbreak\n",
    "\treturn list_of_times\n",
    "\n",
    "def getconvert_minuteto_traditional  (data, convert_type,  trading_hours_criteria,last_hour= None,last_minute= None):\n",
    "\t\"\"\"Converts minute data to 5 minute , 15 minute , 30 minute , 1 hour , 2 hour and 5 hour data type \n",
    "\n",
    "\tArguments : \n",
    "\tdata : data to work with\n",
    "\tconvert_type : what type to convert to \n",
    "\ttrading_hours_criteria : wether to work within trading hours or with all data\"\"\"\n",
    "\n",
    "\tdataframe_final ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Time\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t\"TotalQuantity\":[],\n",
    "\t\t\"TotalTradeCount\":[]\n",
    "\t\t}\n",
    "\tif trading_hours_criteria == False :\n",
    "\n",
    "\t\tsymbols = data.Symbol.unique()\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tsymbol_df = data[data['Symbol'] == symbol]\n",
    "\t\t\tdates = symbol_df.Date.unique()\n",
    "\t\t\tfor date in dates : \n",
    "\t\t\t\tdate_symbol_df = symbol_df[symbol_df['Date'] == date]\n",
    "\t\t\t\tfor step in range( convert_type,len(date_symbol_df),  convert_type):\n",
    "\t\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-convert_type:step]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(None)\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\t\tif remaining != 0 : \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final[\"TotalrTfivadeCount\"].append(None)\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\telif trading_hours_criteria== True :\n",
    "\t\tdata.Time =data.Time.astype(str)\n",
    "\t\tif last_hour ==None : \n",
    "\t\t\tdata = data[data['Time'] >= \"09:30:00\" ]\n",
    "\t\t\tdata = data[data['Time'] <= \"16:00:00\"]\n",
    "\t\telse:\n",
    "\t\t\tif len(str(last_minute))==1 :\n",
    "\t\t\t\tlast_minute_ = \"0\"+str(last_minute)\n",
    "\t\t\tdata = data[data['Time'] >= \"09:30:00\" ]\n",
    "\t\t\tdata = data[data['Time'] <= f\"{last_hour}:{last_minute_}:00\"]\t\t\t\n",
    "\t\tsymbols = data.Symbol.unique()\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tsymbol_df = data[data['Symbol'] == symbol]\n",
    "\t\t\tdates = symbol_df.Date.unique()\n",
    "\t\t\tfor date in dates : \n",
    "\n",
    "\t\t\t\tdate_symbol_df = symbol_df[symbol_df['Date'] == date]\n",
    "\t\t\t\tlist_of_times_= get_time_with_given_interval(date,convert_type,last_hour,last_minute)\n",
    "\t\t\t\tfor time in list_of_times_:\n",
    "\t\t\t\t\tcurrent_dataframe = get_start_end_only_data_custom(date_symbol_df,time[0],time[1])\n",
    "\t\t\t\t\ttry:\n",
    "\t\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\t\telse : \n",
    "\t\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\t\telse : \n",
    "\t\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(None)\n",
    "\t\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\t\t\texcept:\n",
    "\t\t\t\t\t\tpass\t\n",
    "\n",
    "    #convert to dataframe\n",
    "\tdf_minute = pd.DataFrame(dataframe_final)\n",
    "\treturn df_minute\n",
    "    \n",
    "def getconvert_minuteto_mathametical (data, convert_type,  trading_hours_criteria):\n",
    "\t\"\"\"Converts minute data to 5 minute , 15 minute , 30 minute , 1 hour , 2 hour and 5 hour data type \n",
    "\t\n",
    "\tArguments : \n",
    "\tdata : data to work with\n",
    "\tconvert_type : what type to convert to \n",
    "\ttrading_hours_criteria : wether to work within trading hours or with all data\"\"\"\n",
    "\n",
    "\tdataframe_final ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Time\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t\"TotalQuantity\":[],\n",
    "\t\t\"TotalTradeCount\":[]\n",
    "\t\t}\n",
    "\tif trading_hours_criteria == False :\n",
    "\n",
    "\t\tsymbols = data.Symbol.unique()\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tsymbol_df = data[data['Symbol'] == symbol]\n",
    "\t\t\tdates = symbol_df.Date.unique()\n",
    "\t\t\tfor date in dates : \n",
    "\t\t\t\tdate_symbol_df = symbol_df[symbol_df['Date'] == date]\n",
    "\t\t\t\tfor step in range( convert_type,len(date_symbol_df),  convert_type):\n",
    "\t\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-convert_type:step]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(None)\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\t\tif remaining != 0 : \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(None)\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\telif trading_hours_criteria== True :\n",
    "\t\tdata.Time =data.Time.astype(str)\n",
    "\t\tdata = data[data['Time'] >= \"09:30:00\" ]\n",
    "\t\tdata = data[data['Time'] <= \"16:00:00\"]\n",
    "\t\tsymbols = data.Symbol.unique()\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tsymbol_df = data[data['Symbol'] == symbol]\n",
    "\t\t\tdates = symbol_df.Date.unique()\n",
    "\t\t\tfor date in dates : \n",
    "\t\t\t\tdate_symbol_df = symbol_df[symbol_df['Date'] == date]\n",
    "\t\t\t\tfor step in range( convert_type,len(date_symbol_df),  convert_type):\n",
    "\t\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-convert_type:step]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(None)\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\t\tif remaining != 0 : \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Time'].append(current_dataframe['Time'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tif \"TotalQuantity\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalQuantity\"].append(sum(current_dataframe['TotalQuantity']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final['TotalQuantity'].append(None)\n",
    "\t\t\t\t\tif \"TotalTradeCount\" in current_dataframe.columns : \n",
    "\n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(sum(current_dataframe['TotalTradeCount']))\n",
    "\t\t\t\t\telse : \n",
    "\t\t\t\t\t\tdataframe_final[\"TotalTradeCount\"].append(None)\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "    #convert to dataframe\n",
    "\tdf_minute = pd.DataFrame(dataframe_final)\n",
    "\treturn df_minute\n",
    "\n",
    "    \n",
    "def getconvert_dailyto_mathamtical(data,amount):\n",
    "\t\"\"\"Converts daily data to different types of data\n",
    "\tArguments : \n",
    " \tdata : data to work with\n",
    "\tamount : what frequencey to work with \"\"\"\n",
    "\t\n",
    "\tyear = []\n",
    "\tmonth = []\n",
    "\tweek = []\n",
    "\tday = []\n",
    "\tdataframe_final ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t}\n",
    "\tfor date in data.Date:\n",
    "\t\tdate = str(date)\n",
    "\t\tdate_time_obj = datetime.strptime(date, '%Y%m%d')\n",
    "\t\tweek.append(date_time_obj.date().isocalendar()[1])\n",
    "\t\tmonth.append(date_time_obj.month)\n",
    "\t\tyear.append(date_time_obj.year)\n",
    "\t\tday.append(date_time_obj.isoweekday())\n",
    "\tdata['Month'] = month\n",
    "\tdata[\"Year\"] = year\n",
    "\tdata['Week'] = week\n",
    "\tdata[\"Day\"]  = day\n",
    "\tsymbols = data.Symbol.unique()\n",
    "\tfor symbol in symbols : \n",
    "\t\t\tdate_symbol_df = data[data['Symbol'] == symbol]\n",
    "\t\t\tfor step in range( amount,len(date_symbol_df),  amount): \n",
    "\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-amount:step]\n",
    "\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\tif remaining != 0 : \n",
    "\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "    #convert to dataframe\n",
    "\tdf_daily = pd.DataFrame(dataframe_final)\n",
    "\treturn df_daily\n",
    "    \n",
    "def getconvert_dailyto_traditional(data,amount,convert_type):\n",
    "\t\"\"\"Converts daily data to \"\"Daily\" \"Weekly\" \"Monthly\" \"Yearly\"\n",
    "\tArguments : \n",
    " \tdata : data to work with\n",
    "\tamount : what frequencey to work with\n",
    "\tconvert_type : what type to convert to  \"\"\"\n",
    "\tyear = []\n",
    "\tmonth = []\n",
    "\tweek = []\n",
    "\tdataframe_final ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t}\n",
    "\tfor date in data.Date:\n",
    "\t\tdate = str(date)\n",
    "\t\tdate_time_obj = datetime.strptime(date, '%Y%m%d')\n",
    "\t\tweek.append(date_time_obj.date().isocalendar()[1])\n",
    "\t\tmonth.append(date_time_obj.month)\n",
    "\t\tyear.append(date_time_obj.year)\n",
    "\tdata['Month'] = month\n",
    "\tdata[\"Year\"] = year\n",
    "\tdata['Week'] = week\n",
    "\n",
    "\tsymbols = data.Symbol.unique()\n",
    "\tif convert_type == \"Daily\": \n",
    "\t\tdataframe_final = pd.DataFrame(getconvert_dailyto_mathamtical(data,amount))\n",
    "\telif convert_type == \"Weekly\":\n",
    "\t\tdataframe_weekly ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t}\n",
    "\t\tfor current_symbol in symbols :\n",
    "\t\t\tsymbol_data = data[data[\"Symbol\"]== current_symbol]\n",
    "\t\t\tyears_we_have = symbol_data.Year.unique()\n",
    "\t\t\tfor year in years_we_have : \n",
    "\t\t\t\tdata_for_current_year = symbol_data[symbol_data[\"Year\"] == year]\n",
    "\t\t\t\tweeks_for_current_year = data_for_current_year.Week.unique()\n",
    "\t\t\t\tfor week in weeks_for_current_year : \n",
    "\t\t\t\t\tdata_for_current_week_for_current_year = data_for_current_year[data_for_current_year['Week'] == week]\n",
    "\t\t\t\t\tdata_for_current_week_for_current_year = data_for_current_week_for_current_year.sort_values([\"Date\"],ascending = True)\n",
    "\t\t\t\t\tdataframe_weekly['Date'].append(data_for_current_week_for_current_year['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_weekly['Open'].append(data_for_current_week_for_current_year['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_weekly['Close'].append(data_for_current_week_for_current_year['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_weekly[\"High\"].append(max(data_for_current_week_for_current_year['High']))\n",
    "\t\t\t\t\tdataframe_weekly[\"Low\"].append(min(data_for_current_week_for_current_year['Low']))\n",
    "\t\t\t\t\tdataframe_weekly[\"Volume\"].append(sum(data_for_current_week_for_current_year['Volume']))\n",
    "\t\t\t\t\tdataframe_weekly['Symbol'].append(data_for_current_week_for_current_year['Symbol'].iloc[0])\n",
    "\t\tdataframe_weekly = pd.DataFrame(dataframe_weekly)\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tdate_symbol_df = dataframe_weekly[dataframe_weekly['Symbol'] == symbol]\n",
    "\t\t\tfor step in range( amount,len(date_symbol_df),  amount): \n",
    "\t\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-amount:step]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\tif remaining != 0 : \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\telif convert_type == \"Monthly\":\n",
    "\t\tdataframe_monthly ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t}\n",
    "\t\tfor current_symbol in symbols :\n",
    "\t\t\tsymbol_data = data[data[\"Symbol\"]== current_symbol]\n",
    "\t\t\tyears_we_have = symbol_data.Year.unique()\n",
    "\t\t\tfor year in years_we_have : \n",
    "\t\t\t\tdata_for_current_year = symbol_data[symbol_data[\"Year\"] == year]\n",
    "\t\t\t\tmonths_for_current_year = data_for_current_year.Month.unique()\n",
    "\t\t\t\tfor month in months_for_current_year : \n",
    "\t\t\t\t\tdata_for_current_month_for_current_year = data_for_current_year[data_for_current_year['Month'] == month]\n",
    "\t\t\t\t\tdata_for_current_month_for_current_year = data_for_current_month_for_current_year.sort_values([\"Date\"],ascending = True)\n",
    "\t\t\t\t\tdataframe_monthly['Date'].append(data_for_current_month_for_current_year['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_monthly['Open'].append(data_for_current_month_for_current_year['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_monthly['Close'].append(data_for_current_month_for_current_year['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_monthly[\"High\"].append(max(data_for_current_month_for_current_year['High']))\n",
    "\t\t\t\t\tdataframe_monthly[\"Low\"].append(min(data_for_current_month_for_current_year['Low']))\n",
    "\t\t\t\t\tdataframe_monthly[\"Volume\"].append(sum(data_for_current_month_for_current_year['Volume']))\n",
    "\t\t\t\t\tdataframe_monthly['Symbol'].append(data_for_current_month_for_current_year['Symbol'].iloc[0])\n",
    "\t\tdataframe_monthly = pd.DataFrame(dataframe_monthly)\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tdate_symbol_df = dataframe_monthly[dataframe_monthly['Symbol'] == symbol]\n",
    "\t\t\tfor step in range( amount,len(date_symbol_df),  amount): \n",
    "\t\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-amount:step]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\tif remaining != 0 : \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\telif convert_type == \"Yearly\":\n",
    "\t\tdataframe_Yearly ={\n",
    "\t\t\"Date\":[],\n",
    "\t\t\"Open\":[],\n",
    "\t\t\"Close\":[],\n",
    "\t\t\"High\":[],\n",
    "\t\t\"Low\":[],\n",
    "\t\t\"Volume\":[],\n",
    "\t\t\"Symbol\":[],\n",
    "\t\t}\n",
    "\t\tfor current_symbol in symbols :\n",
    "\t\t\tsymbol_data = data[data[\"Symbol\"]== current_symbol]\n",
    "\t\t\tyears_we_have = symbol_data.Year.unique()\n",
    "\t\t\tfor year in years_we_have : \n",
    "\t\t\t\tdata_for_current_year = symbol_data[symbol_data[\"Year\"] == year]\n",
    "\t\t\t\tdata_for_current_year = data_for_current_year.sort_values([\"Date\"],ascending = True)\n",
    "\t\t\t\tdataframe_Yearly['Date'].append(data_for_current_year['Date'].iloc[0])\n",
    "\t\t\t\tdataframe_Yearly['Open'].append(data_for_current_year['Open'].iloc[0])\n",
    "\t\t\t\tdataframe_Yearly['Close'].append(data_for_current_year['Close'].iloc[-1])\n",
