{
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  {
   "cell_type": "markdown",
   "id": "8b4405f3-ff20-45fc-b83b-8ab976285d28",
   "metadata": {},
   "source": [
    "<img src=\"https://5264302.fs1.hubspotusercontent-na1.net/hubfs/5264302/Demo%20Asset%20Resources/CM-Demo-options_exploration-Cover.png\" width=1100 margin-left='auto' margin-right='auto'/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfec924a-a0ed-4fc6-a9d7-ce0ca5b16bb3",
   "metadata": {},
   "source": [
    "Options contracts have become an increasingly liquid segment of crypytoasset derivatives. Coin Metrics currently offers options data through various endpoints in our Market Data Feed offering. Available endpoints include market greeks, implied volatility, contract prices, market quotes, open interest, and more. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15688944-a794-453e-b773-f711726cc63a",
   "metadata": {},
   "source": [
    "## Resources\n",
    "This notebook demonstrates basic functionality offered by the Coin Metrics Python API Client and Market Data Feed.\n",
    "\n",
    "Coin Metrics offers a vast assortment of data for hundreds of cryptoassets. The Python API Client allows for easy access to this data using Python without needing to create your own wrappers using `requests` and other such libraries.\n",
    "\n",
    "To understand the data that Coin Metrics offers, feel free to peruse the resources below.\n",
    "\n",
    "- The [Coin Metrics API v4](https://docs.coinmetrics.io/api/v4) website contains the full set of endpoints and data offered by Coin Metrics.\n",
    "- The [Coin Metrics Product Documentation](https://docs.coinmetrics.io/info) gives detailed, conceptual explanations of the data that Coin Metrics offers.\n",
    "- The [API Spec](https://docs.coinmetrics.io/python-api-client/reference) contains a full list of functions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16c3476d-c33a-421e-811e-344b59735ec0",
   "metadata": {},
   "source": [
    "# Notebook Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "7fbd2927-9184-41fd-8403-b259146ee1a2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from os import environ\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import logging\n",
    "from datetime import date, timedelta\n",
    "from coinmetrics.api_client import CoinMetricsClient\n",
    "import logging\n",
    "import calendar\n",
    "from datetime import date\n",
    "import matplotlib.ticker as mtick\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "6ab06f8c-e7f4-41b4-b92e-18a3de36a427",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sns.set_theme()\n",
    "sns.set(rc={'figure.figsize':(18,8)})\n",
    "sns.set_palette(\"YlGn\",3)\n",
    "sns.set_style(\"ticks\", {\"xtick.major.size\":20,\"ytick.major.size\":20})\n",
    "sns.set_style(\"whitegrid\",{'axes.grid' : True,'grid.linestyle': '--', 'grid.color': '#b0b0b0','axes.edgecolor': 'white',\n",
    "              'font.family': ['arial'],'axes.facecolor':'#4b5359'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "abc14b24-03f4-457c-94aa-0c33ff01c79b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "logging.basicConfig(\n",
    "    format='%(asctime)s %(levelname)-8s %(message)s',\n",
    "    level=logging.INFO,\n",
    "    datefmt='%Y-%m-%d %H:%M:%S'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ecbe22c4-ee5a-4130-bc7f-9bf9a61b4bc1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-10-14 15:43:59 INFO     API key not found. Using community client\n"
     ]
    }
   ],
   "source": [
    "# We recommend privately storing your API key in your local environment.\n",
    "try:\n",
    "    api_key = environ[\"CM_API_KEY\"]\n",
    "    logging.info(\"Using API key found in environment\")\n",
    "except KeyError:\n",
    "    api_key = \"\"\n",
    "    logging.info(\"API key not found. Using community client\")\n",
    "client = CoinMetricsClient(api_key)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca39f5b4-150d-4518-a88d-526b9c82a542",
   "metadata": {},
   "source": [
    "# Query Examples\n",
