1-alphavantage_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Alphavantage Intraday\n",
    "* API for \"real time\" stock data\n",
    "* Freeium model - sign up fro free account to get API key\n",
    "* Can make API calls directly or install the helper library:\n",
    "pip install alpha_vantage from the command line\n",
    "\n",
    "#### https://alphavantage.co"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Set up Environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from alpha_vantage.timeseries import TimeSeries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Store API Key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace with your own API key\n",
    "key = open('../1-alphavantage.txt').read()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Create TimeSeries Object and Make API Call"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts = TimeSeries(key, output_format='pandas')\n",
    "data, meta = ts.get_intraday('TSLA', interval='1min', outputsize='full')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Examine Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'1. Information': 'Intraday (1min) open, high, low, close prices and volume',\n",
       " '2. Symbol': 'TSLA',\n",
       " '3. Last Refreshed': '2021-01-07 20:00:00',\n",
       " '4. Interval': '1min',\n",
       " '5. Output Size': 'Full size',\n",
       " '6. Time Zone': 'US/Eastern'}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 6459 entries, 2021-01-07 20:00:00 to 2020-12-28 04:01:00\n",
      "Data columns (total 5 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   1. open    6459 non-null   float64\n",
      " 1   2. high    6459 non-null   float64\n",
      " 2   3. low     6459 non-null   float64\n",
      " 3   4. close   6459 non-null   float64\n",
      " 4   5. volume  6459 non-null   float64\n",
      "dtypes: float64(5)\n",
      "memory usage: 302.8 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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",
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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>1. open</th>\n",
       "      <th>2. high</th>\n",
       "      <th>3. low</th>\n",
       "      <th>4. close</th>\n",
       "      <th>5. volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-07 20:00:00</th>\n",
       "      <td>829.02</td>\n",
       "      <td>829.5000</td>\n",
       "      <td>828.82</td>\n",
       "      <td>829.50</td>\n",
       "      <td>14315.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07 19:59:00</th>\n",
       "      <td>829.45</td>\n",
       "      <td>829.4500</td>\n",
       "      <td>829.00</td>\n",
       "      <td>829.14</td>\n",
       "      <td>10706.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07 19:58:00</th>\n",
       "      <td>830.00</td>\n",
       "      <td>830.0099</td>\n",
       "      <td>829.50</td>\n",
       "      <td>829.50</td>\n",
       "      <td>9655.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07 19:57:00</th>\n",
       "      <td>830.50</td>\n",
       "      <td>830.5000</td>\n",
       "      <td>829.84</td>\n",
       "      <td>830.00</td>\n",
       "      <td>5355.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07 19:56:00</th>\n",
       "      <td>830.88</td>\n",
       "      <td>830.9500</td>\n",
       "      <td>830.60</td>\n",
       "      <td>830.90</td>\n",
       "      <td>3087.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     1. open   2. high  3. low  4. close  5. volume\n",
       "date                                                               \n",
       "2021-01-07 20:00:00   829.02  829.5000  828.82    829.50    14315.0\n",
       "2021-01-07 19:59:00   829.45  829.4500  829.00    829.14    10706.0\n",
       "2021-01-07 19:58:00   830.00  830.0099  829.50    829.50     9655.0\n",
       "2021-01-07 19:57:00   830.50  830.5000  829.84    830.00     5355.0\n",
       "2021-01-07 19:56:00   830.88  830.9500  830.60    830.90     3087.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1186c0e50>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data['4. close'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Rename Columns and Add Separate Date and Time Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['open', 'high', 'low', 'close', 'volume']\n",
    "data.columns = columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['TradeDate'] = data.index.date\n",
    "data['time'] = data.index.time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>TradeDate</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-31 20:00:00</th>\n",
       "      <td>704.69</td>\n",
       "      <td>704.70</td>\n",
       "      <td>704.50</td>\n",
       "      <td>704.50</td>\n",
       "      <td>2435.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>20:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 19:59:00</th>\n",
       "      <td>704.50</td>\n",
       "      <td>704.70</td>\n",
       "      <td>704.50</td>\n",