    "\t\t\t\tdataframe_Yearly[\"High\"].append(max(data_for_current_year['High']))\n",
    "\t\t\t\tdataframe_Yearly[\"Low\"].append(min(data_for_current_year['Low']))\n",
    "\t\t\t\tdataframe_Yearly[\"Volume\"].append(sum(data_for_current_year['Volume']))\n",
    "\t\t\t\tdataframe_Yearly['Symbol'].append(data_for_current_year['Symbol'].iloc[0])\n",
    "\t\tdataframe_Yearly = pd.DataFrame(dataframe_Yearly)\n",
    "\t\tfor symbol in symbols : \n",
    "\t\t\tdate_symbol_df = dataframe_Yearly[dataframe_Yearly['Symbol'] == symbol]\n",
    "\t\t\tfor step in range( amount,len(date_symbol_df),  amount): \n",
    "\t\t\t\t\tremaining = len(date_symbol_df)- step \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df.iloc[step-amount:step]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "\t\t\tif remaining != 0 : \n",
    "\t\t\t\t\tcurrent_dataframe = date_symbol_df[len(date_symbol_df)-remaining : ]\n",
    "\t\t\t\t\tdataframe_final['Date'].append(current_dataframe['Date'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Open'].append(current_dataframe['Open'].iloc[0])\n",
    "\t\t\t\t\tdataframe_final['Close'].append(current_dataframe['Close'].iloc[-1])\n",
    "\t\t\t\t\tdataframe_final[\"High\"].append(max(current_dataframe['High']))\n",
    "\t\t\t\t\tdataframe_final[\"Low\"].append(min(current_dataframe['Low']))\n",
    "\t\t\t\t\tdataframe_final[\"Volume\"].append(sum(current_dataframe['Volume']))\n",
    "\t\t\t\t\tdataframe_final['Symbol'].append(current_dataframe['Symbol'].iloc[0])\n",
    "    #convert to dataframe\n",
    "\tdf_daily = pd.DataFrame(dataframe_final)\n",
    "\treturn df_daily"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The timeframe is another stage of cleaning the data.\n",
    "# The Stock market is open Monday to Friday, excluding holidays from 9:30 to 4:00pm EST\n",
    "# There are some exceptions in which it is open half days to 1:00pm EST\n",
    "\n",
    "# So depending on how we want to analyse the data we can trim off data before 9:30am and after 4:00pm\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24774</th>\n",
       "      <td>20210412</td>\n",
       "      <td>04:42:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>39600.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24775</th>\n",
       "      <td>20210412</td>\n",
       "      <td>06:14:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>198.00</td>\n",
       "      <td>39600.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24776</th>\n",
       "      <td>20210412</td>\n",
       "      <td>08:44:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.87</td>\n",
       "      <td>197.87</td>\n",
       "      <td>197.87</td>\n",
       "      <td>197.87</td>\n",
       "      <td>19787.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24777</th>\n",
       "      <td>20210412</td>\n",
       "      <td>08:56:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.70</td>\n",
       "      <td>198.70</td>\n",
       "      <td>198.70</td>\n",
       "      <td>198.70</td>\n",
       "      <td>25036.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24778</th>\n",
       "      <td>20210412</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.25</td>\n",
       "      <td>197.63</td>\n",
       "      <td>198.34</td>\n",
       "      <td>197.54</td>\n",
       "      <td>2485331.41</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>20210709</td>\n",
       "      <td>15:59:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.11</td>\n",
       "      <td>200.99</td>\n",
       "      <td>2909039.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>20210709</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.02</td>\n",
       "      <td>200.98</td>\n",
       "      <td>201.08</td>\n",
       "      <td>200.95</td>\n",
       "      <td>4940895.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>20210709</td>\n",
       "      <td>16:04:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>69382587.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>20210709</td>\n",
       "      <td>16:59:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>26733.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>20210709</td>\n",
       "      <td>17:09:00</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.00</td>\n",
       "      <td>20100.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25178 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date      Time Symbol    Open   Close    High     Low       Volume\n",
       "24774  20210412  04:42:00    MMM  198.00  198.00  198.00  198.00     39600.00\n",
       "24775  20210412  06:14:00    MMM  198.00  198.00  198.00  198.00     39600.00\n",
       "24776  20210412  08:44:00    MMM  197.87  197.87  197.87  197.87     19787.00\n",
       "24777  20210412  08:56:00    MMM  198.70  198.70  198.70  198.70     25036.20\n",
       "24778  20210412  09:31:00    MMM  198.25  197.63  198.34  197.54   2485331.41\n",
       "...         ...       ...    ...     ...     ...     ...     ...          ...\n",
       "389    20210709  15:59:00    MMM  201.11  201.04  201.11  200.99   2909039.61\n",
       "390    20210709  16:00:00    MMM  201.02  200.98  201.08  200.95   4940895.48\n",
       "391    20210709  16:04:00    MMM  201.00  201.00  201.00  201.00  69382587.00\n",
       "392    20210709  16:59:00    MMM  201.00  201.00  201.00  201.00     26733.00\n",
       "393    20210709  17:09:00    MMM  201.00  201.00  201.00  201.00     20100.00\n",
       "\n",
       "[25178 rows x 8 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_MMM_m_type_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>TotalQuantity</th>\n",
       "      <th>TotalTradeCount</th>\n",
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       "      <th>0</th>\n",
       "      <td>20210412</td>\n",
       "      <td>09:31:00</td>\n",
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       "      <td>198.34</td>\n",
       "      <td>197.54</td>\n",
       "      <td>2485331.41</td>\n",
       "      <td>MMM</td>\n",
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       "      <td>198.26</td>\n",
       "      <td>197.70</td>\n",
       "      <td>877144.31</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20210412</td>\n",
       "      <td>09:33:00</td>\n",
       "      <td>198.26</td>\n",
       "      <td>198.14</td>\n",
       "      <td>198.26</td>\n",
       "      <td>198.04</td>\n",
       "      <td>477146.81</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20210412</td>\n",
       "      <td>09:34:00</td>\n",
       "      <td>198.12</td>\n",
       "      <td>197.92</td>\n",
       "      <td>198.15</td>\n",
       "      <td>197.91</td>\n",
       "      <td>297396.62</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20210412</td>\n",
       "      <td>09:35:00</td>\n",
       "      <td>198.02</td>\n",
       "      <td>198.44</td>\n",
       "      <td>198.44</td>\n",
       "      <td>198.01</td>\n",
       "      <td>800694.64</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>24495</th>\n",
       "      <td>20210709</td>\n",
       "      <td>15:56:00</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.07</td>\n",
       "      <td>200.96</td>\n",
       "      <td>2176869.20</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24496</th>\n",
       "      <td>20210709</td>\n",
       "      <td>15:57:00</td>\n",
       "      <td>201.07</td>\n",
       "      <td>201.05</td>\n",
       "      <td>201.10</td>\n",
       "      <td>201.03</td>\n",
       "      <td>2058977.34</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24497</th>\n",
       "      <td>20210709</td>\n",
       "      <td>15:58:00</td>\n",
       "      <td>201.07</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.04</td>\n",
       "      <td>3037745.19</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24498</th>\n",
       "      <td>20210709</td>\n",
       "      <td>15:59:00</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.11</td>\n",
       "      <td>200.99</td>\n",
       "      <td>2909039.61</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24499</th>\n",
       "      <td>20210709</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>201.02</td>\n",
       "      <td>200.98</td>\n",
       "      <td>201.08</td>\n",
       "      <td>200.95</td>\n",
       "      <td>4940895.48</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24500 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date      Time    Open   Close    High     Low      Volume Symbol  \\\n",
       "0      20210412  09:31:00  198.25  197.63  198.34  197.54  2485331.41    MMM   \n",
       "1      20210412  09:32:00  197.70  198.26  198.26  197.70   877144.31    MMM   \n",
       "2      20210412  09:33:00  198.26  198.14  198.26  198.04   477146.81    MMM   \n",
       "3      20210412  09:34:00  198.12  197.92  198.15  197.91   297396.62    MMM   \n",
       "4      20210412  09:35:00  198.02  198.44  198.44  198.01   800694.64    MMM   \n",
       "...         ...       ...     ...     ...     ...     ...         ...    ...   \n",
       "24495  20210709  15:56:00  201.04  201.04  201.07  200.96  2176869.20    MMM   \n",
       "24496  20210709  15:57:00  201.07  201.05  201.10  201.03  2058977.34    MMM   \n",
       "24497  20210709  15:58:00  201.07  201.11  201.11  201.04  3037745.19    MMM   \n",
       "24498  20210709  15:59:00  201.11  201.04  201.11  200.99  2909039.61    MMM   \n",
       "24499  20210709  16:00:00  201.02  200.98  201.08  200.95  4940895.48    MMM   \n",
       "\n",
       "      TotalQuantity TotalTradeCount  \n",
       "0              None            None  \n",
       "1              None            None  \n",
       "2              None            None  \n",
       "3              None            None  \n",
       "4              None            None  \n",
       "...             ...             ...  \n",
       "24495          None            None  \n",
       "24496          None            None  \n",
       "24497          None            None  \n",
       "24498          None            None  \n",
       "24499          None            None  \n",
       "\n",
       "[24500 rows x 10 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 1 min from the minute data\n",
    "# This code take a long time for just MMM I can not imagine how long it will take for 500 - 5000 symbols\n",
    "df_MMM_1m_mathametical = getconvert_minuteto_mathametical (df_MMM_m_type_1, 1,  True)\n",
    "df_MMM_1m_mathametical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>TotalQuantity</th>\n",
       "      <th>TotalTradeCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>197.63</td>\n",
       "      <td>198.34</td>\n",
       "      <td>197.54</td>\n",
       "      <td>2485331.41</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:32:00</td>\n",
       "      <td>197.70</td>\n",
       "      <td>198.26</td>\n",
       "      <td>198.26</td>\n",
       "      <td>197.70</td>\n",
       "      <td>877144.31</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:33:00</td>\n",
       "      <td>198.26</td>\n",
       "      <td>198.14</td>\n",
       "      <td>198.26</td>\n",
       "      <td>198.04</td>\n",
       "      <td>477146.81</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:34:00</td>\n",
       "      <td>198.12</td>\n",
       "      <td>197.92</td>\n",
       "      <td>198.15</td>\n",
       "      <td>197.91</td>\n",
       "      <td>297396.62</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:35:00</td>\n",
       "      <td>198.02</td>\n",
       "      <td>198.44</td>\n",
       "      <td>198.44</td>\n",
       "      <td>198.01</td>\n",
       "      <td>800694.64</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24524</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:56:00</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.07</td>\n",
       "      <td>200.96</td>\n",
       "      <td>2176869.20</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24525</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:57:00</td>\n",
       "      <td>201.07</td>\n",
       "      <td>201.05</td>\n",
       "      <td>201.10</td>\n",
       "      <td>201.03</td>\n",
       "      <td>2058977.34</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24526</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:58:00</td>\n",
       "      <td>201.07</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.04</td>\n",
       "      <td>3037745.19</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24527</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:59:00</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.11</td>\n",
       "      <td>200.99</td>\n",
       "      <td>2909039.61</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24528</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>201.02</td>\n",
       "      <td>200.98</td>\n",
       "      <td>201.08</td>\n",
       "      <td>200.95</td>\n",
       "      <td>4940895.48</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24529 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date      Time    Open   Close    High     Low      Volume Symbol  \\\n",
       "0     2021-04-12  09:31:00  198.25  197.63  198.34  197.54  2485331.41    MMM   \n",
       "1     2021-04-12  09:32:00  197.70  198.26  198.26  197.70   877144.31    MMM   \n",
       "2     2021-04-12  09:33:00  198.26  198.14  198.26  198.04   477146.81    MMM   \n",
       "3     2021-04-12  09:34:00  198.12  197.92  198.15  197.91   297396.62    MMM   \n",
