{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Historical Prices With the OpenBB Platform\n",
    "\n",
    "This notebook demonstrates some of the ways to approach loading historical price data using the OpenBB Platform.  The action is in the Equity module; but first, we need to initialize the notebook with the import statements block.\n",
    "\n",
    "## Import Statements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta\n",
    "\n",
    "import pandas as pd\n",
    "from openbb import obb\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Equity Module\n",
    "\n",
    "Historical market prices typically come in the form of OHLC+V - open, high, low, close, volume.  There may be additional fields returned by a provider, but those are the expected columns.  Granularity and amount of historical data will vary by provider and subscription status.  Visit their websites to understand what your entitlements are.\n",
    "\n",
    "### openbb.equity.price.historical()\n",
    "\n",
    "- This endpoint has the most number of providers out of any function. At the time of writing, choices are:\n",
    "\n",
    "['alpha_vantage', 'cboe', 'fmp', 'intrinio', 'polygon', 'tiingo', 'yfinance']\n",
    "\n",
    "- Common parameters have been standardized across all souces, `start_date`, `end_date`, `interval`.\n",
    "\n",
    "- The default interval will be `1d`.\n",
    "\n",
    "- The depth of historical data and choices for granularity will vary by provider and subscription status.  Refer to the website and documentation of each source understand your specific entitlements.\n",
    "\n",
    "- For demonstration purposes, we will use the `openbb-yfinance` data extension."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>dividends</th>\n",
       "      <th>stock splits</th>\n",
       "      <th>capital gains</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-11-22</th>\n",
       "      <td>396.63</td>\n",
       "      <td>400.07</td>\n",
       "      <td>395.15</td>\n",
       "      <td>399.9</td>\n",
       "      <td>60429000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low  close    volume  dividends  stock splits  \\\n",
       "date                                                                           \n",
       "2022-11-22  396.63  400.07  395.15  399.9  60429000        0.0           0.0   \n",
       "\n",
       "            capital gains  \n",
       "date                       \n",
       "2022-11-22            0.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_daily = obb.equity.price.historical(symbol = \"spy\", provider=\"yfinance\")\n",
    "df_daily.to_df().head(1)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To load the entire history available from a source, pick a starting date well beyond what it might be. For example, `1900-01-01`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>dividends</th>\n",
       "      <th>stock splits</th>\n",
       "      <th>capital gains</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1993-01-29</th>\n",
       "      <td>43.97</td>\n",
       "      <td>43.97</td>\n",
       "      <td>43.75</td>\n",
       "      <td>43.94</td>\n",
       "      <td>1003200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             open   high    low  close   volume  dividends  stock splits  \\\n",
       "date                                                                       \n",
       "1993-01-29  43.97  43.97  43.75  43.94  1003200        0.0           0.0   \n",
       "\n",
       "            capital gains  \n",
       "date                       \n",
       "1993-01-29            0.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_daily = obb.equity.price.historical(symbol = \"spy\", start_date = \"1990-01-01\", provider=\"yfinance\").to_df()\n",
    "df_daily.head(1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Intervals\n",
    "\n",
    "The intervals are entered according to this pattern:\n",
    "\n",
    "- `1m` = One Minute\n",
    "- `1h` = One Hour\n",
    "- `1d` = One Day\n",
    "- `1W` = One Week\n",
    "- `1M` = One Month\n",
    "\n",
    "The date for monthly value is the first or last, depending on the provider.  This can be easily resampled from daily data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>dividends</th>\n",
       "      <th>stock splits</th>\n",
       "      <th>capital gains</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-10-01</th>\n",
       "      <td>426.62</td>\n",
       "      <td>438.14</td>\n",
       "      <td>409.21</td>\n",
       "      <td>418.20</td>\n",
       "      <td>1999149700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>419.20</td>\n",
       "      <td>456.38</td>\n",
       "      <td>418.65</td>\n",
       "      <td>455.02</td>\n",
       "      <td>1161239576</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close      volume  dividends  \\\n",
       "date                                                                \n",
       "2023-10-01  426.62  438.14  409.21  418.20  1999149700        0.0   \n",
       "2023-11-01  419.20  456.38  418.65  455.02  1161239576        0.0   \n",
       "\n",
       "            stock splits  capital gains  \n",
       "date                                     \n",
       "2023-10-01           0.0            0.0  \n",
       "2023-11-01           0.0            0.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_monthly = obb.equity.price.historical(\"spy\", start_date=\"1990-01-01\", interval=\"1M\", provider=\"yfinance\").to_df()\n",
    "df_monthly.tail(2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Resample a Time Series\n",
    "\n",
    "`yfinance` returns the monthly data for the first day of each month.  Let's resample it to take from the last, using the daily information captured in the previous cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</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",