       "      <td>704.70</td>\n",
       "      <td>5691.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>19:59:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 19:58:00</th>\n",
       "      <td>704.48</td>\n",
       "      <td>704.50</td>\n",
       "      <td>704.48</td>\n",
       "      <td>704.50</td>\n",
       "      <td>2642.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>19:58:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 19:57:00</th>\n",
       "      <td>704.40</td>\n",
       "      <td>704.47</td>\n",
       "      <td>704.40</td>\n",
       "      <td>704.40</td>\n",
       "      <td>1453.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>19:57:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 19:54:00</th>\n",
       "      <td>704.35</td>\n",
       "      <td>704.47</td>\n",
       "      <td>704.35</td>\n",
       "      <td>704.35</td>\n",
       "      <td>2701.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>19:54:00</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>2020-12-31 04:07:00</th>\n",
       "      <td>692.00</td>\n",
       "      <td>692.00</td>\n",
       "      <td>692.00</td>\n",
       "      <td>692.00</td>\n",
       "      <td>718.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>04:07:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 04:06:00</th>\n",
       "      <td>692.70</td>\n",
       "      <td>692.70</td>\n",
       "      <td>692.70</td>\n",
       "      <td>692.70</td>\n",
       "      <td>444.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>04:06:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 04:04:00</th>\n",
       "      <td>693.62</td>\n",
       "      <td>693.62</td>\n",
       "      <td>693.20</td>\n",
       "      <td>693.20</td>\n",
       "      <td>2586.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>04:04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 04:02:00</th>\n",
       "      <td>693.50</td>\n",
       "      <td>693.50</td>\n",
       "      <td>693.50</td>\n",
       "      <td>693.50</td>\n",
       "      <td>910.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>04:02:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 04:01:00</th>\n",
       "      <td>693.50</td>\n",
       "      <td>693.50</td>\n",
       "      <td>693.00</td>\n",
       "      <td>693.00</td>\n",
       "      <td>847.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>04:01:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>768 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       open    high     low   close  volume   TradeDate  \\\n",
       "date                                                                      \n",
       "2020-12-31 20:00:00  704.69  704.70  704.50  704.50  2435.0  2020-12-31   \n",
       "2020-12-31 19:59:00  704.50  704.70  704.50  704.70  5691.0  2020-12-31   \n",
       "2020-12-31 19:58:00  704.48  704.50  704.48  704.50  2642.0  2020-12-31   \n",
       "2020-12-31 19:57:00  704.40  704.47  704.40  704.40  1453.0  2020-12-31   \n",
       "2020-12-31 19:54:00  704.35  704.47  704.35  704.35  2701.0  2020-12-31   \n",
       "...                     ...     ...     ...     ...     ...         ...   \n",
       "2020-12-31 04:07:00  692.00  692.00  692.00  692.00   718.0  2020-12-31   \n",
       "2020-12-31 04:06:00  692.70  692.70  692.70  692.70   444.0  2020-12-31   \n",
       "2020-12-31 04:04:00  693.62  693.62  693.20  693.20  2586.0  2020-12-31   \n",
       "2020-12-31 04:02:00  693.50  693.50  693.50  693.50   910.0  2020-12-31   \n",
       "2020-12-31 04:01:00  693.50  693.50  693.00  693.00   847.0  2020-12-31   \n",
       "\n",
       "                         time  \n",
       "date                           \n",
       "2020-12-31 20:00:00  20:00:00  \n",
       "2020-12-31 19:59:00  19:59:00  \n",
       "2020-12-31 19:58:00  19:58:00  \n",
       "2020-12-31 19:57:00  19:57:00  \n",
       "2020-12-31 19:54:00  19:54:00  \n",
       "...                       ...  \n",
       "2020-12-31 04:07:00  04:07:00  \n",
       "2020-12-31 04:06:00  04:06:00  \n",
       "2020-12-31 04:04:00  04:04:00  \n",
       "2020-12-31 04:02:00  04:02:00  \n",
       "2020-12-31 04:01:00  04:01:00  \n",
       "\n",
       "[768 rows x 7 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc['2020-12-31']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 3128 entries, 2020-12-28 09:30:00 to 2021-01-07 16:00:00\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   open       3128 non-null   float64\n",
      " 1   high       3128 non-null   float64\n",
      " 2   low        3128 non-null   float64\n",
      " 3   close      3128 non-null   float64\n",
      " 4   volume     3128 non-null   float64\n",
      " 5   TradeDate  3128 non-null   object \n",
      " 6   time       3128 non-null   object \n",
      "dtypes: float64(5), object(2)\n",
      "memory usage: 195.5+ KB\n"
     ]
    }
   ],
   "source": [
    "market = data.between_time('09:30:00', '16:00:00').copy()\n",
    "market.sort_index(inplace=True)\n",