       "4     2021-04-12  09:35:00  198.02  198.44  198.44  198.01   800694.64    MMM   \n",
       "...          ...       ...     ...     ...     ...     ...         ...    ...   \n",
       "24524 2021-07-09  15:56:00  201.04  201.04  201.07  200.96  2176869.20    MMM   \n",
       "24525 2021-07-09  15:57:00  201.07  201.05  201.10  201.03  2058977.34    MMM   \n",
       "24526 2021-07-09  15:58:00  201.07  201.11  201.11  201.04  3037745.19    MMM   \n",
       "24527 2021-07-09  15:59:00  201.11  201.04  201.11  200.99  2909039.61    MMM   \n",
       "24528 2021-07-09  16:00:00  201.02  200.98  201.08  200.95  4940895.48    MMM   \n",
       "\n",
       "      TotalQuantity TotalTradeCount  \n",
       "0              None            None  \n",
       "1              None            None  \n",
       "2              None            None  \n",
       "3              None            None  \n",
       "4              None            None  \n",
       "...             ...             ...  \n",
       "24524          None            None  \n",
       "24525          None            None  \n",
       "24526          None            None  \n",
       "24527          None            None  \n",
       "24528          None            None  \n",
       "\n",
       "[24529 rows x 10 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 1 min from the minute data\n",
    "# Traditional groups time frames from 0\n",
    "# Bug Alert - The trading_hours_criteria = False is not working\n",
    "# This code take a long time for just MMM I can not imagine how long it will take for 500 - 5000 symbols\n",
    "# Note - Code adds unncessary columns: TotalQuantity\tTotalTradeCount\n",
    "df_MMM_1m_traditional = getconvert_minuteto_traditional  (df_MMM_m_type_1, 1,  trading_hours_criteria = True,last_hour= 4,last_minute= 0)\n",
    "df_MMM_1m_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "data": {
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       "      <td>201.02</td>\n",
       "      <td>5862105.59</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4975</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:55:00</td>\n",
       "      <td>201.13</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.13</td>\n",
       "      <td>200.96</td>\n",
       "      <td>11167800.62</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4976</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>201.02</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.08</td>\n",
       "      <td>200.95</td>\n",
       "      <td>74323482.48</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4977 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date      Time    Open   Close    High     Low       Volume Symbol  \\\n",
       "0    2021-04-12  09:31:00  198.25  197.92  198.34  197.54   4137019.15    MMM   \n",
       "1    2021-04-12  09:35:00  198.02  198.18  198.44  198.01   2505193.36    MMM   \n",
       "2    2021-04-12  09:40:00  198.06  198.76  198.84  197.90   4286892.02    MMM   \n",
       "3    2021-04-12  09:45:00  198.79  198.70  199.25  198.61   7802217.73    MMM   \n",
       "4    2021-04-12  09:50:00  198.84  199.16  199.21  198.72   3239573.69    MMM   \n",
       "...         ...       ...     ...     ...     ...     ...          ...    ...   \n",
       "4972 2021-07-09  15:40:00  201.00  200.95  201.06  200.93   5200669.96    MMM   \n",
       "4973 2021-07-09  15:45:00  200.95  201.03  201.04  200.88   3869397.91    MMM   \n",
       "4974 2021-07-09  15:50:00  201.05  201.12  201.14  201.02   5862105.59    MMM   \n",
       "4975 2021-07-09  15:55:00  201.13  201.04  201.13  200.96  11167800.62    MMM   \n",
       "4976 2021-07-09  16:00:00  201.02  201.00  201.08  200.95  74323482.48    MMM   \n",
       "\n",
       "     TotalQuantity TotalTradeCount  \n",
       "0             None            None  \n",
       "1             None            None  \n",
       "2             None            None  \n",
       "3             None            None  \n",
       "4             None            None  \n",
       "...            ...             ...  \n",
       "4972          None            None  \n",
       "4973          None            None  \n",
       "4974          None            None  \n",
       "4975          None            None  \n",
       "4976          None            None  \n",
       "\n",
       "[4977 rows x 10 columns]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 5 min from the minute data\n",
    "df_MMM_5m_traditional = getconvert_minuteto_traditional  (df_MMM_m_type_1, 5,  trading_hours_criteria = True,last_hour= 4,last_minute= 4)\n",
    "df_MMM_5m_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>TotalQuantity</th>\n",
       "      <th>TotalTradeCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.76</td>\n",
       "      <td>198.84</td>\n",
       "      <td>197.54</td>\n",
       "      <td>10929104.53</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:45:00</td>\n",
       "      <td>198.79</td>\n",
       "      <td>199.10</td>\n",
       "      <td>199.27</td>\n",
       "      <td>198.61</td>\n",
       "      <td>15022796.14</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>199.13</td>\n",
       "      <td>198.41</td>\n",
       "      <td>199.29</td>\n",
       "      <td>198.35</td>\n",
       "      <td>6986501.49</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>10:15:00</td>\n",
       "      <td>198.46</td>\n",
       "      <td>198.35</td>\n",
       "      <td>198.68</td>\n",
       "      <td>198.27</td>\n",
       "      <td>5175655.26</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>10:30:00</td>\n",
       "      <td>198.33</td>\n",
       "      <td>198.57</td>\n",
       "      <td>198.67</td>\n",
       "      <td>198.20</td>\n",
       "      <td>6350619.87</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1696</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:00:00</td>\n",
       "      <td>201.06</td>\n",
       "      <td>201.11</td>\n",
       "      <td>201.23</td>\n",
       "      <td>201.00</td>\n",
       "      <td>4411411.36</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1697</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:15:00</td>\n",
       "      <td>201.09</td>\n",
       "      <td>201.08</td>\n",
       "      <td>201.18</td>\n",
       "      <td>201.01</td>\n",
       "      <td>5417800.80</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1698</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:30:00</td>\n",
       "      <td>201.10</td>\n",
       "      <td>200.95</td>\n",
       "      <td>201.10</td>\n",
       "      <td>200.93</td>\n",
       "      <td>10370560.40</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1699</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:45:00</td>\n",
       "      <td>200.95</td>\n",
       "      <td>201.04</td>\n",
       "      <td>201.14</td>\n",
       "      <td>200.88</td>\n",
       "      <td>20899304.12</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1700</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>201.02</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.08</td>\n",
       "      <td>200.95</td>\n",
       "      <td>74323482.48</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1701 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date      Time    Open   Close    High     Low       Volume Symbol  \\\n",
       "0    2021-04-12  09:31:00  198.25  198.76  198.84  197.54  10929104.53    MMM   \n",
       "1    2021-04-12  09:45:00  198.79  199.10  199.27  198.61  15022796.14    MMM   \n",
       "2    2021-04-12  10:00:00  199.13  198.41  199.29  198.35   6986501.49    MMM   \n",
       "3    2021-04-12  10:15:00  198.46  198.35  198.68  198.27   5175655.26    MMM   \n",
       "4    2021-04-12  10:30:00  198.33  198.57  198.67  198.20   6350619.87    MMM   \n",
       "...         ...       ...     ...     ...     ...     ...          ...    ...   \n",
       "1696 2021-07-09  15:00:00  201.06  201.11  201.23  201.00   4411411.36    MMM   \n",
       "1697 2021-07-09  15:15:00  201.09  201.08  201.18  201.01   5417800.80    MMM   \n",
       "1698 2021-07-09  15:30:00  201.10  200.95  201.10  200.93  10370560.40    MMM   \n",
       "1699 2021-07-09  15:45:00  200.95  201.04  201.14  200.88  20899304.12    MMM   \n",
       "1700 2021-07-09  16:00:00  201.02  201.00  201.08  200.95  74323482.48    MMM   \n",
       "\n",
       "     TotalQuantity TotalTradeCount  \n",
       "0             None            None  \n",
       "1             None            None  \n",
       "2             None            None  \n",
       "3             None            None  \n",
       "4             None            None  \n",
       "...            ...             ...  \n",
       "1696          None            None  \n",
       "1697          None            None  \n",
       "1698          None            None  \n",
       "1699          None            None  \n",
       "1700          None            None  \n",
       "\n",
       "[1701 rows x 10 columns]"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 15 min from the minute data\n",
    "# Bug Alert - Code will not accept last_minute > 10 only 9 and below\n",
    "df_MMM_15m_traditional = getconvert_minuteto_traditional  (df_MMM_m_type_1, 15,  trading_hours_criteria = True,last_hour= 4,last_minute= 9)\n",
    "df_MMM_15m_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n",
      "/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5516: 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",
      "  self[name] = value\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>TotalQuantity</th>\n",
       "      <th>TotalTradeCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.35</td>\n",
       "      <td>199.29</td>\n",
       "      <td>197.54</td>\n",
       "      <td>3.811406e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>10:30:00</td>\n",
       "      <td>198.33</td>\n",
       "      <td>198.22</td>\n",
       "      <td>198.67</td>\n",
       "      <td>197.82</td>\n",
       "      <td>2.944195e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>11:30:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.15</td>\n",
       "      <td>198.73</td>\n",
       "      <td>198.06</td>\n",
       "      <td>2.348289e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>12:30:00</td>\n",
       "      <td>198.15</td>\n",
       "      <td>197.59</td>\n",
       "      <td>198.39</td>\n",
       "      <td>197.39</td>\n",
       "      <td>2.211164e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>197.58</td>\n",
       "      <td>197.28</td>\n",
       "      <td>197.61</td>\n",
       "      <td>197.06</td>\n",
       "      <td>1.912919e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>11:30:00</td>\n",
       "      <td>201.01</td>\n",
       "      <td>200.53</td>\n",
       "      <td>201.52</td>\n",
       "      <td>200.48</td>\n",
       "      <td>1.818551e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>12:30:00</td>\n",
       "      <td>200.56</td>\n",
       "      <td>200.86</td>\n",
       "      <td>200.92</td>\n",
       "      <td>200.45</td>\n",
       "      <td>1.463036e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>200.87</td>\n",
       "      <td>200.99</td>\n",
       "      <td>201.06</td>\n",
       "      <td>200.62</td>\n",
       "      <td>1.778228e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>14:30:00</td>\n",
       "      <td>201.01</td>\n",
       "      <td>201.08</td>\n",
       "      <td>201.23</td>\n",
       "      <td>200.87</td>\n",
       "      <td>2.486125e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:30:00</td>\n",
       "      <td>201.10</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.14</td>\n",
       "      <td>200.88</td>\n",
       "      <td>1.055933e+08</td>\n",
       "      <td>MMM</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>441 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date      Time    Open   Close    High     Low        Volume Symbol  \\\n",
       "0   2021-04-12  09:31:00  198.25  198.35  199.29  197.54  3.811406e+07    MMM   \n",
       "1   2021-04-12  10:30:00  198.33  198.22  198.67  197.82  2.944195e+07    MMM   \n",
       "2   2021-04-12  11:30:00  198.25  198.15  198.73  198.06  2.348289e+07    MMM   \n",
       "3   2021-04-12  12:30:00  198.15  197.59  198.39  197.39  2.211164e+07    MMM   \n",
       "4   2021-04-12  13:30:00  197.58  197.28  197.61  197.06  1.912919e+07    MMM   \n",
       "..         ...       ...     ...     ...     ...     ...           ...    ...   \n",
       "436 2021-07-09  11:30:00  201.01  200.53  201.52  200.48  1.818551e+07    MMM   \n",
       "437 2021-07-09  12:30:00  200.56  200.86  200.92  200.45  1.463036e+07    MMM   \n",
       "438 2021-07-09  13:30:00  200.87  200.99  201.06  200.62  1.778228e+07    MMM   \n",
       "439 2021-07-09  14:30:00  201.01  201.08  201.23  200.87  2.486125e+07    MMM   \n",
       "440 2021-07-09  15:30:00  201.10  201.00  201.14  200.88  1.055933e+08    MMM   \n",
       "\n",
       "    TotalQuantity TotalTradeCount  \n",
       "0            None            None  \n",
       "1            None            None  \n",
       "2            None            None  \n",
       "3            None            None  \n",
       "4            None            None  \n",
       "..            ...             ...  \n",
       "436          None            None  \n",
       "437          None            None  \n",
       "438          None            None  \n",