       "    </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>1993-01-31</th>\n",
       "      <td>43.97</td>\n",
       "      <td>43.97</td>\n",
       "      <td>43.75</td>\n",
       "      <td>43.94</td>\n",
       "      <td>1003200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-02-28</th>\n",
       "      <td>43.97</td>\n",
       "      <td>45.12</td>\n",
       "      <td>42.81</td>\n",
       "      <td>44.41</td>\n",
       "      <td>5417600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-03-31</th>\n",
       "      <td>44.56</td>\n",
       "      <td>45.84</td>\n",
       "      <td>44.22</td>\n",
       "      <td>45.19</td>\n",
       "      <td>3019200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-04-30</th>\n",
       "      <td>45.25</td>\n",
       "      <td>45.25</td>\n",
       "      <td>43.28</td>\n",
       "      <td>44.03</td>\n",
       "      <td>2697200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-05-31</th>\n",
       "      <td>44.09</td>\n",
       "      <td>45.66</td>\n",
       "      <td>43.84</td>\n",
       "      <td>45.22</td>\n",
       "      <td>1808000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-31</th>\n",
       "      <td>442.92</td>\n",
       "      <td>459.44</td>\n",
       "      <td>437.06</td>\n",
       "      <td>457.79</td>\n",
       "      <td>1374632400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>456.27</td>\n",
       "      <td>457.25</td>\n",
       "      <td>433.01</td>\n",
       "      <td>450.35</td>\n",
       "      <td>1754764700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>453.17</td>\n",
       "      <td>453.67</td>\n",
       "      <td>422.29</td>\n",
       "      <td>427.48</td>\n",
       "      <td>1588673200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>426.62</td>\n",
       "      <td>438.14</td>\n",
       "      <td>409.21</td>\n",
       "      <td>418.20</td>\n",
       "      <td>1999149700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>419.20</td>\n",
       "      <td>456.38</td>\n",
       "      <td>418.65</td>\n",
       "      <td>455.02</td>\n",
       "      <td>1214703500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>371 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close      volume\n",
       "date                                                  \n",
       "1993-01-31   43.97   43.97   43.75   43.94     1003200\n",
       "1993-02-28   43.97   45.12   42.81   44.41     5417600\n",
       "1993-03-31   44.56   45.84   44.22   45.19     3019200\n",
       "1993-04-30   45.25   45.25   43.28   44.03     2697200\n",
       "1993-05-31   44.09   45.66   43.84   45.22     1808000\n",
       "...            ...     ...     ...     ...         ...\n",
       "2023-07-31  442.92  459.44  437.06  457.79  1374632400\n",
       "2023-08-31  456.27  457.25  433.01  450.35  1754764700\n",
       "2023-09-30  453.17  453.67  422.29  427.48  1588673200\n",
       "2023-10-31  426.62  438.14  409.21  418.20  1999149700\n",
       "2023-11-30  419.20  456.38  418.65  455.02  1214703500\n",
       "\n",
       "[371 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    df_daily[[\"open\", \"high\", \"low\", \"close\", \"volume\"]]\n",
    "    .resample(\"M\")\n",
    "    .agg(\n",
    "        {\"open\": \"first\", \"high\": \"max\", \"low\": \"min\", \"close\": \"last\", \"volume\": \"sum\"}\n",
    "    )\n",
    ")\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The block below packs an object with most intervals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['one', 'five', 'fifteen', 'thirty', 'sixty', 'daily', 'weekly', 'monthly'])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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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>dividends</th>\n",
       "      <th>stock splits</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",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-11-13</th>\n",
       "      <td>439.23</td>\n",
       "      <td>451.42</td>\n",
       "      <td>438.42</td>\n",
       "      <td>450.79</td>\n",
       "      <td>376539600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>450.53</td>\n",
       "      <td>456.38</td>\n",
       "      <td>450.52</td>\n",
       "      <td>455.02</td>\n",
       "      <td>233751276</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open    high     low   close     volume  dividends  \\\n",
       "date                                                               \n",
       "2023-11-13  439.23  451.42  438.42  450.79  376539600        0.0   \n",
       "2023-11-20  450.53  456.38  450.52  455.02  233751276        0.0   \n",
       "\n",
       "            stock splits  capital gains  \n",
       "date                                     \n",
       "2023-11-13             0              0  \n",
       "2023-11-20             0              0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class HistoricalPrices:\n",
    "    def __init__(self, symbol, start_date, end_date, provider, **kwargs) -> None:\n",
    "        self.one: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"1m\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.five: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"5m\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.fifteen: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"15m\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.thirty: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"30m\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.sixty: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"60m\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.daily: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"1d\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.weekly: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"1W\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "        self.monthly: pd.DataFrame = obb.equity.price.historical(\n",