    "### Retrieving Market Greeks\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3aa7fabf-1e2b-4522-8638-df3b6a3e79dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-10-14 12:58:05 INFO     no data to export\n"
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     "execution_count": 5,
     "metadata": {},
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   ],
   "source": [
    "greeks_deribit = client.get_market_greeks(\n",
    "    markets='deribit-BTC-30DEC22-*-option',\n",
    "    limit_per_market=1\n",
    ").to_dataframe()\n",
    "greeks_deribit.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d27fabbf-a5ed-4673-950d-89d62928f91a",
   "metadata": {},
   "source": [
    "### Retrieving Market Quotes\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "965c7aa2-a6e9-48d5-b5c4-21b0fe858578",
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    {
     "name": "stderr",
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     "text": [
      "2024-10-14 12:58:06 INFO     no data to export\n"
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       "Empty DataFrame\n",
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     "execution_count": 6,
     "metadata": {},
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   ],
   "source": [
    "quotes_deribit = client.get_market_quotes(\n",
    "    markets='deribit-BTC-30DEC22-*-option',\n",
    "    limit_per_market=1,\n",
    ").to_dataframe()\n",
    "quotes_deribit.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecb6a67e-dda5-4900-b784-6ce76c9f9406",
   "metadata": {},
   "source": [
    "### Retrieving Contract Prices\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2ed8333a-b547-4eb3-ae1a-77cfec91f070",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-10-14 12:58:06 INFO     no data to export\n"
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       "Empty DataFrame\n",
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   ],
   "source": [
    "prices_deribit = client.get_market_contract_prices(\n",
    "    markets='deribit-BTC-30DEC22-*-option',\n",
    "    limit_per_market=1,\n",
    ").to_dataframe()\n",
    "prices_deribit.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40975f88-dc86-499e-91bf-2fa24006ebe2",
   "metadata": {},
   "source": [
    "### Retrieving Open Interest\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "135ec528-49b2-4bc9-8da2-90b1c256b08e",
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
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      "2024-10-14 12:58:06 INFO     no data to export\n"
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     "execution_count": 8,
     "metadata": {},
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   ],
   "source": [
    "oi_deribit = client.get_market_open_interest(\n",
    "    markets='deribit-BTC-30DEC22-*-option',\n",
    "    limit_per_market=1,\n",
    ").to_dataframe()\n",
    "oi_deribit.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19d96bc9-3ca3-4b11-9848-e0d6e7728811",
   "metadata": {},
   "source": [
    "# Plotting Options 'Volatility Smiles'\n",
    "---\n",
    "'Volatility smiles' are a popular options data visualization tool that help traders understand predicted asset volatility across various contract expiration dates. The 'smile' is plotted by mapping the strike price and implied volatility of a group of options with the same underlying asset and expiration date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "90dec4eb-4af1-4c7a-8d09-e427ba96d78a",
   "metadata": {},
   "outputs": [],
   "source": [
    "asset = 'btc'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32cfcda6-2546-4965-82a6-bdf857ffc251",
   "metadata": {},
   "source": [
    "### Catalog Endpoint\n",
    "\n",
    "The Coin Metrics API contains two types of catalog endpoints (Python client functions in paranthesis): the `catalog` (`catalog_*`) and `catalog-all` (`catalog_full_*`). The `catalog` endpoint displays the set of data available to your API key. The `catalog-all` endpoint displays the full set of data for CM Pro users.\n",
    "\n",