       "439          None            None  \n",
       "440          None            None  \n",
       "\n",
       "[441 rows x 10 columns]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 1 hour from the minute data\n",
    "df_MMM_1h_traditional = getconvert_minuteto_traditional  (df_MMM_m_type_1, 60,  trading_hours_criteria = True,last_hour= 4,last_minute= 9)\n",
    "df_MMM_1h_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19980102</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.68750</td>\n",
       "      <td>42.6250</td>\n",
       "      <td>40.8750</td>\n",
       "      <td>5078600</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19980106</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>42.15625</td>\n",
       "      <td>42.8750</td>\n",
       "      <td>41.3750</td>\n",
       "      <td>6115000</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19980108</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>41.31250</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>41.0000</td>\n",
       "      <td>9934400</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19980112</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>42.06250</td>\n",
       "      <td>42.0625</td>\n",
       "      <td>40.5000</td>\n",
       "      <td>4177400</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19980114</td>\n",
       "      <td>41.87500</td>\n",
       "      <td>41.25000</td>\n",
       "      <td>42.1250</td>\n",
       "      <td>41.1875</td>\n",
       "      <td>3124800</td>\n",
       "      <td>MMM</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2970</th>\n",
       "      <td>20210810</td>\n",
       "      <td>198.24000</td>\n",
       "      <td>201.57000</td>\n",
       "      <td>201.7700</td>\n",
       "      <td>197.7000</td>\n",
       "      <td>3815880</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2971</th>\n",
       "      <td>20210812</td>\n",
       "      <td>201.48000</td>\n",
       "      <td>200.58000</td>\n",
       "      <td>202.3728</td>\n",
       "      <td>200.2900</td>\n",
       "      <td>3142884</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2972</th>\n",
       "      <td>20210816</td>\n",
       "      <td>201.09000</td>\n",
       "      <td>199.55000</td>\n",
       "      <td>202.7700</td>\n",
       "      <td>197.6000</td>\n",
       "      <td>3895054</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2973</th>\n",
       "      <td>20210818</td>\n",
       "      <td>198.57000</td>\n",
       "      <td>195.36000</td>\n",
       "      <td>198.8100</td>\n",
       "      <td>194.3070</td>\n",
       "      <td>4429008</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2974</th>\n",
       "      <td>20210820</td>\n",
       "      <td>194.34000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>196.2400</td>\n",
       "      <td>193.3650</td>\n",
       "      <td>4371714</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2975 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date       Open      Close      High       Low   Volume Symbol\n",
       "0     19980102   41.09375   41.68750   42.6250   40.8750  5078600    MMM\n",
       "1     19980106   41.62500   42.15625   42.8750   41.3750  6115000    MMM\n",
       "2     19980108   42.00000   41.31250   42.0000   41.0000  9934400    MMM\n",
       "3     19980112   40.50000   42.06250   42.0625   40.5000  4177400    MMM\n",
       "4     19980114   41.87500   41.25000   42.1250   41.1875  3124800    MMM\n",
       "...        ...        ...        ...       ...       ...      ...    ...\n",
       "2970  20210810  198.24000  201.57000  201.7700  197.7000  3815880    MMM\n",
       "2971  20210812  201.48000  200.58000  202.3728  200.2900  3142884    MMM\n",
       "2972  20210816  201.09000  199.55000  202.7700  197.6000  3895054    MMM\n",
       "2973  20210818  198.57000  195.36000  198.8100  194.3070  4429008    MMM\n",
       "2974  20210820  194.34000  194.68000  196.2400  193.3650  4371714    MMM\n",
       "\n",
       "[2975 rows x 7 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 2 Day min from Daily data\n",
    "# Note - There is no reason to do a 1 Day because that is daily data\n",
    "df_MMM_2d_mathametical = getconvert_dailyto_mathamtical(df_MMM_d_type_1,2)\n",
    "df_MMM_2d_mathametical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19980102</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.68750</td>\n",
       "      <td>42.6250</td>\n",
       "      <td>40.8750</td>\n",
       "      <td>5078600</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19980106</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>42.15625</td>\n",
       "      <td>42.8750</td>\n",
       "      <td>41.3750</td>\n",
       "      <td>6115000</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19980108</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>41.31250</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>41.0000</td>\n",
       "      <td>9934400</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19980112</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>42.06250</td>\n",
       "      <td>42.0625</td>\n",
       "      <td>40.5000</td>\n",
       "      <td>4177400</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19980114</td>\n",
       "      <td>41.87500</td>\n",
       "      <td>41.25000</td>\n",
       "      <td>42.1250</td>\n",
       "      <td>41.1875</td>\n",
       "      <td>3124800</td>\n",
       "      <td>MMM</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2970</th>\n",
       "      <td>20210810</td>\n",
       "      <td>198.24000</td>\n",
       "      <td>201.57000</td>\n",
       "      <td>201.7700</td>\n",
       "      <td>197.7000</td>\n",
       "      <td>3815880</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2971</th>\n",
       "      <td>20210812</td>\n",
       "      <td>201.48000</td>\n",
       "      <td>200.58000</td>\n",
       "      <td>202.3728</td>\n",
       "      <td>200.2900</td>\n",
       "      <td>3142884</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2972</th>\n",
       "      <td>20210816</td>\n",
       "      <td>201.09000</td>\n",
       "      <td>199.55000</td>\n",
       "      <td>202.7700</td>\n",
       "      <td>197.6000</td>\n",
       "      <td>3895054</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2973</th>\n",
       "      <td>20210818</td>\n",
       "      <td>198.57000</td>\n",
       "      <td>195.36000</td>\n",
       "      <td>198.8100</td>\n",
       "      <td>194.3070</td>\n",
       "      <td>4429008</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2974</th>\n",
       "      <td>20210820</td>\n",
       "      <td>194.34000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>196.2400</td>\n",
       "      <td>193.3650</td>\n",
       "      <td>4371714</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2975 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date       Open      Close      High       Low   Volume Symbol\n",
       "0     19980102   41.09375   41.68750   42.6250   40.8750  5078600    MMM\n",
       "1     19980106   41.62500   42.15625   42.8750   41.3750  6115000    MMM\n",
       "2     19980108   42.00000   41.31250   42.0000   41.0000  9934400    MMM\n",
       "3     19980112   40.50000   42.06250   42.0625   40.5000  4177400    MMM\n",
       "4     19980114   41.87500   41.25000   42.1250   41.1875  3124800    MMM\n",
       "...        ...        ...        ...       ...       ...      ...    ...\n",
       "2970  20210810  198.24000  201.57000  201.7700  197.7000  3815880    MMM\n",
       "2971  20210812  201.48000  200.58000  202.3728  200.2900  3142884    MMM\n",
       "2972  20210816  201.09000  199.55000  202.7700  197.6000  3895054    MMM\n",
       "2973  20210818  198.57000  195.36000  198.8100  194.3070  4429008    MMM\n",
       "2974  20210820  194.34000  194.68000  196.2400  193.3650  4371714    MMM\n",
       "\n",
       "[2975 rows x 7 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a 2 Day from Daily data in a Traditional way\n",
    "# Converts daily data types are Daily\" \"Weekly\" \"Monthly\" \"Yearly\"\n",
    "# Traditional is suppose to start from the beginning of the week (1st day of the week)\n",
    "df_MMM_2d_traditional = getconvert_dailyto_traditional(df_MMM_d_type_1,2,\"Daily\")\n",
    "df_MMM_2d_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19980102</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>41.81250</td>\n",
       "      <td>40.87500</td>\n",
       "      <td>2573000</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19980105</td>\n",
       "      <td>41.50000</td>\n",
       "      <td>41.31250</td>\n",
       "      <td>42.87500</td>\n",
       "      <td>41.00000</td>\n",
       "      <td>18555000</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19980112</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>42.12500</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>9829200</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19980120</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>40.78125</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>40.03125</td>\n",
       "      <td>8235000</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19980126</td>\n",
       "      <td>41.00000</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>42.96875</td>\n",
       "      <td>40.28125</td>\n",
       "      <td>13163200</td>\n",
       "      <td>MMM</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>20210726</td>\n",
       "      <td>200.45000</td>\n",
       "      <td>197.94000</td>\n",
       "      <td>202.74000</td>\n",
       "      <td>194.91000</td>\n",
       "      <td>11579084</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1231</th>\n",
       "      <td>20210802</td>\n",
       "      <td>199.07000</td>\n",
       "      <td>198.13000</td>\n",
       "      <td>202.21000</td>\n",
       "      <td>197.20000</td>\n",
       "      <td>8289593</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1232</th>\n",
       "      <td>20210809</td>\n",
       "      <td>197.65000</td>\n",
       "      <td>200.58000</td>\n",
       "      <td>202.37280</td>\n",
       "      <td>196.78000</td>\n",
       "      <td>8152122</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>20210816</td>\n",
       "      <td>201.09000</td>\n",
       "      <td>194.16000</td>\n",
       "      <td>202.77000</td>\n",
       "      <td>193.36500</td>\n",
       "      <td>10721487</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1234</th>\n",
       "      <td>20210823</td>\n",
       "      <td>195.00000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>196.24000</td>\n",
       "      <td>193.68000</td>\n",
       "      <td>1974289</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1235 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date       Open      Close       High        Low    Volume Symbol\n",
       "0     19980102   41.09375   41.75000   41.81250   40.87500   2573000    MMM\n",
       "1     19980105   41.50000   41.31250   42.87500   41.00000  18555000    MMM\n",
       "2     19980112   40.50000   41.62500   42.12500   40.50000   9829200    MMM\n",
       "3     19980120   41.62500   40.78125   41.75000   40.03125   8235000    MMM\n",
       "4     19980126   41.00000   41.75000   42.96875   40.28125  13163200    MMM\n",
       "...        ...        ...        ...        ...        ...       ...    ...\n",
       "1230  20210726  200.45000  197.94000  202.74000  194.91000  11579084    MMM\n",
       "1231  20210802  199.07000  198.13000  202.21000  197.20000   8289593    MMM\n",
       "1232  20210809  197.65000  200.58000  202.37280  196.78000   8152122    MMM\n",
       "1233  20210816  201.09000  194.16000  202.77000  193.36500  10721487    MMM\n",
       "1234  20210823  195.00000  194.68000  196.24000  193.68000   1974289    MMM\n",
       "\n",
       "[1235 rows x 7 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a weekly from Daily data in a Traditional way\n",
    "# Converts daily data types are Daily\" \"Weekly\" \"Monthly\" \"Yearly\"\n",
    "# Traditional is suppose to start from the beginning of the week (1st day of the week)\n",
    "df_MMM_1w_traditional = getconvert_dailyto_traditional(df_MMM_d_type_1,1,\"Weekly\")\n",
    "df_MMM_1w_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19980102</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>42.96875</td>\n",
       "      <td>40.03125</td>\n",
       "      <td>52355400</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19980202</td>\n",
       "      <td>42.18750</td>\n",
       "      <td>42.65625</td>\n",
       "      <td>44.68750</td>\n",
       "      <td>42.15625</td>\n",
       "      <td>34888400</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19980302</td>\n",
       "      <td>42.65625</td>\n",
       "      <td>45.50000</td>\n",
       "      <td>48.06250</td>\n",
       "      <td>42.65625</td>\n",
       "      <td>45769800</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19980401</td>\n",
       "      <td>46.31250</td>\n",
       "      <td>47.18750</td>\n",
       "      <td>48.93750</td>\n",
       "      <td>44.53125</td>\n",
       "      <td>36851600</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19980501</td>\n",
       "      <td>47.18750</td>\n",
       "      <td>46.31250</td>\n",
       "      <td>48.75000</td>\n",
       "      <td>46.21875</td>\n",
       "      <td>26461800</td>\n",
       "      <td>MMM</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>20210401</td>\n",