    "            symbol=symbol, start_date=start_date, end_date=end_date, interval = \"1M\", provider=provider, **kwargs\n",
    "        ).to_df().convert_dtypes()\n",
    "\n",
    "def load_historical(\n",
    "    symbol: str = \"\",\n",
    "    start_date = None,\n",
    "    end_date = None,\n",
    "    provider = None,\n",
    "    **kwargs\n",
    ") -> HistoricalPrices:\n",
    "\n",
    "    if symbol == \"\":\n",
    "        display(\"Please enter a ticker symbol\")\n",
    "    if provider is None:\n",
    "        provider = \"yfinance\"\n",
    "    prices = HistoricalPrices(symbol, start_date, end_date, provider, **kwargs)\n",
    "\n",
    "    return prices\n",
    "\n",
    "prices = load_historical(\"spy\")\n",
    "display(prices.__dict__.keys())\n",
    "prices.weekly.tail(2)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To demonstrate the difference between sources, let's compare values for daily volume from several sources."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>AV Volume</th>\n",
       "      <th>FMP Volume</th>\n",
       "      <th>Intrinio Volume</th>\n",
       "      <th>Yahoo Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-11-09</th>\n",
       "      <td>83174417.0</td>\n",
       "      <td>83071417</td>\n",
       "      <td>83174417.0</td>\n",
       "      <td>83174400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-10</th>\n",
       "      <td>89558054.0</td>\n",
       "      <td>89558054</td>\n",
       "      <td>89558054.0</td>\n",
       "      <td>89462200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-13</th>\n",
       "      <td>52236068.0</td>\n",
       "      <td>52192568</td>\n",
       "      <td>52236068.0</td>\n",
       "      <td>52236100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-14</th>\n",
       "      <td>97176935.0</td>\n",
       "      <td>97130503</td>\n",
       "      <td>97176935.0</td>\n",
       "      <td>97176900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-15</th>\n",
       "      <td>77327573.0</td>\n",
       "      <td>77327573</td>\n",
       "      <td>77327573.0</td>\n",
       "      <td>77327600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-16</th>\n",
       "      <td>66665797.0</td>\n",
       "      <td>66654468</td>\n",
       "      <td>66665797.0</td>\n",
       "      <td>66665800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-17</th>\n",
       "      <td>83193902.0</td>\n",
       "      <td>83193902</td>\n",
       "      <td>83193902.0</td>\n",
       "      <td>83133200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>70055633.0</td>\n",
       "      <td>69614633</td>\n",
       "      <td>70055633.0</td>\n",
       "      <td>69936200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>49244639.0</td>\n",
       "      <td>49244639</td>\n",
       "      <td>49244639.0</td>\n",
       "      <td>49244600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>59446573.0</td>\n",
       "      <td>59313820</td>\n",
       "      <td>58205780.0</td>\n",
       "      <td>59394900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             AV Volume  FMP Volume  Intrinio Volume  Yahoo Volume\n",
       "date                                                             \n",
       "2023-11-09  83174417.0    83071417       83174417.0      83174400\n",
       "2023-11-10  89558054.0    89558054       89558054.0      89462200\n",
       "2023-11-13  52236068.0    52192568       52236068.0      52236100\n",
       "2023-11-14  97176935.0    97130503       97176935.0      97176900\n",
       "2023-11-15  77327573.0    77327573       77327573.0      77327600\n",
       "2023-11-16  66665797.0    66654468       66665797.0      66665800\n",
       "2023-11-17  83193902.0    83193902       83193902.0      83133200\n",
       "2023-11-20  70055633.0    69614633       70055633.0      69936200\n",
       "2023-11-21  49244639.0    49244639       49244639.0      49244600\n",
       "2023-11-22  59446573.0    59313820       58205780.0      59394900"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Collect the data\n",
    "\n",
    "yahoo = obb.equity.price.historical(\"spy\", provider=\"yfinance\").to_df()\n",
    "alphavantage = obb.equity.price.historical(\"spy\", provider = \"alpha_vantage\").to_df()\n",
    "intrinio = obb.equity.price.historical(\"spy\", provider=\"intrinio\").to_df()\n",
    "fmp = obb.equity.price.historical(\"spy\", provider=\"fmp\").to_df()\n",
    "\n",
    "# Make a new DataFrame with just the volume columns\n",
    "compare = pd.DataFrame()\n",
    "compare[\"AV Volume\"] = alphavantage[\"volume\"].tail(10)\n",
    "compare[\"FMP Volume\"] = fmp[\"volume\"].tail(10)\n",
    "compare[\"Intrinio Volume\"] = intrinio[\"volume\"].tail(10)\n",
    "compare[\"Yahoo Volume\"] = yahoo[\"volume\"].tail(10)\n",
    "\n",
    "compare\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other Types of Symbols\n",
    "\n",
    "Other types of assets and ticker symbols can be loaded from `obb.equity.price.historical()`, below are some examples but not an exhaustive list.\n",
    "\n",
    "### Share Classes\n",
    "\n",
    "Some sources use `-` as the distinction between a share class, e.g., `BRK-A` and `BRK-B`. Other formats include:\n",
    "\n",
    "- A period: `BRK.A`\n",
    "- A slash: `BRK/A`\n",
    "- No separator, the share class becomes the fourth or fifth letter.\n",
    "\n",
    "```python\n",
    "obb.equity.price.historical(\"brk.b\", provider=\"polygon\")\n",
    "```\n",
    "\n",
    "```python\n",
    "obb.equity.price.historical(\"brk-b\", provider=\"fmp\")\n",
    "```\n",
    "\n",
    "While some providers handle the different formats on their end, others do not. This is something to consider when no results are returned from one source. Some may even use a combination, or accept multiple variations. Sometimes there is no real logic behind the additional characters, `GOOGL` vs. `GOOG`. These are known unknown variables of ticker symbology, what's good for one source may return errors from another. \n",