    "market.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>low</th>\n",
       "      <th>high</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TradeDate</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-28</th>\n",
       "      <td>660.8000</td>\n",
       "      <td>681.4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-29</th>\n",
       "      <td>655.0000</td>\n",
       "      <td>669.9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>668.3603</td>\n",
       "      <td>696.6000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>691.1200</td>\n",
       "      <td>718.7200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>717.1895</td>\n",
       "      <td>744.4899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05</th>\n",
       "      <td>719.2000</td>\n",
       "      <td>740.8400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-06</th>\n",
       "      <td>749.1000</td>\n",
       "      <td>774.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07</th>\n",
       "      <td>775.2000</td>\n",
       "      <td>816.9900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 low      high\n",
       "TradeDate                     \n",
       "2020-12-28  660.8000  681.4000\n",
       "2020-12-29  655.0000  669.9000\n",
       "2020-12-30  668.3603  696.6000\n",
       "2020-12-31  691.1200  718.7200\n",
       "2021-01-04  717.1895  744.4899\n",
       "2021-01-05  719.2000  740.8400\n",
       "2021-01-06  749.1000  774.0000\n",
       "2021-01-07  775.2000  816.9900"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "market.groupby('TradeDate').agg({'low':min, 'high':max})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>TradeDate</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-28 10:49:00</th>\n",
       "      <td>661.025</td>\n",
       "      <td>663.8800</td>\n",
       "      <td>660.8000</td>\n",
       "      <td>663.8800</td>\n",
       "      <td>169251.0</td>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>10:49:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-29 10:15:00</th>\n",
       "      <td>657.000</td>\n",
       "      <td>658.5800</td>\n",
       "      <td>655.0000</td>\n",
       "      <td>656.0600</td>\n",
       "      <td>162237.0</td>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>10:15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30 09:41:00</th>\n",
       "      <td>669.685</td>\n",
       "      <td>671.6300</td>\n",
       "      <td>668.3603</td>\n",
       "      <td>671.3301</td>\n",
       "      <td>141286.0</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>09:41:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 09:57:00</th>\n",
       "      <td>692.670</td>\n",
       "      <td>693.1200</td>\n",
       "      <td>691.1200</td>\n",
       "      <td>691.7961</td>\n",
       "      <td>175834.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>09:57:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04 09:31:00</th>\n",
       "      <td>719.460</td>\n",
       "      <td>721.4900</td>\n",
       "      <td>717.1895</td>\n",
       "      <td>717.6900</td>\n",
       "      <td>871163.0</td>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>09:31:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05 09:34:00</th>\n",
       "      <td>720.530</td>\n",
       "      <td>722.9109</td>\n",
       "      <td>719.2000</td>\n",
       "      <td>719.9714</td>\n",
       "      <td>209148.0</td>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>09:34:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-06 10:01:00</th>\n",
       "      <td>751.520</td>\n",
       "      <td>752.2772</td>\n",
       "      <td>749.1000</td>\n",
       "      <td>751.4219</td>\n",
       "      <td>349451.0</td>\n",
       "      <td>2021-01-06</td>\n",
       "      <td>10:01:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07 09:32:00</th>\n",
       "      <td>776.660</td>\n",
       "      <td>777.7000</td>\n",
       "      <td>775.2000</td>\n",
       "      <td>776.2500</td>\n",
       "      <td>236797.0</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>09:32:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        open      high       low     close    volume  \\\n",
       "date                                                                   \n",
       "2020-12-28 10:49:00  661.025  663.8800  660.8000  663.8800  169251.0   \n",
       "2020-12-29 10:15:00  657.000  658.5800  655.0000  656.0600  162237.0   \n",
       "2020-12-30 09:41:00  669.685  671.6300  668.3603  671.3301  141286.0   \n",
       "2020-12-31 09:57:00  692.670  693.1200  691.1200  691.7961  175834.0   \n",
       "2021-01-04 09:31:00  719.460  721.4900  717.1895  717.6900  871163.0   \n",
       "2021-01-05 09:34:00  720.530  722.9109  719.2000  719.9714  209148.0   \n",
       "2021-01-06 10:01:00  751.520  752.2772  749.1000  751.4219  349451.0   \n",
       "2021-01-07 09:32:00  776.660  777.7000  775.2000  776.2500  236797.0   \n",