       "      <td>193.25000</td>\n",
       "      <td>197.14000</td>\n",
       "      <td>203.15500</td>\n",
       "      <td>188.63000</td>\n",
       "      <td>46438173</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>20210503</td>\n",
       "      <td>197.99000</td>\n",
       "      <td>203.04000</td>\n",
       "      <td>208.95000</td>\n",
       "      <td>196.66000</td>\n",
       "      <td>37466515</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>20210601</td>\n",
       "      <td>204.98000</td>\n",
       "      <td>198.63000</td>\n",
       "      <td>206.80630</td>\n",
       "      <td>191.53000</td>\n",
       "      <td>51315729</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282</th>\n",
       "      <td>20210701</td>\n",
       "      <td>199.45000</td>\n",
       "      <td>197.94000</td>\n",
       "      <td>203.21000</td>\n",
       "      <td>194.76000</td>\n",
       "      <td>46028249</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>283</th>\n",
       "      <td>20210802</td>\n",
       "      <td>199.07000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>202.77000</td>\n",
       "      <td>193.36500</td>\n",
       "      <td>29137491</td>\n",
       "      <td>MMM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>284 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date       Open      Close       High        Low    Volume Symbol\n",
       "0    19980102   41.09375   41.75000   42.96875   40.03125  52355400    MMM\n",
       "1    19980202   42.18750   42.65625   44.68750   42.15625  34888400    MMM\n",
       "2    19980302   42.65625   45.50000   48.06250   42.65625  45769800    MMM\n",
       "3    19980401   46.31250   47.18750   48.93750   44.53125  36851600    MMM\n",
       "4    19980501   47.18750   46.31250   48.75000   46.21875  26461800    MMM\n",
       "..        ...        ...        ...        ...        ...       ...    ...\n",
       "279  20210401  193.25000  197.14000  203.15500  188.63000  46438173    MMM\n",
       "280  20210503  197.99000  203.04000  208.95000  196.66000  37466515    MMM\n",
       "281  20210601  204.98000  198.63000  206.80630  191.53000  51315729    MMM\n",
       "282  20210701  199.45000  197.94000  203.21000  194.76000  46028249    MMM\n",
       "283  20210802  199.07000  194.68000  202.77000  193.36500  29137491    MMM\n",
       "\n",
       "[284 rows x 7 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets get a monthly from Daily data in a Traditional way\n",
    "# Converts daily data types are Daily\" \"Weekly\" \"Monthly\" \"Yearly\"\n",
    "# Traditional is suppose to start from the beginning of the week (1st day of the week)\n",
    "df_MMM_1mon_traditional = getconvert_dailyto_traditional(df_MMM_d_type_1,1,\"Monthly\")\n",
    "df_MMM_1mon_traditional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now that we have our data in the time frames we want let us now add columns\n",
    "# There are x types of columns where x = = 8 for now\n",
    "# 1. Indicators e.g. moving averages, slope, etc the are 100s of columns that are to contain indicator returns\n",
    "# 2. Profile Data e.g. CIK, Company name etc\n",
    "# 3. Accounting Data e.g. Revenues, cash flow, earnings\n",
    "# 4. Accounting Ratios e.g. Apply formulas to Accounting Data\n",
    "# 5. Propietary Data e.g. Data from Short Squeeze\n",
    "# 6. Missing Data e.g. Data obtained from Bloomberg\n",
    "# 7. Experimental Data e.g creating new symbols derived for current groups of symbols\n",
    "# 8. Predictive Data e.g. Using Blast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let us add indicators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Custom indicators group 1\n",
    "# These are simple indicators "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SimpleMovingAvg(data, price, length):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tsma = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in data[data['Symbol'] == _][price].rolling(length).mean():\n",
    "\t\t\tsma.append(__)\n",
    "\treturn sma\n",
    "\n",
    "def ExpMovingAvg(data, price, length):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tema = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=length, adjust=False).mean():\n",
    "\t\t\tema.append(__)\n",
    "\treturn ema\n",
    "\n",
    "def movingAverageConvergenceDivergence_Value(data, price,fastLength, slowLength, MACDLength):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tValue = []\n",
    "\tAverage = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=fastLength, adjust=False).mean() - data[data['Symbol'] == _][price].ewm(span=slowLength, adjust=False).mean():\n",
    "\t\t\tValue.append(__)\n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=MACDLength, adjust=False).mean():\n",
    "\t\t\tAverage.append(__)\n",
    "\treturn Value\n",
    "\n",
    "def movingAverageConvergenceDivergence_Average(data, price,fastLength, slowLength, MACDLength):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tValue = []\n",
    "\tAverage = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=fastLength, adjust=False).mean() - data[data['Symbol'] == _][price].ewm(span=slowLength, adjust=False).mean():\n",
    "\t\t\tValue.append(__)\n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=MACDLength, adjust=False).mean():\n",
    "\t\t\tAverage.append(__)\n",
    "\treturn Average\n",
    "\n",
    "def movingAverageConvergenceDivergence_Difference(data, price,fastLength, slowLength, MACDLength):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tValue = []\n",
    "\tAverage = []\n",
    "\tDifference = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=fastLength, adjust=False).mean() - data[data['Symbol'] == _][price].ewm(span=slowLength, adjust=False).mean():\n",
    "\t\t\tValue.append(__)\n",
    "\t\tfor __ in data[data['Symbol'] == _][price].ewm(span=MACDLength, adjust=False).mean():\n",
    "\t\t\tAverage.append(__)\n",
    "\tfor i in range(len(Value)):\n",
    "\t\tDifference.append(Value[i] - Average[i])\n",
    "\treturn Difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We will use the 15min time frame  (df_MMM_15m_traditional) and the weekly (df_MMM_1w_traditional)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cleaning\n",
    "df_MMM_15m_traditional.drop(['TotalQuantity'], axis=1, inplace=True)\n",
    "df_MMM_15m_traditional.drop(['TotalTradeCount'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>2_p_sma</th>\n",
       "      <th>macd_val</th>\n",
       "      <th>macd_avg</th>\n",
       "      <th>macd_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.35</td>\n",
       "      <td>199.29</td>\n",
       "      <td>197.54</td>\n",
       "      <td>3.811406e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>198.350000</td>\n",
       "      <td>-198.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>10:30:00</td>\n",
       "      <td>198.33</td>\n",
       "      <td>198.22</td>\n",
       "      <td>198.67</td>\n",
       "      <td>197.82</td>\n",
       "      <td>2.944195e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.285</td>\n",
       "      <td>-0.010370</td>\n",
       "      <td>198.324000</td>\n",
       "      <td>-198.334370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>11:30:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.15</td>\n",
       "      <td>198.73</td>\n",
       "      <td>198.06</td>\n",
       "      <td>2.348289e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.185</td>\n",
       "      <td>-0.023961</td>\n",
       "      <td>198.289200</td>\n",
       "      <td>-198.313161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>12:30:00</td>\n",
       "      <td>198.15</td>\n",
       "      <td>197.59</td>\n",
       "      <td>198.39</td>\n",
       "      <td>197.39</td>\n",
       "      <td>2.211164e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.870</td>\n",
       "      <td>-0.079009</td>\n",
       "      <td>198.149360</td>\n",
       "      <td>-198.228369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>197.58</td>\n",
       "      <td>197.28</td>\n",
       "      <td>197.61</td>\n",
       "      <td>197.06</td>\n",
       "      <td>1.912919e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.435</td>\n",
       "      <td>-0.145966</td>\n",
       "      <td>197.975488</td>\n",
       "      <td>-198.121454</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>11:30:00</td>\n",
       "      <td>201.01</td>\n",
       "      <td>200.53</td>\n",
       "      <td>201.52</td>\n",
       "      <td>200.48</td>\n",
       "      <td>1.818551e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>200.800</td>\n",
       "      <td>0.592100</td>\n",
       "      <td>199.620256</td>\n",
       "      <td>-199.028156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>12:30:00</td>\n",
       "      <td>200.56</td>\n",
       "      <td>200.86</td>\n",
       "      <td>200.92</td>\n",
       "      <td>200.45</td>\n",
       "      <td>1.463036e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>200.695</td>\n",
       "      <td>0.665545</td>\n",
       "      <td>199.868205</td>\n",
       "      <td>-199.202660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>200.87</td>\n",
       "      <td>200.99</td>\n",
       "      <td>201.06</td>\n",
       "      <td>200.62</td>\n",
       "      <td>1.778228e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>200.925</td>\n",
       "      <td>0.725873</td>\n",
       "      <td>200.092564</td>\n",
       "      <td>-199.366691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>14:30:00</td>\n",
       "      <td>201.01</td>\n",
       "      <td>201.08</td>\n",
       "      <td>201.23</td>\n",
       "      <td>200.87</td>\n",
       "      <td>2.486125e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.035</td>\n",
       "      <td>0.772046</td>\n",
       "      <td>200.290051</td>\n",
       "      <td>-199.518005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:30:00</td>\n",
       "      <td>201.10</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.14</td>\n",
       "      <td>200.88</td>\n",
       "      <td>1.055933e+08</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.040</td>\n",
       "      <td>0.793042</td>\n",
       "      <td>200.432041</td>\n",
       "      <td>-199.638999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>441 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date      Time    Open   Close    High     Low        Volume Symbol  \\\n",
       "0   2021-04-12  09:31:00  198.25  198.35  199.29  197.54  3.811406e+07    MMM   \n",
       "1   2021-04-12  10:30:00  198.33  198.22  198.67  197.82  2.944195e+07    MMM   \n",
       "2   2021-04-12  11:30:00  198.25  198.15  198.73  198.06  2.348289e+07    MMM   \n",
       "3   2021-04-12  12:30:00  198.15  197.59  198.39  197.39  2.211164e+07    MMM   \n",
       "4   2021-04-12  13:30:00  197.58  197.28  197.61  197.06  1.912919e+07    MMM   \n",
       "..         ...       ...     ...     ...     ...     ...           ...    ...   \n",
       "436 2021-07-09  11:30:00  201.01  200.53  201.52  200.48  1.818551e+07    MMM   \n",
       "437 2021-07-09  12:30:00  200.56  200.86  200.92  200.45  1.463036e+07    MMM   \n",
       "438 2021-07-09  13:30:00  200.87  200.99  201.06  200.62  1.778228e+07    MMM   \n",
       "439 2021-07-09  14:30:00  201.01  201.08  201.23  200.87  2.486125e+07    MMM   \n",
       "440 2021-07-09  15:30:00  201.10  201.00  201.14  200.88  1.055933e+08    MMM   \n",
       "\n",
       "     2_p_sma  macd_val    macd_avg   macd_diff  \n",
       "0        NaN  0.000000  198.350000 -198.350000  \n",
       "1    198.285 -0.010370  198.324000 -198.334370  \n",
       "2    198.185 -0.023961  198.289200 -198.313161  \n",
       "3    197.870 -0.079009  198.149360 -198.228369  \n",
       "4    197.435 -0.145966  197.975488 -198.121454  \n",
       "..       ...       ...         ...         ...  \n",
       "436  200.800  0.592100  199.620256 -199.028156  \n",
       "437  200.695  0.665545  199.868205 -199.202660  \n",
       "438  200.925  0.725873  200.092564 -199.366691  \n",
       "439  201.035  0.772046  200.290051 -199.518005  \n",
       "440  201.040  0.793042  200.432041 -199.638999  \n",
       "\n",
       "[441 rows x 12 columns]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Applying Indicators on the 15min time frame\n",
    "df_MMM_15m = df_MMM_15m_traditional\n",
    "df_MMM_15m[\"2_p_sma\"] = SimpleMovingAvg(df_MMM_15m_traditional, \"Close\", 2)\n",
    "df_MMM_15m[\"macd_val\"]= movingAverageConvergenceDivergence_Value(df_MMM_15m_traditional, \"Close\",12, 26, 9)\n",
    "df_MMM_15m[\"macd_avg\"] = movingAverageConvergenceDivergence_Average(df_MMM_15m_traditional, \"Close\",12, 26, 9)\n",
    "df_MMM_15m[\"macd_diff\"] = movingAverageConvergenceDivergence_Difference(df_MMM_15m_traditional, \"Close\",12, 26, 9)\n",
    "df_MMM_15m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>2_p_sma</th>\n",
       "      <th>macd_val</th>\n",
       "      <th>macd_avg</th>\n",
       "      <th>macd_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19980102</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>41.81250</td>\n",
       "      <td>40.87500</td>\n",
       "      <td>2573000</td>\n",
       "      <td>MMM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>41.750000</td>\n",
       "      <td>-41.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19980105</td>\n",
       "      <td>41.50000</td>\n",
       "      <td>41.31250</td>\n",