    "\n",
    "### Regional Identifiers\n",
    "\n",
    "With providers supporting market data from multiple jurisdictions, the most common method for requesting data outside of US-listings is to append a suffix to the ticker symbol (e.g., `RELIANCE.NS` for Indian equities). Formats may be unique to a provider, so it is best to review the source's documentation for an overview of their specific conventions. [This page](https://help.yahoo.com/kb/SLN2310.html) on Yahoo describes how they format symbols, which many others follow to some degree.\n",
    "\n",
    "### Indexes\n",
    "\n",
    "Sources will have their own treatment of these symbols, some examples are:\n",
    "\n",
    "- YahooFinance/FMP/CBOE: ^RUT\n",
    "- Polygon: I:NDX\n",
    "\n",
    "### Currencies\n",
    "\n",
    "FX symbols face the same dilemna as share classes, there are several variations of the same symbol.\n",
    "\n",
    "- YahooFinance: `EURUSD=X`\n",
    "- Polygon: `C:EURUSD`\n",
    "- AlphaVantage/FMP: `EURUSD`\n",
    "\n",
    "**The symbol prefixes are handled internally when `obb.currency.price.historical()` is used to enter a pair with no extra characters.**\n",
    "\n",
    "### Crypto\n",
    "\n",
    "Similar, but different to FX tickers.\n",
    "\n",
    "- YahooFinance: `BTC-USD`\n",
    "- Polygon: `X:BTCUSD`\n",
    "- AlphaVantage/FMP: `BTCUSD`\n",
    "\n",
    "**The symbol prefixes are handled internally when `obb.crypto.price.historical()` is used to enter a pair with no extra characters and placing the fiat currency second.**\n",
    "\n",
    "### Futures\n",
    "\n",
    "Historical prices for active contracts, and the continuation chart, can be fetched via `yfinance`.\n",
    "\n",
    "- Continuous front-month: `CL=F`\n",
    "- December 2023 contract: `CLZ24.NYM`\n",
    "- March 2024 contract: `CLH24.NYM`\n",
    "\n",
    "Individual contracts will require knowing which of the CME venues the future is listed on. `[\"NYM\", \"NYB\", \"CME\", \"CBT\"]`.\n",
    "\n",
    "### Options\n",
    "\n",
    "Individual options contracts are also loadable from `openbb.equity.price.historical()`.\n",
    "\n",
    "- YahooFinance: `SPY241220P00400000`\n",
    "- Polygon: `O:SPY241220P00400000`"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These examples represent only a few methods for fetching historical price data.  Explore the contents of each module to find more!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>dividends</th>\n",
       "      <th>stock splits</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>2022-11-22</th>\n",
       "      <td>43.08</td>\n",
       "      <td>44.24</td>\n",
       "      <td>43.00</td>\n",
       "      <td>43.00</td>\n",
       "      <td>287</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-23</th>\n",
       "      <td>41.58</td>\n",
       "      <td>42.45</td>\n",
       "      <td>39.00</td>\n",
       "      <td>39.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-28</th>\n",
       "      <td>42.50</td>\n",
       "      <td>42.90</td>\n",
       "      <td>42.50</td>\n",
       "      <td>42.90</td>\n",
       "      <td>18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-30</th>\n",
       "      <td>41.00</td>\n",
       "      <td>41.00</td>\n",
       "      <td>41.00</td>\n",
       "      <td>41.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-01</th>\n",
       "      <td>40.73</td>\n",
       "      <td>40.81</td>\n",
       "      <td>39.85</td>\n",
       "      <td>40.25</td>\n",
       "      <td>42</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>2023-11-16</th>\n",
       "      <td>11.41</td>\n",
       "      <td>11.88</td>\n",
       "      <td>11.27</td>\n",
       "      <td>11.70</td>\n",
       "      <td>264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-17</th>\n",
       "      <td>11.50</td>\n",
       "      <td>11.50</td>\n",
       "      <td>11.19</td>\n",
       "      <td>11.40</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>11.00</td>\n",
       "      <td>11.10</td>\n",
       "      <td>10.50</td>\n",
       "      <td>10.76</td>\n",
       "      <td>121</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>10.90</td>\n",
       "      <td>10.95</td>\n",
       "      <td>10.75</td>\n",
       "      <td>10.75</td>\n",
       "      <td>17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>10.50</td>\n",
       "      <td>10.82</td>\n",
       "      <td>10.25</td>\n",
       "      <td>10.61</td>\n",
       "      <td>77</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>239 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             open   high    low  close  volume  dividends  stock splits\n",
       "date                                                                   \n",
       "2022-11-22  43.08  44.24  43.00  43.00     287        0.0           0.0\n",
       "2022-11-23  41.58  42.45  39.00  39.00       6        0.0           0.0\n",
       "2022-11-28  42.50  42.90  42.50  42.90      18        0.0           0.0\n",
       "2022-11-30  41.00  41.00  41.00  41.00       1        0.0           0.0\n",
       "2022-12-01  40.73  40.81  39.85  40.25      42        0.0           0.0\n",
       "...           ...    ...    ...    ...     ...        ...           ...\n",
       "2023-11-16  11.41  11.88  11.27  11.70     264        0.0           0.0\n",
       "2023-11-17  11.50  11.50  11.19  11.40       0        0.0           0.0\n",
       "2023-11-20  11.00  11.10  10.50  10.76     121        0.0           0.0\n",
       "2023-11-21  10.90  10.95  10.75  10.75      17        0.0           0.0\n",
       "2023-11-22  10.50  10.82  10.25  10.61      77        0.0           0.0\n",
       "\n",