       "\n",
       "                      TradeDate      time  \n",
       "date                                       \n",
       "2020-12-28 10:49:00  2020-12-28  10:49:00  \n",
       "2020-12-29 10:15:00  2020-12-29  10:15:00  \n",
       "2020-12-30 09:41:00  2020-12-30  09:41:00  \n",
       "2020-12-31 09:57:00  2020-12-31  09:57:00  \n",
       "2021-01-04 09:31:00  2021-01-04  09:31:00  \n",
       "2021-01-05 09:34:00  2021-01-05  09:34:00  \n",
       "2021-01-06 10:01:00  2021-01-06  10:01:00  \n",
       "2021-01-07 09:32:00  2021-01-07  09:32:00  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "market.loc[market.groupby('TradeDate')['low'].idxmin()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
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       "      <th>TradeDate</th>\n",
       "      <th>time</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-28 09:43:00</th>\n",
       "      <td>679.8350</td>\n",
       "      <td>681.4000</td>\n",
       "      <td>678.0000</td>\n",
       "      <td>678.8728</td>\n",
       "      <td>416362.0</td>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>09:43:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-29 09:49:00</th>\n",
       "      <td>668.8599</td>\n",
       "      <td>669.9000</td>\n",
       "      <td>667.2000</td>\n",
       "      <td>667.7950</td>\n",
       "      <td>154742.0</td>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>09:49:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30 14:44:00</th>\n",
       "      <td>695.6699</td>\n",
       "      <td>696.6000</td>\n",
       "      <td>695.5801</td>\n",
       "      <td>696.1716</td>\n",
       "      <td>166469.0</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>14:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31 11:38:00</th>\n",
       "      <td>717.5985</td>\n",
       "      <td>718.7200</td>\n",
       "      <td>717.4100</td>\n",
       "      <td>718.4900</td>\n",
       "      <td>239463.0</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>11:38:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04 10:33:00</th>\n",
       "      <td>741.7239</td>\n",
       "      <td>744.4899</td>\n",
       "      <td>741.6500</td>\n",
       "      <td>743.8500</td>\n",
       "      <td>295133.0</td>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>10:33:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05 11:34:00</th>\n",
       "      <td>739.5500</td>\n",
       "      <td>740.8400</td>\n",
       "      <td>739.2000</td>\n",
       "      <td>740.3900</td>\n",
       "      <td>107022.0</td>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>11:34:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-06 14:07:00</th>\n",
       "      <td>772.7913</td>\n",
       "      <td>774.0000</td>\n",
       "      <td>772.6700</td>\n",
       "      <td>773.7541</td>\n",
       "      <td>130661.0</td>\n",
       "      <td>2021-01-06</td>\n",
       "      <td>14:07:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07 15:55:00</th>\n",
       "      <td>816.4611</td>\n",
       "      <td>816.9900</td>\n",
       "      <td>815.4400</td>\n",
       "      <td>815.9050</td>\n",
       "      <td>240217.0</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>15:55:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         open      high       low     close    volume  \\\n",
       "date                                                                    \n",
       "2020-12-28 09:43:00  679.8350  681.4000  678.0000  678.8728  416362.0   \n",
       "2020-12-29 09:49:00  668.8599  669.9000  667.2000  667.7950  154742.0   \n",
       "2020-12-30 14:44:00  695.6699  696.6000  695.5801  696.1716  166469.0   \n",
       "2020-12-31 11:38:00  717.5985  718.7200  717.4100  718.4900  239463.0   \n",
       "2021-01-04 10:33:00  741.7239  744.4899  741.6500  743.8500  295133.0   \n",
       "2021-01-05 11:34:00  739.5500  740.8400  739.2000  740.3900  107022.0   \n",
       "2021-01-06 14:07:00  772.7913  774.0000  772.6700  773.7541  130661.0   \n",
       "2021-01-07 15:55:00  816.4611  816.9900  815.4400  815.9050  240217.0   \n",
       "\n",
       "                      TradeDate      time  \n",
       "date                                       \n",
       "2020-12-28 09:43:00  2020-12-28  09:43:00  \n",
       "2020-12-29 09:49:00  2020-12-29  09:49:00  \n",
       "2020-12-30 14:44:00  2020-12-30  14:44:00  \n",
       "2020-12-31 11:38:00  2020-12-31  11:38:00  \n",
       "2021-01-04 10:33:00  2021-01-04  10:33:00  \n",
       "2021-01-05 11:34:00  2021-01-05  11:34:00  \n",
       "2021-01-06 14:07:00  2021-01-06  14:07:00  \n",
       "2021-01-07 15:55:00  2021-01-07  15:55:00  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "market.loc[market.groupby('TradeDate')['high'].idxmax()]"
   ]
  },
  {
   "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,
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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