       "      <td>42.87500</td>\n",
       "      <td>41.00000</td>\n",
       "      <td>18555000</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.531250</td>\n",
       "      <td>-0.034900</td>\n",
       "      <td>41.662500</td>\n",
       "      <td>-41.697400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19980112</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>42.12500</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>9829200</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.468750</td>\n",
       "      <td>-0.036917</td>\n",
       "      <td>41.655000</td>\n",
       "      <td>-41.691917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19980120</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>40.78125</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>40.03125</td>\n",
       "      <td>8235000</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.203125</td>\n",
       "      <td>-0.105385</td>\n",
       "      <td>41.480250</td>\n",
       "      <td>-41.585635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19980126</td>\n",
       "      <td>41.00000</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>42.96875</td>\n",
       "      <td>40.28125</td>\n",
       "      <td>13163200</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.265625</td>\n",
       "      <td>-0.080547</td>\n",
       "      <td>41.534200</td>\n",
       "      <td>-41.614747</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>20210726</td>\n",
       "      <td>200.45000</td>\n",
       "      <td>197.94000</td>\n",
       "      <td>202.74000</td>\n",
       "      <td>194.91000</td>\n",
       "      <td>11579084</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.215000</td>\n",
       "      <td>5.073759</td>\n",
       "      <td>199.079634</td>\n",
       "      <td>-194.005876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1231</th>\n",
       "      <td>20210802</td>\n",
       "      <td>199.07000</td>\n",
       "      <td>198.13000</td>\n",
       "      <td>202.21000</td>\n",
       "      <td>197.20000</td>\n",
       "      <td>8289593</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.035000</td>\n",
       "      <td>4.662252</td>\n",
       "      <td>198.889708</td>\n",
       "      <td>-194.227456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1232</th>\n",
       "      <td>20210809</td>\n",
       "      <td>197.65000</td>\n",
       "      <td>200.58000</td>\n",
       "      <td>202.37280</td>\n",
       "      <td>196.78000</td>\n",
       "      <td>8152122</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.355000</td>\n",
       "      <td>4.482157</td>\n",
       "      <td>199.227766</td>\n",
       "      <td>-194.745609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>20210816</td>\n",
       "      <td>201.09000</td>\n",
       "      <td>194.16000</td>\n",
       "      <td>202.77000</td>\n",
       "      <td>193.36500</td>\n",
       "      <td>10721487</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.370000</td>\n",
       "      <td>3.777841</td>\n",
       "      <td>198.214213</td>\n",
       "      <td>-194.436371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1234</th>\n",
       "      <td>20210823</td>\n",
       "      <td>195.00000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>196.24000</td>\n",
       "      <td>193.68000</td>\n",
       "      <td>1974289</td>\n",
       "      <td>MMM</td>\n",
       "      <td>194.420000</td>\n",
       "      <td>3.224456</td>\n",
       "      <td>197.507370</td>\n",
       "      <td>-194.282914</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1235 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date       Open      Close       High        Low    Volume Symbol  \\\n",
       "0     19980102   41.09375   41.75000   41.81250   40.87500   2573000    MMM   \n",
       "1     19980105   41.50000   41.31250   42.87500   41.00000  18555000    MMM   \n",
       "2     19980112   40.50000   41.62500   42.12500   40.50000   9829200    MMM   \n",
       "3     19980120   41.62500   40.78125   41.75000   40.03125   8235000    MMM   \n",
       "4     19980126   41.00000   41.75000   42.96875   40.28125  13163200    MMM   \n",
       "...        ...        ...        ...        ...        ...       ...    ...   \n",
       "1230  20210726  200.45000  197.94000  202.74000  194.91000  11579084    MMM   \n",
       "1231  20210802  199.07000  198.13000  202.21000  197.20000   8289593    MMM   \n",
       "1232  20210809  197.65000  200.58000  202.37280  196.78000   8152122    MMM   \n",
       "1233  20210816  201.09000  194.16000  202.77000  193.36500  10721487    MMM   \n",
       "1234  20210823  195.00000  194.68000  196.24000  193.68000   1974289    MMM   \n",
       "\n",
       "         2_p_sma  macd_val    macd_avg   macd_diff  \n",
       "0            NaN  0.000000   41.750000  -41.750000  \n",
       "1      41.531250 -0.034900   41.662500  -41.697400  \n",
       "2      41.468750 -0.036917   41.655000  -41.691917  \n",
       "3      41.203125 -0.105385   41.480250  -41.585635  \n",
       "4      41.265625 -0.080547   41.534200  -41.614747  \n",
       "...          ...       ...         ...         ...  \n",
       "1230  199.215000  5.073759  199.079634 -194.005876  \n",
       "1231  198.035000  4.662252  198.889708 -194.227456  \n",
       "1232  199.355000  4.482157  199.227766 -194.745609  \n",
       "1233  197.370000  3.777841  198.214213 -194.436371  \n",
       "1234  194.420000  3.224456  197.507370 -194.282914  \n",
       "\n",
       "[1235 rows x 11 columns]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Applying Indicators on the 1 week time frame\n",
    "df_MMM_1w = df_MMM_1w_traditional\n",
    "df_MMM_1w[\"2_p_sma\"] = SimpleMovingAvg(df_MMM_1w_traditional, \"Close\", 2)\n",
    "df_MMM_1w[\"macd_val\"]= movingAverageConvergenceDivergence_Value(df_MMM_1w_traditional, \"Close\",12, 26, 9)\n",
    "df_MMM_1w[\"macd_avg\"] = movingAverageConvergenceDivergence_Average(df_MMM_1w_traditional, \"Close\",12, 26, 9)\n",
    "df_MMM_1w[\"macd_diff\"] = movingAverageConvergenceDivergence_Difference(df_MMM_1w_traditional, \"Close\",12, 26, 9)\n",
    "df_MMM_1w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Custom indicators group 2\n",
    "# These are difficult indicators - currently being coded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Next we will apply library indicators\n",
    "# There are others but we will use talib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "import talib as ta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "1. Use talib to calculate Doji\n",
    "\"\"\"\n",
    "def Doji(data, open, high, low, close):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tDoji = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in ta.CDLDOJI(data[data['Symbol'] == _][open], data[data['Symbol'] == _][high], data[data['Symbol'] == _][low], data[data['Symbol'] == _][close]):\n",
    "\t\t\tDoji.append(__)\n",
    "\treturn Doji\n",
    "\n",
    "\"\"\"\n",
    "1. Use talib to calculate Engulfing Pattern\n",
    "\"\"\"\n",
    "def EngulfingPattern(data, open, high, low, close):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tEngulfingPattern = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in ta.CDLENGULFING(data[data['Symbol'] == _][open], data[data['Symbol'] == _][high], data[data['Symbol'] == _][low], data[data['Symbol'] == _][close]):\n",
    "\t\t\tEngulfingPattern.append(__)\n",
    "\treturn EngulfingPattern\n",
    "\n",
    "\"\"\"\n",
    "1. Use talib to calculate RSI(data, price, timeperiod)\n",
    "\"\"\"\n",
    "def RSI(data, price, timeperiod):\n",
    "\tsymbols = data[\"Symbol\"].unique()\n",
    "\tRSI = []\n",
    "\tfor _ in symbols: \n",
    "\t\tfor __ in ta.RSI(data[data['Symbol'] == _][price], timeperiod=timeperiod):\n",
    "\t\t\tRSI.append(__)\n",
    "\treturn RSI\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\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>Time</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>2_p_sma</th>\n",
       "      <th>macd_val</th>\n",
       "      <th>macd_avg</th>\n",
       "      <th>macd_diff</th>\n",
       "      <th>doji</th>\n",
       "      <th>engulfing</th>\n",
       "      <th>5_RSI</th>\n",
       "      <th>14_RSI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>09:31:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.35</td>\n",
       "      <td>199.29</td>\n",
       "      <td>197.54</td>\n",
       "      <td>3.811406e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>198.350000</td>\n",
       "      <td>-198.350000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>10:30:00</td>\n",
       "      <td>198.33</td>\n",
       "      <td>198.22</td>\n",
       "      <td>198.67</td>\n",
       "      <td>197.82</td>\n",
       "      <td>2.944195e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.285</td>\n",
       "      <td>-0.010370</td>\n",
       "      <td>198.324000</td>\n",
       "      <td>-198.334370</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>11:30:00</td>\n",
       "      <td>198.25</td>\n",
       "      <td>198.15</td>\n",
       "      <td>198.73</td>\n",
       "      <td>198.06</td>\n",
       "      <td>2.348289e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.185</td>\n",
       "      <td>-0.023961</td>\n",
       "      <td>198.289200</td>\n",
       "      <td>-198.313161</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>12:30:00</td>\n",
       "      <td>198.15</td>\n",
       "      <td>197.59</td>\n",
       "      <td>198.39</td>\n",
       "      <td>197.39</td>\n",
       "      <td>2.211164e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.870</td>\n",
       "      <td>-0.079009</td>\n",
       "      <td>198.149360</td>\n",
       "      <td>-198.228369</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>197.58</td>\n",
       "      <td>197.28</td>\n",
       "      <td>197.61</td>\n",
       "      <td>197.06</td>\n",
       "      <td>1.912919e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.435</td>\n",
       "      <td>-0.145966</td>\n",
       "      <td>197.975488</td>\n",
       "      <td>-198.121454</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>11:30:00</td>\n",
       "      <td>201.01</td>\n",
       "      <td>200.53</td>\n",
       "      <td>201.52</td>\n",
       "      <td>200.48</td>\n",
       "      <td>1.818551e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>200.800</td>\n",
       "      <td>0.592100</td>\n",
       "      <td>199.620256</td>\n",
       "      <td>-199.028156</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>64.218169</td>\n",
       "      <td>59.643224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>12:30:00</td>\n",
       "      <td>200.56</td>\n",
       "      <td>200.86</td>\n",
       "      <td>200.92</td>\n",
       "      <td>200.45</td>\n",
       "      <td>1.463036e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>200.695</td>\n",
       "      <td>0.665545</td>\n",
       "      <td>199.868205</td>\n",
       "      <td>-199.202660</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>67.563941</td>\n",
       "      <td>61.048422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>200.87</td>\n",
       "      <td>200.99</td>\n",
       "      <td>201.06</td>\n",
       "      <td>200.62</td>\n",
       "      <td>1.778228e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>200.925</td>\n",
       "      <td>0.725873</td>\n",
       "      <td>200.092564</td>\n",
       "      <td>-199.366691</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68.991689</td>\n",
       "      <td>61.615434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>14:30:00</td>\n",
       "      <td>201.01</td>\n",
       "      <td>201.08</td>\n",
       "      <td>201.23</td>\n",
       "      <td>200.87</td>\n",
       "      <td>2.486125e+07</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.035</td>\n",
       "      <td>0.772046</td>\n",
       "      <td>200.290051</td>\n",
       "      <td>-199.518005</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>70.129512</td>\n",
       "      <td>62.027550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>15:30:00</td>\n",
       "      <td>201.10</td>\n",
       "      <td>201.00</td>\n",
       "      <td>201.14</td>\n",
       "      <td>200.88</td>\n",
       "      <td>1.055933e+08</td>\n",
       "      <td>MMM</td>\n",
       "      <td>201.040</td>\n",
       "      <td>0.793042</td>\n",
       "      <td>200.432041</td>\n",
       "      <td>-199.638999</td>\n",
       "      <td>0</td>\n",
       "      <td>-100</td>\n",
       "      <td>67.382252</td>\n",
       "      <td>61.396536</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>441 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date      Time    Open   Close    High     Low        Volume Symbol  \\\n",
       "0   2021-04-12  09:31:00  198.25  198.35  199.29  197.54  3.811406e+07    MMM   \n",
       "1   2021-04-12  10:30:00  198.33  198.22  198.67  197.82  2.944195e+07    MMM   \n",
       "2   2021-04-12  11:30:00  198.25  198.15  198.73  198.06  2.348289e+07    MMM   \n",
       "3   2021-04-12  12:30:00  198.15  197.59  198.39  197.39  2.211164e+07    MMM   \n",
       "4   2021-04-12  13:30:00  197.58  197.28  197.61  197.06  1.912919e+07    MMM   \n",
       "..         ...       ...     ...     ...     ...     ...           ...    ...   \n",
       "436 2021-07-09  11:30:00  201.01  200.53  201.52  200.48  1.818551e+07    MMM   \n",