       "[239 rows x 7 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obb.equity.price.historical(\"SPY241220P00400000\", provider=\"yfinance\").to_df()\n"
   ]
  },
  {
   "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",
       "        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",
       "    </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>2020-11-27</th>\n",
       "      <td>1846.26</td>\n",
       "      <td>1855.27</td>\n",
       "      <td>1845.50</td>\n",
       "      <td>1855.27</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>1854.87</td>\n",
       "      <td>1854.87</td>\n",
       "      <td>1813.56</td>\n",
       "      <td>1819.82</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-01</th>\n",
       "      <td>1822.92</td>\n",
       "      <td>1848.02</td>\n",
       "      <td>1822.92</td>\n",
       "      <td>1836.05</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-02</th>\n",
       "      <td>1833.08</td>\n",
       "      <td>1842.53</td>\n",
       "      <td>1817.02</td>\n",
       "      <td>1838.03</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-03</th>\n",
       "      <td>1838.52</td>\n",
       "      <td>1860.35</td>\n",
       "      <td>1838.52</td>\n",
       "      <td>1848.70</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-16</th>\n",
       "      <td>1797.00</td>\n",
       "      <td>1797.00</td>\n",
       "      <td>1767.42</td>\n",
       "      <td>1773.76</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-17</th>\n",
       "      <td>1784.86</td>\n",
       "      <td>1798.44</td>\n",
       "      <td>1784.86</td>\n",
       "      <td>1797.77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>1798.56</td>\n",
       "      <td>1809.21</td>\n",
       "      <td>1794.71</td>\n",
       "      <td>1807.08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>1799.33</td>\n",
       "      <td>1799.33</td>\n",
       "      <td>1783.26</td>\n",
       "      <td>1783.26</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>1796.37</td>\n",
       "      <td>1804.96</td>\n",
       "      <td>1785.93</td>\n",
       "      <td>1792.92</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>752 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               open     high      low    close  volume\n",
       "date                                                  \n",
       "2020-11-27  1846.26  1855.27  1845.50  1855.27       0\n",
       "2020-11-30  1854.87  1854.87  1813.56  1819.82       0\n",
       "2020-12-01  1822.92  1848.02  1822.92  1836.05       0\n",
       "2020-12-02  1833.08  1842.53  1817.02  1838.03       0\n",
       "2020-12-03  1838.52  1860.35  1838.52  1848.70       0\n",
       "...             ...      ...      ...      ...     ...\n",
       "2023-11-16  1797.00  1797.00  1767.42  1773.76       0\n",
       "2023-11-17  1784.86  1798.44  1784.86  1797.77       0\n",
       "2023-11-20  1798.56  1809.21  1794.71  1807.08       0\n",
       "2023-11-21  1799.33  1799.33  1783.26  1783.26       0\n",
       "2023-11-22  1796.37  1804.96  1785.93  1792.92       0\n",
       "\n",
       "[752 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obb.equity.price.historical(\"^RUT\", provider=\"cboe\").to_df()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
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       "      <th>volume</th>\n",
       "      <th>vwap</th>\n",
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       "      <th>unadjusted_volume</th>\n",
       "      <th>change</th>\n",
       "      <th>change_percent</th>\n",
       "      <th>change_over_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-11-22</th>\n",
       "      <td>1843.869995</td>\n",
       "      <td>1861.079956</td>\n",
       "      <td>1840.040039</td>\n",
       "      <td>1860.439941</td>\n",
       "      <td>3887990000</td>\n",
       "      <td>1853.85</td>\n",
       "      <td>November 22, 22</td>\n",
       "      <td>1860.439941</td>\n",
       "      <td>3.887990e+09</td>\n",
       "      <td>16.56995</td>\n",
       "      <td>0.89865</td>\n",
       "      <td>0.008986</td>\n",
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       "    <tr>\n",
       "      <th>2022-11-23</th>\n",
       "      <td>1857.589966</td>\n",
       "      <td>1868.920044</td>\n",
       "      <td>1851.680054</td>\n",
       "      <td>1863.520020</td>\n",
       "      <td>3279720000</td>\n",
       "      <td>1861.37</td>\n",
       "      <td>November 23, 22</td>\n",
       "      <td>1863.520020</td>\n",
       "      <td>3.279720e+09</td>\n",
       "      <td>5.93005</td>\n",
       "      <td>0.31923</td>\n",
       "      <td>0.003192</td>\n",
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       "    <tr>\n",
       "      <th>2022-11-25</th>\n",
       "      <td>1862.920044</td>\n",
       "      <td>1873.589966</td>\n",
       "      <td>1861.000000</td>\n",
       "      <td>1869.189941</td>\n",
       "      <td>1706460000</td>\n",
       "      <td>1867.93</td>\n",
       "      <td>November 25, 22</td>\n",
       "      <td>1869.189941</td>\n",
       "      <td>1.706460e+09</td>\n",
       "      <td>6.26990</td>\n",
       "      <td>0.33656</td>\n",
       "      <td>0.003366</td>\n",
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       "    <tr>\n",
       "      <th>2022-11-28</th>\n",
       "      <td>1857.180054</td>\n",
       "      <td>1857.520020</td>\n",
       "      <td>1827.079956</td>\n",
       "      <td>1830.959961</td>\n",
       "      <td>3615430000</td>\n",
       "      <td>1838.52</td>\n",
       "      <td>November 28, 22</td>\n",
       "      <td>1830.959961</td>\n",
       "      <td>3.615430e+09</td>\n",
       "      <td>-26.22009</td>\n",
       "      <td>-1.41000</td>\n",
       "      <td>-0.014100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-29</th>\n",