    "Catalog objects return a list of dictionaries. For `catalog_full_market_implied_volatility_v2`, each element of the list is an option market that supports implied volatility data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b10b90fd-0bd7-4fb7-ad3d-568f5021d85b",
   "metadata": {},
   "outputs": [],
   "source": [
    "markets_deribit = client.catalog_full_market_implied_volatility_v2(\n",
    "    exchange='deribit',\n",
    "    market_type='option',\n",
    "    base=asset,\n",
    "    page_size=10000\n",
    ").to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "927b2f14-731b-4e12-908f-4db37dea42c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>market</th>\n",
       "      <th>min_time</th>\n",
       "      <th>max_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40721</th>\n",
       "      <td>deribit-BTC-2SEP21-56000-P-option</td>\n",
       "      <td>2021-09-01 13:24:00+00:00</td>\n",
       "      <td>2021-09-02 08:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40713</th>\n",
       "      <td>deribit-BTC-2SEP21-51000-P-option</td>\n",
       "      <td>2021-09-01 13:24:00+00:00</td>\n",
       "      <td>2021-09-02 08:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40712</th>\n",
       "      <td>deribit-BTC-2SEP21-51000-C-option</td>\n",
       "      <td>2021-09-01 13:24:00+00:00</td>\n",
       "      <td>2021-09-02 08:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40711</th>\n",
       "      <td>deribit-BTC-2SEP21-50000-P-option</td>\n",
       "      <td>2021-09-01 13:24:00+00:00</td>\n",
       "      <td>2021-09-02 08:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40710</th>\n",
       "      <td>deribit-BTC-2SEP21-50000-C-option</td>\n",
       "      <td>2021-09-01 13:24:00+00:00</td>\n",
       "      <td>2021-09-02 08:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33184</th>\n",
       "      <td>deribit-BTC-26SEP25-55000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33183</th>\n",
       "      <td>deribit-BTC-26SEP25-50000-P-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33698</th>\n",
       "      <td>deribit-BTC-27DEC24-70000-C-option</td>\n",
       "      <td>2023-12-28 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33180</th>\n",
       "      <td>deribit-BTC-26SEP25-40000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16571</th>\n",
       "      <td>deribit-BTC-18OCT24-50000-P-option</td>\n",
       "      <td>2024-10-01 17:28:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>56780 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   market                  min_time   \n",
       "40721   deribit-BTC-2SEP21-56000-P-option 2021-09-01 13:24:00+00:00  \\\n",
       "40713   deribit-BTC-2SEP21-51000-P-option 2021-09-01 13:24:00+00:00   \n",
       "40712   deribit-BTC-2SEP21-51000-C-option 2021-09-01 13:24:00+00:00   \n",
       "40711   deribit-BTC-2SEP21-50000-P-option 2021-09-01 13:24:00+00:00   \n",
       "40710   deribit-BTC-2SEP21-50000-C-option 2021-09-01 13:24:00+00:00   \n",
       "...                                   ...                       ...   \n",
       "33184  deribit-BTC-26SEP25-55000-C-option 2024-09-26 08:02:00+00:00   \n",
       "33183  deribit-BTC-26SEP25-50000-P-option 2024-09-26 08:02:00+00:00   \n",
       "33698  deribit-BTC-27DEC24-70000-C-option 2023-12-28 08:02:00+00:00   \n",
       "33180  deribit-BTC-26SEP25-40000-C-option 2024-09-26 08:02:00+00:00   \n",
       "16571  deribit-BTC-18OCT24-50000-P-option 2024-10-01 17:28:00+00:00   \n",
       "\n",
       "                       max_time  \n",
       "40721 2021-09-02 08:00:00+00:00  \n",
       "40713 2021-09-02 08:00:00+00:00  \n",
       "40712 2021-09-02 08:00:00+00:00  \n",
       "40711 2021-09-02 08:00:00+00:00  \n",
       "40710 2021-09-02 08:00:00+00:00  \n",
       "...                         ...  \n",
       "33184 2024-10-14 11:17:00+00:00  \n",
       "33183 2024-10-14 11:17:00+00:00  \n",
       "33698 2024-10-14 11:17:00+00:00  \n",
       "33180 2024-10-14 11:17:00+00:00  \n",
       "16571 2024-10-14 11:17:00+00:00  \n",
       "\n",