       "437 2021-07-09  12:30:00  200.56  200.86  200.92  200.45  1.463036e+07    MMM   \n",
       "438 2021-07-09  13:30:00  200.87  200.99  201.06  200.62  1.778228e+07    MMM   \n",
       "439 2021-07-09  14:30:00  201.01  201.08  201.23  200.87  2.486125e+07    MMM   \n",
       "440 2021-07-09  15:30:00  201.10  201.00  201.14  200.88  1.055933e+08    MMM   \n",
       "\n",
       "     2_p_sma  macd_val    macd_avg   macd_diff  doji  engulfing      5_RSI  \\\n",
       "0        NaN  0.000000  198.350000 -198.350000     0          0        NaN   \n",
       "1    198.285 -0.010370  198.324000 -198.334370     0          0        NaN   \n",
       "2    198.185 -0.023961  198.289200 -198.313161     0          0        NaN   \n",
       "3    197.870 -0.079009  198.149360 -198.228369     0          0        NaN   \n",
       "4    197.435 -0.145966  197.975488 -198.121454     0          0        NaN   \n",
       "..       ...       ...         ...         ...   ...        ...        ...   \n",
       "436  200.800  0.592100  199.620256 -199.028156     0          0  64.218169   \n",
       "437  200.695  0.665545  199.868205 -199.202660     0          0  67.563941   \n",
       "438  200.925  0.725873  200.092564 -199.366691     0          0  68.991689   \n",
       "439  201.035  0.772046  200.290051 -199.518005   100          0  70.129512   \n",
       "440  201.040  0.793042  200.432041 -199.638999     0       -100  67.382252   \n",
       "\n",
       "        14_RSI  \n",
       "0          NaN  \n",
       "1          NaN  \n",
       "2          NaN  \n",
       "3          NaN  \n",
       "4          NaN  \n",
       "..         ...  \n",
       "436  59.643224  \n",
       "437  61.048422  \n",
       "438  61.615434  \n",
       "439  62.027550  \n",
       "440  61.396536  \n",
       "\n",
       "[441 rows x 16 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding more indicators from libraries for 15min time frame\n",
    "df_MMM_15m[\"doji\"] = Doji(df_MMM_15m, \"Open\", \"High\", \"Low\", \"Close\")\n",
    "df_MMM_15m[\"engulfing\"] = EngulfingPattern(df_MMM_15m, \"Open\", \"High\", \"Low\", \"Close\")\n",
    "df_MMM_15m[\"5_RSI\"] = RSI(df_MMM_15m, \"Close\",5)\n",
    "df_MMM_15m[\"14_RSI\"] = RSI(df_MMM_15m, \"Close\",14)\n",
    "df_MMM_15m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Symbol</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19980102</td>\n",
       "      <td>41.09375</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>41.81250</td>\n",
       "      <td>40.87500</td>\n",
       "      <td>2573000</td>\n",
       "      <td>MMM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>41.750000</td>\n",
       "      <td>-41.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19980105</td>\n",
       "      <td>41.50000</td>\n",
       "      <td>41.31250</td>\n",
       "      <td>42.87500</td>\n",
       "      <td>41.00000</td>\n",
       "      <td>18555000</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.531250</td>\n",
       "      <td>-0.034900</td>\n",
       "      <td>41.662500</td>\n",
       "      <td>-41.697400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19980112</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>42.12500</td>\n",
       "      <td>40.50000</td>\n",
       "      <td>9829200</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.468750</td>\n",
       "      <td>-0.036917</td>\n",
       "      <td>41.655000</td>\n",
       "      <td>-41.691917</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19980120</td>\n",
       "      <td>41.62500</td>\n",
       "      <td>40.78125</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>40.03125</td>\n",
       "      <td>8235000</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.203125</td>\n",
       "      <td>-0.105385</td>\n",
       "      <td>41.480250</td>\n",
       "      <td>-41.585635</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19980126</td>\n",
       "      <td>41.00000</td>\n",
       "      <td>41.75000</td>\n",
       "      <td>42.96875</td>\n",
       "      <td>40.28125</td>\n",
       "      <td>13163200</td>\n",
       "      <td>MMM</td>\n",
       "      <td>41.265625</td>\n",
       "      <td>-0.080547</td>\n",
       "      <td>41.534200</td>\n",
       "      <td>-41.614747</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>20210726</td>\n",
       "      <td>200.45000</td>\n",
       "      <td>197.94000</td>\n",
       "      <td>202.74000</td>\n",
       "      <td>194.91000</td>\n",
       "      <td>11579084</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.215000</td>\n",
       "      <td>5.073759</td>\n",
       "      <td>199.079634</td>\n",
       "      <td>-194.005876</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45.014476</td>\n",
       "      <td>55.474259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1231</th>\n",
       "      <td>20210802</td>\n",
       "      <td>199.07000</td>\n",
       "      <td>198.13000</td>\n",
       "      <td>202.21000</td>\n",
       "      <td>197.20000</td>\n",
       "      <td>8289593</td>\n",
       "      <td>MMM</td>\n",
       "      <td>198.035000</td>\n",
       "      <td>4.662252</td>\n",
       "      <td>198.889708</td>\n",
       "      <td>-194.227456</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45.913595</td>\n",
       "      <td>55.664836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1232</th>\n",
       "      <td>20210809</td>\n",
       "      <td>197.65000</td>\n",
       "      <td>200.58000</td>\n",
       "      <td>202.37280</td>\n",
       "      <td>196.78000</td>\n",
       "      <td>8152122</td>\n",
       "      <td>MMM</td>\n",
       "      <td>199.355000</td>\n",
       "      <td>4.482157</td>\n",
       "      <td>199.227766</td>\n",
       "      <td>-194.745609</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>57.195461</td>\n",
       "      <td>58.152154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>20210816</td>\n",
       "      <td>201.09000</td>\n",
       "      <td>194.16000</td>\n",
       "      <td>202.77000</td>\n",
       "      <td>193.36500</td>\n",
       "      <td>10721487</td>\n",
       "      <td>MMM</td>\n",
       "      <td>197.370000</td>\n",
       "      <td>3.777841</td>\n",
       "      <td>198.214213</td>\n",
       "      <td>-194.436371</td>\n",
       "      <td>0</td>\n",
       "      <td>-100</td>\n",
       "      <td>33.979433</td>\n",
       "      <td>50.203864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1234</th>\n",
       "      <td>20210823</td>\n",
       "      <td>195.00000</td>\n",
       "      <td>194.68000</td>\n",
       "      <td>196.24000</td>\n",
       "      <td>193.68000</td>\n",
       "      <td>1974289</td>\n",
       "      <td>MMM</td>\n",
       "      <td>194.420000</td>\n",
       "      <td>3.224456</td>\n",
       "      <td>197.507370</td>\n",
       "      <td>-194.282914</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>36.585545</td>\n",
       "      <td>50.790555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1235 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date       Open      Close       High        Low    Volume Symbol  \\\n",
       "0     19980102   41.09375   41.75000   41.81250   40.87500   2573000    MMM   \n",
       "1     19980105   41.50000   41.31250   42.87500   41.00000  18555000    MMM   \n",
       "2     19980112   40.50000   41.62500   42.12500   40.50000   9829200    MMM   \n",
       "3     19980120   41.62500   40.78125   41.75000   40.03125   8235000    MMM   \n",
       "4     19980126   41.00000   41.75000   42.96875   40.28125  13163200    MMM   \n",
       "...        ...        ...        ...        ...        ...       ...    ...   \n",
       "1230  20210726  200.45000  197.94000  202.74000  194.91000  11579084    MMM   \n",
       "1231  20210802  199.07000  198.13000  202.21000  197.20000   8289593    MMM   \n",
       "1232  20210809  197.65000  200.58000  202.37280  196.78000   8152122    MMM   \n",
       "1233  20210816  201.09000  194.16000  202.77000  193.36500  10721487    MMM   \n",
       "1234  20210823  195.00000  194.68000  196.24000  193.68000   1974289    MMM   \n",
       "\n",
       "         2_p_sma  macd_val    macd_avg   macd_diff  doji  engulfing  \\\n",
       "0            NaN  0.000000   41.750000  -41.750000     0          0   \n",
       "1      41.531250 -0.034900   41.662500  -41.697400     0          0   \n",
       "2      41.468750 -0.036917   41.655000  -41.691917     0        100   \n",
       "3      41.203125 -0.105385   41.480250  -41.585635     0          0   \n",
       "4      41.265625 -0.080547   41.534200  -41.614747     0          0   \n",
       "...          ...       ...         ...         ...   ...        ...   \n",
       "1230  199.215000  5.073759  199.079634 -194.005876     0          0   \n",
       "1231  198.035000  4.662252  198.889708 -194.227456     0          0   \n",
       "1232  199.355000  4.482157  199.227766 -194.745609     0        100   \n",
       "1233  197.370000  3.777841  198.214213 -194.436371     0       -100   \n",
       "1234  194.420000  3.224456  197.507370 -194.282914   100          0   \n",
       "\n",
       "          5_RSI     14_RSI  \n",
       "0           NaN        NaN  \n",
       "1           NaN        NaN  \n",
       "2           NaN        NaN  \n",
       "3           NaN        NaN  \n",
       "4           NaN        NaN  \n",
       "...         ...        ...  \n",
       "1230  45.014476  55.474259  \n",
       "1231  45.913595  55.664836  \n",
       "1232  57.195461  58.152154  \n",
       "1233  33.979433  50.203864  \n",
       "1234  36.585545  50.790555  \n",
       "\n",
       "[1235 rows x 15 columns]"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding more indicators from libraries for 1 week time frame\n",
    "df_MMM_1w[\"doji\"] = Doji(df_MMM_1w, \"Open\", \"High\", \"Low\", \"Close\")\n",
    "df_MMM_1w[\"engulfing\"] = EngulfingPattern(df_MMM_1w, \"Open\", \"High\", \"Low\", \"Close\")\n",
    "df_MMM_1w[\"5_RSI\"] = RSI(df_MMM_1w, \"Close\",5)\n",
    "df_MMM_1w[\"14_RSI\"] = RSI(df_MMM_1w, \"Close\",14)\n",
    "df_MMM_1w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Date',\n",
       " 'Time',\n",
       " 'Open',\n",
       " 'Close',\n",
       " 'High',\n",
       " 'Low',\n",
       " 'Volume',\n",
       " 'Symbol',\n",
       " '2_p_sma',\n",
       " 'macd_val',\n",
       " 'macd_avg',\n",
       " 'macd_diff',\n",
       " 'doji',\n",
       " 'engulfing',\n",
       " '5_RSI',\n",
       " '14_RSI']"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let us see what columns we have for the df_MMM_15m\n",
    "list(df_MMM_15m.columns.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Date',\n",
       " 'Open',\n",
       " 'Close',\n",
       " 'High',\n",
       " 'Low',\n",
       " 'Volume',\n",
       " 'Symbol',\n",
       " '2_p_sma',\n",
       " 'macd_val',\n",
       " 'macd_avg',\n",
       " 'macd_diff',\n",
       " 'doji',\n",
       " 'engulfing',\n",
       " '5_RSI',\n",
       " '14_RSI']"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let us see what columns we have for the df_MMM_1w\n",
    "list(df_MMM_1w.columns.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remember the List?\n",
    "# There are x types of columns where x = = 8 for now\n",
    "# 1. Indicators e.g. moving averages, slope, etc the are 100s of columns that are to contain indicator returns\n",
    "# 2. Profile Data e.g. CIK, Company name etc\n",
    "# 3. Accounting Data e.g. Revenues, cash flow, earnings\n",
    "# 4. Accounting Ratios e.g. Apply formulas to Accounting Data\n",
    "# 5. Propietary Data e.g. Data from Short Squeeze\n",
    "# 6. Missing Data e.g. Data obtained from Bloomberg\n",
    "# 7. Experimental Data e.g creating new symbols derived for current groups of symbols\n",
    "# 8. Predictive Data e.g. Using Blast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>date</th>\n",
       "      <th>period</th>\n",
       "      <th>currentRatio</th>\n",
       "      <th>quickRatio</th>\n",
       "      <th>cashRatio</th>\n",
       "      <th>daysOfSalesOutstanding</th>\n",
       "      <th>daysOfInventoryOutstanding</th>\n",
       "      <th>operatingCycle</th>\n",
       "      <th>daysOfPayablesOutstanding</th>\n",
       "      <th>...</th>\n",
       "      <th>priceToSalesRatio</th>\n",
       "      <th>priceEarningsRatio</th>\n",
       "      <th>priceToFreeCashFlowsRatio</th>\n",
       "      <th>priceToOperatingCashFlowsRatio</th>\n",
       "      <th>priceCashFlowRatio</th>\n",
       "      <th>priceEarningsToGrowthRatio</th>\n",
       "      <th>priceSalesRatio</th>\n",
       "      <th>dividendYield</th>\n",
       "      <th>enterpriseValueMultiple</th>\n",
       "      <th>priceFairValue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MMM</td>\n",
       "      <td>2022-03-31</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1.579108</td>\n",
       "      <td>0.893138</td>\n",
       "      <td>0.354786</td>\n",
       "      <td>199.057085</td>\n",
       "      <td>98.653129</td>\n",
       "      <td>147.735698</td>\n",
       "      <td>59.005387</td>\n",
       "      <td>...</td>\n",
       "      <td>9.650473</td>\n",
       "      <td>16.398003</td>\n",
       "      <td>145.151659</td>\n",
       "      <td>84.276977</td>\n",
       "      <td>84.276977</td>\n",
       "      <td>-6.367891</td>\n",
       "      <td>9.650473</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>45.791083</td>\n",