       "      <td>1832.520020</td>\n",
       "      <td>1846.069946</td>\n",
       "      <td>1832.520020</td>\n",
       "      <td>1836.550049</td>\n",
       "      <td>3546040000</td>\n",
       "      <td>1838.38</td>\n",
       "      <td>November 29, 22</td>\n",
       "      <td>1836.550049</td>\n",
       "      <td>3.546040e+09</td>\n",
       "      <td>4.03003</td>\n",
       "      <td>0.21992</td>\n",
       "      <td>0.002199</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-16</th>\n",
       "      <td>1797.000000</td>\n",
       "      <td>1797.000000</td>\n",
       "      <td>1767.420040</td>\n",
       "      <td>1773.760010</td>\n",
       "      <td>3964520000</td>\n",
       "      <td>1783.80</td>\n",
       "      <td>November 16, 23</td>\n",
       "      <td>1773.760010</td>\n",
       "      <td>3.964520e+09</td>\n",
       "      <td>-23.23999</td>\n",
       "      <td>-1.29000</td>\n",
       "      <td>-0.012900</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-17</th>\n",
       "      <td>1784.859990</td>\n",
       "      <td>1798.439940</td>\n",
       "      <td>1784.859990</td>\n",
       "      <td>1797.770020</td>\n",
       "      <td>3777240000</td>\n",
       "      <td>1791.48</td>\n",
       "      <td>November 17, 23</td>\n",
       "      <td>1797.770020</td>\n",
       "      <td>3.777240e+09</td>\n",
       "      <td>12.91003</td>\n",
       "      <td>0.72331</td>\n",
       "      <td>0.007233</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>1798.560060</td>\n",
       "      <td>1809.209960</td>\n",
       "      <td>1794.709960</td>\n",
       "      <td>1807.079960</td>\n",
       "      <td>3644790000</td>\n",
       "      <td>1802.39</td>\n",
       "      <td>November 20, 23</td>\n",
       "      <td>1807.079960</td>\n",
       "      <td>3.644790e+09</td>\n",
       "      <td>8.51990</td>\n",
       "      <td>0.47371</td>\n",
       "      <td>0.004737</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>1799.329960</td>\n",
       "      <td>1799.329960</td>\n",
       "      <td>1783.260010</td>\n",
       "      <td>1783.260010</td>\n",
       "      <td>3511080000</td>\n",
       "      <td>1791.29</td>\n",
       "      <td>November 21, 23</td>\n",
       "      <td>1783.260010</td>\n",
       "      <td>3.511080e+09</td>\n",
       "      <td>-16.06995</td>\n",
       "      <td>-0.89311</td>\n",
       "      <td>-0.008931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>1792.511480</td>\n",
       "      <td>1803.116700</td>\n",
       "      <td>1789.876830</td>\n",
       "      <td>1795.540410</td>\n",
       "      <td>0</td>\n",
       "      <td>1796.18</td>\n",
       "      <td>November 22, 23</td>\n",
       "      <td>1795.540410</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.02893</td>\n",
       "      <td>0.16898</td>\n",
       "      <td>0.001690</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   open         high          low        close      volume  \\\n",
       "date                                                                         \n",
       "2022-11-22  1843.869995  1861.079956  1840.040039  1860.439941  3887990000   \n",
       "2022-11-23  1857.589966  1868.920044  1851.680054  1863.520020  3279720000   \n",
       "2022-11-25  1862.920044  1873.589966  1861.000000  1869.189941  1706460000   \n",
       "2022-11-28  1857.180054  1857.520020  1827.079956  1830.959961  3615430000   \n",
       "2022-11-29  1832.520020  1846.069946  1832.520020  1836.550049  3546040000   \n",
       "...                 ...          ...          ...          ...         ...   \n",
       "2023-11-16  1797.000000  1797.000000  1767.420040  1773.760010  3964520000   \n",
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       "2023-11-20  1798.560060  1809.209960  1794.709960  1807.079960  3644790000   \n",
       "2023-11-21  1799.329960  1799.329960  1783.260010  1783.260010  3511080000   \n",
       "2023-11-22  1792.511480  1803.116700  1789.876830  1795.540410           0   \n",
       "\n",
       "               vwap            label    adj_close  unadjusted_volume  \\\n",
       "date                                                                   \n",
       "2022-11-22  1853.85  November 22, 22  1860.439941       3.887990e+09   \n",
       "2022-11-23  1861.37  November 23, 22  1863.520020       3.279720e+09   \n",
       "2022-11-25  1867.93  November 25, 22  1869.189941       1.706460e+09   \n",
       "2022-11-28  1838.52  November 28, 22  1830.959961       3.615430e+09   \n",
       "2022-11-29  1838.38  November 29, 22  1836.550049       3.546040e+09   \n",
       "...             ...              ...          ...                ...   \n",
       "2023-11-16  1783.80  November 16, 23  1773.760010       3.964520e+09   \n",
       "2023-11-17  1791.48  November 17, 23  1797.770020       3.777240e+09   \n",
       "2023-11-20  1802.39  November 20, 23  1807.079960       3.644790e+09   \n",
       "2023-11-21  1791.29  November 21, 23  1783.260010       3.511080e+09   \n",
       "2023-11-22  1796.18  November 22, 23  1795.540410       0.000000e+00   \n",
       "\n",
       "              change  change_percent  change_over_time  \n",
       "date                                                    \n",
       "2022-11-22  16.56995         0.89865          0.008986  \n",
       "2022-11-23   5.93005         0.31923          0.003192  \n",
       "2022-11-25   6.26990         0.33656          0.003366  \n",
       "2022-11-28 -26.22009        -1.41000         -0.014100  \n",
       "2022-11-29   4.03003         0.21992          0.002199  \n",
       "...              ...             ...               ...  \n",
       "2023-11-16 -23.23999        -1.29000         -0.012900  \n",
       "2023-11-17  12.91003         0.72331          0.007233  \n",
       "2023-11-20   8.51990         0.47371          0.004737  \n",