       "[56780 rows x 3 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "markets_deribit.sort_values(by='max_time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5a5eafd6-871b-41c3-8be5-6365f48aff57",
   "metadata": {},
   "outputs": [],
   "source": [
    "markets_deribit[\"min_time\"] = pd.to_datetime(markets_deribit.min_time)\n",
    "markets_deribit[\"max_time\"] = pd.to_datetime(markets_deribit.max_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "93359eff-b190-491d-93d3-2eb1bf6c71e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select contracts that are still trading as of yesterday\n",
    "end_date = (date.today() - timedelta(days=1)).strftime(\"%Y-%m-%d\") \n",
    "deribit_current = markets_deribit.loc[(markets_deribit[\"max_time\"] >= end_date)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b135d11-8735-4d4f-bdc1-2322dfd33ab2",
   "metadata": {},
   "source": [
    "### Collect Contract Reference Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2556f850-0824-4872-98eb-bafe2dffa8f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "ref_data = client.reference_data_markets(\n",
    "    exchange = 'deribit',\n",
    "    type = 'option',\n",
    "    base = asset,\n",
    "    page_size=10000\n",
    ").to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fafae5b2-5d66-43f4-9964-6d7113dd6d94",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>exchange</th>\n",
       "      <th>base</th>\n",
       "      <th>quote</th>\n",
       "      <th>pair</th>\n",
       "      <th>symbol</th>\n",
       "      <th>type</th>\n",
       "      <th>size_asset</th>\n",
       "      <th>margin_asset</th>\n",
       "      <th>strike</th>\n",
       "      <th>...</th>\n",
       "      <th>order_amount_min</th>\n",
       "      <th>order_amount_max</th>\n",
       "      <th>order_price_increment</th>\n",
       "      <th>order_price_min</th>\n",
       "      <th>order_price_max</th>\n",
       "      <th>order_size_min</th>\n",
       "      <th>order_taker_fee</th>\n",
       "      <th>order_maker_fee</th>\n",
       "      <th>margin_trading_enabled</th>\n",
       "      <th>experimental</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-BTC-10APR20-4750-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>btc</td>\n",
       "      <td>usd</td>\n",
       "      <td>btc-usd</td>\n",
       "      <td>BTC-10APR20-4750-C</td>\n",
       "      <td>option</td>\n",
       "      <td>btc</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>4750</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-BTC-10APR20-4750-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>btc</td>\n",
       "      <td>usd</td>\n",
       "      <td>btc-usd</td>\n",
       "      <td>BTC-10APR20-4750-P</td>\n",
       "      <td>option</td>\n",
       "      <td>btc</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>4750</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-BTC-10APR20-5000-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>btc</td>\n",
       "      <td>usd</td>\n",
       "      <td>btc-usd</td>\n",
       "      <td>BTC-10APR20-5000-C</td>\n",
       "      <td>option</td>\n",
       "      <td>btc</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>5000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>deribit-BTC-10APR20-5000-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>btc</td>\n",
       "      <td>usd</td>\n",
       "      <td>btc-usd</td>\n",
       "      <td>BTC-10APR20-5000-P</td>\n",
       "      <td>option</td>\n",
       "      <td>btc</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>5000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-BTC-10APR20-5250-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>btc</td>\n",
       "      <td>usd</td>\n",
       "      <td>btc-usd</td>\n",
       "      <td>BTC-10APR20-5250-P</td>\n",
       "      <td>option</td>\n",
       "      <td>btc</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>5250</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              market exchange base quote     pair   \n",
       "0  deribit-BTC-10APR20-4750-C-option  deribit  btc   usd  btc-usd  \\\n",