       "      <td>5.706900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MMM</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>Q4</td>\n",
       "      <td>1.704815</td>\n",
       "      <td>1.055340</td>\n",
       "      <td>0.505147</td>\n",
       "      <td>202.165583</td>\n",
       "      <td>95.498084</td>\n",
       "      <td>145.347132</td>\n",
       "      <td>57.356322</td>\n",
       "      <td>...</td>\n",
       "      <td>11.857814</td>\n",
       "      <td>19.066372</td>\n",
       "      <td>70.475838</td>\n",
       "      <td>50.932414</td>\n",
       "      <td>50.932414</td>\n",
       "      <td>-3.363853</td>\n",
       "      <td>11.857814</td>\n",
       "      <td>0.008304</td>\n",
       "      <td>52.882469</td>\n",
       "      <td>6.787152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MMM</td>\n",
       "      <td>2021-09-30</td>\n",
       "      <td>Q3</td>\n",
       "      <td>1.704826</td>\n",
       "      <td>1.105241</td>\n",
       "      <td>0.506279</td>\n",
       "      <td>200.664281</td>\n",
       "      <td>91.798887</td>\n",
       "      <td>141.277751</td>\n",
       "      <td>53.076448</td>\n",
       "      <td>...</td>\n",
       "      <td>11.370323</td>\n",
       "      <td>17.725494</td>\n",
       "      <td>66.409818</td>\n",
       "      <td>54.254766</td>\n",
       "      <td>54.254766</td>\n",
       "      <td>-3.096053</td>\n",
       "      <td>11.370323</td>\n",
       "      <td>0.008419</td>\n",
       "      <td>49.256670</td>\n",
       "      <td>7.031358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MMM</td>\n",
       "      <td>2021-06-30</td>\n",
       "      <td>Q2</td>\n",
       "      <td>1.731250</td>\n",
       "      <td>1.111335</td>\n",
       "      <td>0.497352</td>\n",
       "      <td>203.543575</td>\n",
       "      <td>92.345836</td>\n",
       "      <td>142.534663</td>\n",
       "      <td>55.899555</td>\n",
       "      <td>...</td>\n",
       "      <td>12.894305</td>\n",
       "      <td>18.931108</td>\n",
       "      <td>77.296740</td>\n",
       "      <td>61.157410</td>\n",
       "      <td>61.157410</td>\n",
       "      <td>-2.944839</td>\n",
       "      <td>12.894305</td>\n",
       "      <td>0.007435</td>\n",
       "      <td>51.274895</td>\n",
       "      <td>7.987544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MMM</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1.834868</td>\n",
       "      <td>1.190243</td>\n",
       "      <td>0.554347</td>\n",
       "      <td>198.644786</td>\n",
       "      <td>88.667403</td>\n",
       "      <td>137.648309</td>\n",
       "      <td>53.104972</td>\n",
       "      <td>...</td>\n",
       "      <td>12.637073</td>\n",
       "      <td>17.218401</td>\n",
       "      <td>81.168894</td>\n",
       "      <td>66.262284</td>\n",
       "      <td>66.262284</td>\n",
       "      <td>1.033104</td>\n",
       "      <td>12.637073</td>\n",
       "      <td>0.007671</td>\n",
       "      <td>49.813703</td>\n",
       "      <td>8.128687</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>MMM</td>\n",
       "      <td>1994-09-30</td>\n",
       "      <td>Q3</td>\n",
       "      <td>1.924565</td>\n",
       "      <td>0.973920</td>\n",
       "      <td>0.085250</td>\n",
       "      <td>285.311518</td>\n",
       "      <td>104.434706</td>\n",
       "      <td>174.785492</td>\n",
       "      <td>34.864154</td>\n",
       "      <td>...</td>\n",
       "      <td>6.094335</td>\n",
       "      <td>17.067713</td>\n",
       "      <td>80.001241</td>\n",
       "      <td>39.659899</td>\n",
       "      <td>39.659899</td>\n",
       "      <td>42.967707</td>\n",
       "      <td>6.094335</td>\n",
       "      <td>0.007947</td>\n",
       "      <td>30.794747</td>\n",
       "      <td>3.495550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>MMM</td>\n",
       "      <td>1994-06-30</td>\n",
       "      <td>Q2</td>\n",
       "      <td>1.993552</td>\n",
       "      <td>1.012603</td>\n",
       "      <td>0.090563</td>\n",
       "      <td>287.974549</td>\n",
       "      <td>103.257677</td>\n",
       "      <td>174.265100</td>\n",
       "      <td>36.248331</td>\n",
       "      <td>...</td>\n",
       "      <td>5.564394</td>\n",
       "      <td>15.298028</td>\n",
       "      <td>135.412218</td>\n",
       "      <td>50.820566</td>\n",
       "      <td>50.820566</td>\n",
       "      <td>1.223842</td>\n",
       "      <td>5.564394</td>\n",
       "      <td>0.008862</td>\n",
       "      <td>27.620263</td>\n",
       "      <td>3.195629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>MMM</td>\n",
       "      <td>1994-03-31</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1.847309</td>\n",
       "      <td>0.967222</td>\n",
       "      <td>0.106528</td>\n",
       "      <td>280.885187</td>\n",
       "      <td>102.785978</td>\n",
       "      <td>172.045339</td>\n",
       "      <td>36.614391</td>\n",
       "      <td>...</td>\n",
       "      <td>5.815732</td>\n",
       "      <td>17.257140</td>\n",
       "      <td>109.444244</td>\n",
       "      <td>48.446649</td>\n",
       "      <td>48.446649</td>\n",
       "      <td>2.323719</td>\n",
       "      <td>5.815732</td>\n",
       "      <td>0.008900</td>\n",
       "      <td>30.161887</td>\n",
       "      <td>3.308700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>MMM</td>\n",
       "      <td>1993-12-31</td>\n",
       "      <td>Q4</td>\n",
       "      <td>1.938757</td>\n",
       "      <td>0.995125</td>\n",
       "      <td>0.083486</td>\n",
       "      <td>313.635841</td>\n",
       "      <td>118.600439</td>\n",
       "      <td>195.935304</td>\n",
       "      <td>43.369923</td>\n",
       "      <td>...</td>\n",
       "      <td>6.663702</td>\n",
       "      <td>20.282350</td>\n",
       "      <td>125.421669</td>\n",
       "      <td>47.256637</td>\n",
       "      <td>47.256637</td>\n",
       "      <td>-2.151066</td>\n",
       "      <td>6.663702</td>\n",
       "      <td>0.007671</td>\n",
       "      <td>33.092153</td>\n",
       "      <td>3.563116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>MMM</td>\n",
       "      <td>1993-09-30</td>\n",
       "      <td>Q3</td>\n",
       "      <td>1.893361</td>\n",
       "      <td>0.984724</td>\n",
       "      <td>0.093420</td>\n",
       "      <td>318.129848</td>\n",
       "      <td>111.968504</td>\n",
       "      <td>190.411480</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.310027</td>\n",
       "      <td>17.377534</td>\n",
       "      <td>67.171874</td>\n",
       "      <td>35.890854</td>\n",
       "      <td>35.890854</td>\n",
       "      <td>-6.603463</td>\n",
       "      <td>6.310027</td>\n",
       "      <td>0.008149</td>\n",
       "      <td>30.508183</td>\n",
       "      <td>3.328061</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>115 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    symbol        date period  currentRatio  quickRatio  cashRatio  \\\n",
       "0      MMM  2022-03-31     Q1      1.579108    0.893138   0.354786   \n",
       "1      MMM  2021-12-31     Q4      1.704815    1.055340   0.505147   \n",
       "2      MMM  2021-09-30     Q3      1.704826    1.105241   0.506279   \n",
       "3      MMM  2021-06-30     Q2      1.731250    1.111335   0.497352   \n",
       "4      MMM  2021-03-31     Q1      1.834868    1.190243   0.554347   \n",
       "..     ...         ...    ...           ...         ...        ...   \n",
       "110    MMM  1994-09-30     Q3      1.924565    0.973920   0.085250   \n",
       "111    MMM  1994-06-30     Q2      1.993552    1.012603   0.090563   \n",
       "112    MMM  1994-03-31     Q1      1.847309    0.967222   0.106528   \n",
       "113    MMM  1993-12-31     Q4      1.938757    0.995125   0.083486   \n",
       "114    MMM  1993-09-30     Q3      1.893361    0.984724   0.093420   \n",
       "\n",
       "     daysOfSalesOutstanding  daysOfInventoryOutstanding  operatingCycle  \\\n",
       "0                199.057085                   98.653129      147.735698   \n",
       "1                202.165583                   95.498084      145.347132   \n",
       "2                200.664281                   91.798887      141.277751   \n",
       "3                203.543575                   92.345836      142.534663   \n",
       "4                198.644786                   88.667403      137.648309   \n",
       "..                      ...                         ...             ...   \n",
       "110              285.311518                  104.434706      174.785492   \n",
       "111              287.974549                  103.257677      174.265100   \n",
       "112              280.885187                  102.785978      172.045339   \n",
       "113              313.635841                  118.600439      195.935304   \n",
       "114              318.129848                  111.968504      190.411480   \n",
       "\n",
       "     daysOfPayablesOutstanding  ...  priceToSalesRatio  priceEarningsRatio  \\\n",
       "0                    59.005387  ...           9.650473           16.398003   \n",
       "1                    57.356322  ...          11.857814           19.066372   \n",
       "2                    53.076448  ...          11.370323           17.725494   \n",
       "3                    55.899555  ...          12.894305           18.931108   \n",
       "4                    53.104972  ...          12.637073           17.218401   \n",
       "..                         ...  ...                ...                 ...   \n",
       "110                  34.864154  ...           6.094335           17.067713   \n",
       "111                  36.248331  ...           5.564394           15.298028   \n",
       "112                  36.614391  ...           5.815732           17.257140   \n",
       "113                  43.369923  ...           6.663702           20.282350   \n",
       "114                  36.000000  ...           6.310027           17.377534   \n",
       "\n",
       "     priceToFreeCashFlowsRatio  priceToOperatingCashFlowsRatio  \\\n",
       "0                   145.151659                       84.276977   \n",
       "1                    70.475838                       50.932414   \n",
       "2                    66.409818                       54.254766   \n",
       "3                    77.296740                       61.157410   \n",
       "4                    81.168894                       66.262284   \n",
       "..                         ...                             ...   \n",
       "110                  80.001241                       39.659899   \n",
       "111                 135.412218                       50.820566   \n",
       "112                 109.444244                       48.446649   \n",
       "113                 125.421669                       47.256637   \n",
       "114                  67.171874                       35.890854   \n",
       "\n",
       "     priceCashFlowRatio  priceEarningsToGrowthRatio  priceSalesRatio  \\\n",
       "0             84.276977                   -6.367891         9.650473   \n",
       "1             50.932414                   -3.363853        11.857814   \n",
       "2             54.254766                   -3.096053        11.370323   \n",
       "3             61.157410                   -2.944839        12.894305   \n",
       "4             66.262284                    1.033104        12.637073   \n",
       "..                  ...                         ...              ...   \n",
       "110           39.659899                   42.967707         6.094335   \n",
       "111           50.820566                    1.223842         5.564394   \n",
       "112           48.446649                    2.323719         5.815732   \n",
       "113           47.256637                   -2.151066         6.663702   \n",
       "114           35.890854                   -6.603463         6.310027   \n",
       "\n",
       "     dividendYield  enterpriseValueMultiple  priceFairValue  \n",
       "0         0.010000                45.791083        5.706900  \n",
       "1         0.008304                52.882469        6.787152  \n",
       "2         0.008419                49.256670        7.031358  \n",
       "3         0.007435                51.274895        7.987544  \n",
       "4         0.007671                49.813703        8.128687  \n",
       "..             ...                      ...             ...  \n",
       "110       0.007947                30.794747        3.495550  \n",
       "111       0.008862                27.620263        3.195629  \n",
       "112       0.008900                30.161887        3.308700  \n",
       "113       0.007671                33.092153        3.563116  \n",
       "114       0.008149                30.508183        3.328061  \n",
       "\n",
       "[115 rows x 57 columns]"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3. Accounting Data e.g. Revenues, cash flow, earnings\n",
    "# This data is retrived from financialmodelingprep\n",
    "\n",
    "\n",
    "url = \"https://financialmodelingprep.com/api/v3/ratios/MMM?period=quarter&limit=140&apikey=aa8b4631b2ad1b2704741d1a2d6a2611\"\n",
    "\n",
    "response = requests.get(url)\n",
    "data = response.json()\n",
    "df_MMM_accounting_all_data = pd.DataFrame(data)\n",
    "df_MMM_accounting_all_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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