       "2023-11-21 -16.06995        -0.89311         -0.008931  \n",
       "2023-11-22   3.02893         0.16898          0.001690  \n",
       "\n",
       "[252 rows x 12 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obb.equity.price.historical(\"^RUT\", provider=\"fmp\").to_df()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>open</th>\n",
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       "      <th>low</th>\n",
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       "      <th>2022-11-22</th>\n",
       "      <td>72.00</td>\n",
       "      <td>72.50</td>\n",
       "      <td>71.70</td>\n",
       "      <td>71.91</td>\n",
       "      <td>6101</td>\n",
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       "      <th>2022-11-23</th>\n",
       "      <td>72.01</td>\n",
       "      <td>72.12</td>\n",
       "      <td>70.53</td>\n",
       "      <td>71.33</td>\n",
       "      <td>10513</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2022-11-25</th>\n",
       "      <td>71.21</td>\n",
       "      <td>72.21</td>\n",
       "      <td>70.55</td>\n",
       "      <td>70.66</td>\n",
       "      <td>5609</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2022-11-28</th>\n",
       "      <td>70.50</td>\n",
       "      <td>71.53</td>\n",
       "      <td>69.26</td>\n",
       "      <td>71.21</td>\n",
       "      <td>12409</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2022-11-29</th>\n",
       "      <td>70.80</td>\n",
       "      <td>72.53</td>\n",
       "      <td>70.61</td>\n",
       "      <td>71.77</td>\n",
       "      <td>14418</td>\n",
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       "      <th>2023-11-16</th>\n",
       "      <td>73.94</td>\n",
       "      <td>74.10</td>\n",
       "      <td>70.94</td>\n",
       "      <td>71.34</td>\n",
       "      <td>58159</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-17</th>\n",
       "      <td>71.37</td>\n",
       "      <td>73.69</td>\n",
       "      <td>71.21</td>\n",
       "      <td>73.58</td>\n",
       "      <td>36644</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>73.05</td>\n",
       "      <td>75.39</td>\n",
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       "      <td>74.98</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>74.65</td>\n",
       "      <td>75.05</td>\n",
       "      <td>74.39</td>\n",
       "      <td>74.98</td>\n",
       "      <td>26277</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>74.07</td>\n",
       "      <td>74.07</td>\n",
       "      <td>73.41</td>\n",
       "      <td>73.61</td>\n",
       "      <td>611</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             open   high    low  close  volume  dividends  stock splits\n",
       "date                                                                   \n",
       "2022-11-22  72.00  72.50  71.70  71.91    6101        0.0           0.0\n",
       "2022-11-23  72.01  72.12  70.53  71.33   10513        0.0           0.0\n",
       "2022-11-25  71.21  72.21  70.55  70.66    5609        0.0           0.0\n",
       "2022-11-28  70.50  71.53  69.26  71.21   12409        0.0           0.0\n",
       "2022-11-29  70.80  72.53  70.61  71.77   14418        0.0           0.0\n",
       "...           ...    ...    ...    ...     ...        ...           ...\n",
       "2023-11-16  73.94  74.10  70.94  71.34   58159        0.0           0.0\n",
       "2023-11-17  71.37  73.69  71.21  73.58   36644        0.0           0.0\n",
       "2023-11-20  73.05  75.39  73.05  74.98   38285        0.0           0.0\n",
       "2023-11-21  74.65  75.05  74.39  74.98   26277        0.0           0.0\n",
       "2023-11-22  74.07  74.07  73.41  73.61     611        0.0           0.0\n",
       "\n",
       "[252 rows x 7 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obb.equity.price.historical(\"CLZ24.NYM\", provider=\"yfinance\").to_df()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>vwap</th>\n",
       "      <th>label</th>\n",
       "      <th>adj_close</th>\n",
       "      <th>unadjusted_volume</th>\n",
       "      <th>change</th>\n",
       "      <th>change_percent</th>\n",
       "      <th>change_over_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",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-11-22</th>\n",
       "      <td>80.22</td>\n",
       "      <td>82.36</td>\n",
       "      <td>79.85</td>\n",
       "      <td>80.95</td>\n",
       "      <td>269615</td>\n",
       "      <td>81.05</td>\n",
       "      <td>November 22, 22</td>\n",
       "      <td>80.949997</td>\n",
       "      <td>269615.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.91000</td>\n",
       "      <td>0.009100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-23</th>\n",
       "      <td>81.08</td>\n",
       "      <td>81.95</td>\n",
       "      <td>76.83</td>\n",
       "      <td>77.94</td>\n",
       "      <td>379145</td>\n",
       "      <td>78.91</td>\n",
       "      <td>November 23, 22</td>\n",
       "      <td>77.940002</td>\n",
       "      <td>379145.0</td>\n",
       "      <td>-3.14</td>\n",
       "      <td>-3.87000</td>\n",
       "      <td>-0.038700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-25</th>\n",
       "      <td>77.51</td>\n",
       "      <td>79.90</td>\n",
       "      <td>76.22</td>\n",
       "      <td>76.28</td>\n",
       "      <td>266451</td>\n",
       "      <td>77.47</td>\n",
       "      <td>November 25, 22</td>\n",
       "      <td>76.279999</td>\n",
       "      <td>266451.0</td>\n",
       "      <td>-1.23</td>\n",
       "      <td>-1.59000</td>\n",
       "      <td>-0.015900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-28</th>\n",
       "      <td>75.93</td>\n",
       "      <td>77.84</td>\n",
       "      <td>73.60</td>\n",
       "      <td>77.24</td>\n",
       "      <td>405033</td>\n",
       "      <td>76.23</td>\n",