       "1  deribit-BTC-10APR20-4750-P-option  deribit  btc   usd  btc-usd   \n",
       "2  deribit-BTC-10APR20-5000-C-option  deribit  btc   usd  btc-usd   \n",
       "3  deribit-BTC-10APR20-5000-P-option  deribit  btc   usd  btc-usd   \n",
       "4  deribit-BTC-10APR20-5250-P-option  deribit  btc   usd  btc-usd   \n",
       "\n",
       "               symbol    type size_asset  margin_asset  strike  ...   \n",
       "0  BTC-10APR20-4750-C  option        btc          <NA>    4750  ...  \\\n",
       "1  BTC-10APR20-4750-P  option        btc          <NA>    4750  ...   \n",
       "2  BTC-10APR20-5000-C  option        btc          <NA>    5000  ...   \n",
       "3  BTC-10APR20-5000-P  option        btc          <NA>    5000  ...   \n",
       "4  BTC-10APR20-5250-P  option        btc          <NA>    5250  ...   \n",
       "\n",
       "  order_amount_min  order_amount_max  order_price_increment  order_price_min   \n",
       "0              0.1              <NA>                 0.0005             <NA>  \\\n",
       "1              0.1              <NA>                 0.0005             <NA>   \n",
       "2              0.1              <NA>                 0.0005             <NA>   \n",
       "3              0.1              <NA>                 0.0005             <NA>   \n",
       "4              0.1              <NA>                 0.0005             <NA>   \n",
       "\n",
       "   order_price_max order_size_min order_taker_fee  order_maker_fee   \n",
       "0             <NA>           <NA>          0.0004           0.0004  \\\n",
       "1             <NA>           <NA>          0.0004           0.0004   \n",
       "2             <NA>           <NA>          0.0004           0.0004   \n",
       "3             <NA>           <NA>          0.0004           0.0004   \n",
       "4             <NA>           <NA>          0.0004           0.0004   \n",
       "\n",
       "   margin_trading_enabled  experimental  \n",
       "0                    <NA>          <NA>  \n",
       "1                    <NA>          <NA>  \n",
       "2                    <NA>          <NA>  \n",
       "3                    <NA>          <NA>  \n",
       "4                    <NA>          <NA>  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ref_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ab5428fd-d3e6-4920-910a-310410588ff6",
   "metadata": {},
   "outputs": [],
   "source": [
    "deribit_current = pd.merge(deribit_current, ref_data[['market','expiration','option_contract_type','strike']], on='market', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "38b86801-8940-4a43-9f7d-dcbc7793d1db",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set max expiration date\n",
    "max_expiry = (date.today() + timedelta(days=365)).strftime(\"%Y-%m-%d\")\n",
    "max_expiry = (pd.to_datetime(max_expiry)).strftime(\"%Y-%m-%d\")\n",
    "deribit_current = pd.DataFrame(deribit_current.loc[(deribit_current[\"expiration\"] < max_expiry)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "16ca2202-cbad-4503-927c-6cc2f58f7309",
   "metadata": {},
   "outputs": [],
   "source": [
    "deribit_current = deribit_current.sort_values(by=['expiration'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "51821924-db5d-4568-817a-d60b25fa2d40",
   "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>market</th>\n",
       "      <th>min_time</th>\n",
       "      <th>max_time</th>\n",
       "      <th>expiration</th>\n",
       "      <th>option_contract_type</th>\n",
       "      <th>strike</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-BTC-13OCT24-53000-C-option</td>\n",
       "      <td>2024-10-10 17:55:00+00:00</td>\n",
       "      <td>2024-10-13 08:00:00+00:00</td>\n",
       "      <td>2024-10-13T08:00:00.000000000Z</td>\n",
       "      <td>call</td>\n",
       "      <td>53000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>deribit-BTC-13OCT24-62500-C-option</td>\n",
       "      <td>2024-10-10 08:02:00+00:00</td>\n",
       "      <td>2024-10-13 08:00:00+00:00</td>\n",
       "      <td>2024-10-13T08:00:00.000000000Z</td>\n",
       "      <td>call</td>\n",