       "      <td>November 28, 22</td>\n",
       "      <td>77.239998</td>\n",
       "      <td>405033.0</td>\n",
       "      <td>1.31</td>\n",
       "      <td>1.73000</td>\n",
       "      <td>0.017300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-29</th>\n",
       "      <td>76.54</td>\n",
       "      <td>79.65</td>\n",
       "      <td>76.29</td>\n",
       "      <td>78.20</td>\n",
       "      <td>381869</td>\n",
       "      <td>78.05</td>\n",
       "      <td>November 29, 22</td>\n",
       "      <td>78.199997</td>\n",
       "      <td>381869.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>2.17000</td>\n",
       "      <td>0.021700</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>2023-11-17</th>\n",
       "      <td>72.97</td>\n",
       "      <td>75.99</td>\n",
       "      <td>72.75</td>\n",
       "      <td>75.89</td>\n",
       "      <td>101484</td>\n",
       "      <td>74.88</td>\n",
       "      <td>November 17, 23</td>\n",
       "      <td>75.890000</td>\n",
       "      <td>101484.0</td>\n",
       "      <td>2.92</td>\n",
       "      <td>4.00000</td>\n",
       "      <td>0.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-19</th>\n",
       "      <td>75.65</td>\n",
       "      <td>75.80</td>\n",
       "      <td>75.65</td>\n",
       "      <td>75.80</td>\n",
       "      <td>10</td>\n",
       "      <td>75.75</td>\n",
       "      <td>November 19, 23</td>\n",
       "      <td>75.800000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.19828</td>\n",
       "      <td>0.001983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>75.65</td>\n",
       "      <td>78.22</td>\n",
       "      <td>75.65</td>\n",
       "      <td>77.60</td>\n",
       "      <td>270638</td>\n",
       "      <td>77.16</td>\n",
       "      <td>November 20, 23</td>\n",
       "      <td>77.600000</td>\n",
       "      <td>270638.0</td>\n",
       "      <td>1.95</td>\n",
       "      <td>2.58000</td>\n",
       "      <td>0.025800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>77.65</td>\n",
       "      <td>77.92</td>\n",
       "      <td>76.92</td>\n",
       "      <td>77.77</td>\n",
       "      <td>270638</td>\n",
       "      <td>77.54</td>\n",
       "      <td>November 21, 23</td>\n",
       "      <td>77.770000</td>\n",
       "      <td>270638.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.15454</td>\n",
       "      <td>0.001545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>77.77</td>\n",
       "      <td>77.97</td>\n",
       "      <td>73.79</td>\n",
       "      <td>76.78</td>\n",
       "      <td>368686</td>\n",
       "      <td>76.18</td>\n",
       "      <td>November 22, 23</td>\n",
       "      <td>76.780000</td>\n",
       "      <td>368686.0</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>-1.27000</td>\n",
       "      <td>-0.012700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>277 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             open   high    low  close  volume   vwap            label  \\\n",
       "date                                                                     \n",
       "2022-11-22  80.22  82.36  79.85  80.95  269615  81.05  November 22, 22   \n",
       "2022-11-23  81.08  81.95  76.83  77.94  379145  78.91  November 23, 22   \n",
       "2022-11-25  77.51  79.90  76.22  76.28  266451  77.47  November 25, 22   \n",
       "2022-11-28  75.93  77.84  73.60  77.24  405033  76.23  November 28, 22   \n",
       "2022-11-29  76.54  79.65  76.29  78.20  381869  78.05  November 29, 22   \n",
       "...           ...    ...    ...    ...     ...    ...              ...   \n",
       "2023-11-17  72.97  75.99  72.75  75.89  101484  74.88  November 17, 23   \n",
       "2023-11-19  75.65  75.80  75.65  75.80      10  75.75  November 19, 23   \n",
       "2023-11-20  75.65  78.22  75.65  77.60  270638  77.16  November 20, 23   \n",
       "2023-11-21  77.65  77.92  76.92  77.77  270638  77.54  November 21, 23   \n",
       "2023-11-22  77.77  77.97  73.79  76.78  368686  76.18  November 22, 23   \n",
       "\n",
       "            adj_close  unadjusted_volume  change  change_percent  \\\n",
       "date                                                               \n",
       "2022-11-22  80.949997           269615.0    0.73         0.91000   \n",
       "2022-11-23  77.940002           379145.0   -3.14        -3.87000   \n",
       "2022-11-25  76.279999           266451.0   -1.23        -1.59000   \n",
       "2022-11-28  77.239998           405033.0    1.31         1.73000   \n",
       "2022-11-29  78.199997           381869.0    1.66         2.17000   \n",
       "...               ...                ...     ...             ...   \n",
       "2023-11-17  75.890000           101484.0    2.92         4.00000   \n",
       "2023-11-19  75.800000               10.0    0.15         0.19828   \n",
       "2023-11-20  77.600000           270638.0    1.95         2.58000   \n",
       "2023-11-21  77.770000           270638.0    0.12         0.15454   \n",
       "2023-11-22  76.780000           368686.0   -0.99        -1.27000   \n",
       "\n",
       "            change_over_time  \n",
       "date                          \n",
       "2022-11-22          0.009100  \n",
       "2022-11-23         -0.038700  \n",
       "2022-11-25         -0.015900  \n",
       "2022-11-28          0.017300  \n",
       "2022-11-29          0.021700  \n",
       "...                      ...  \n",
       "2023-11-17          0.040000  \n",
       "2023-11-19          0.001983  \n",
       "2023-11-20          0.025800  \n",
       "2023-11-21          0.001545  \n",
       "2023-11-22         -0.012700  \n",
       "\n",
       "[277 rows x 12 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obb.equity.price.historical(\"CL=F\", provider=\"fmp\").to_df()\n"
   ]
  }
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