       "      <td>62500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>deribit-BTC-13OCT24-62500-P-option</td>\n",
       "      <td>2024-10-10 08:02:00+00:00</td>\n",
       "      <td>2024-10-13 08:00:00+00:00</td>\n",
       "      <td>2024-10-13T08:00:00.000000000Z</td>\n",
       "      <td>put</td>\n",
       "      <td>62500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>deribit-BTC-13OCT24-63000-C-option</td>\n",
       "      <td>2024-10-10 08:02:00+00:00</td>\n",
       "      <td>2024-10-13 08:00:00+00:00</td>\n",
       "      <td>2024-10-13T08:00:00.000000000Z</td>\n",
       "      <td>call</td>\n",
       "      <td>63000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>deribit-BTC-13OCT24-63000-P-option</td>\n",
       "      <td>2024-10-10 08:02:00+00:00</td>\n",
       "      <td>2024-10-13 08:00:00+00:00</td>\n",
       "      <td>2024-10-13T08:00:00.000000000Z</td>\n",
       "      <td>put</td>\n",
       "      <td>63000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539</th>\n",
       "      <td>deribit-BTC-26SEP25-40000-P-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>put</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538</th>\n",
       "      <td>deribit-BTC-26SEP25-40000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>call</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>537</th>\n",
       "      <td>deribit-BTC-26SEP25-30000-P-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>put</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>deribit-BTC-26SEP25-60000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>call</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>deribit-BTC-26SEP25-75000-P-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>put</td>\n",
       "      <td>75000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>906 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 market                  min_time   \n",
       "0    deribit-BTC-13OCT24-53000-C-option 2024-10-10 17:55:00+00:00  \\\n",
       "30   deribit-BTC-13OCT24-62500-C-option 2024-10-10 08:02:00+00:00   \n",
       "31   deribit-BTC-13OCT24-62500-P-option 2024-10-10 08:02:00+00:00   \n",
       "32   deribit-BTC-13OCT24-63000-C-option 2024-10-10 08:02:00+00:00   \n",
       "33   deribit-BTC-13OCT24-63000-P-option 2024-10-10 08:02:00+00:00   \n",
       "..                                  ...                       ...   \n",
       "539  deribit-BTC-26SEP25-40000-P-option 2024-09-26 08:02:00+00:00   \n",
       "538  deribit-BTC-26SEP25-40000-C-option 2024-09-26 08:02:00+00:00   \n",
       "537  deribit-BTC-26SEP25-30000-P-option 2024-09-26 08:02:00+00:00   \n",
       "544  deribit-BTC-26SEP25-60000-C-option 2024-09-26 08:02:00+00:00   \n",
       "551  deribit-BTC-26SEP25-75000-P-option 2024-09-26 08:02:00+00:00   \n",
       "\n",
       "                     max_time                      expiration   \n",
       "0   2024-10-13 08:00:00+00:00  2024-10-13T08:00:00.000000000Z  \\\n",
       "30  2024-10-13 08:00:00+00:00  2024-10-13T08:00:00.000000000Z   \n",
       "31  2024-10-13 08:00:00+00:00  2024-10-13T08:00:00.000000000Z   \n",
       "32  2024-10-13 08:00:00+00:00  2024-10-13T08:00:00.000000000Z   \n",
       "33  2024-10-13 08:00:00+00:00  2024-10-13T08:00:00.000000000Z   \n",
       "..                        ...                             ...   \n",
       "539 2024-10-14 11:17:00+00:00  2025-09-26T08:00:00.000000000Z   \n",
       "538 2024-10-14 11:17:00+00:00  2025-09-26T08:00:00.000000000Z   \n",
       "537 2024-10-14 11:17:00+00:00  2025-09-26T08:00:00.000000000Z   \n",
       "544 2024-10-14 11:17:00+00:00  2025-09-26T08:00:00.000000000Z   \n",
       "551 2024-10-14 11:17:00+00:00  2025-09-26T08:00:00.000000000Z   \n",
       "\n",
       "    option_contract_type  strike  \n",
       "0                   call   53000  \n",
       "30                  call   62500  \n",
       "31                   put   62500  \n",
       "32                  call   63000  \n",
       "33                   put   63000  \n",
       "..                   ...     ...  \n",
       "539                  put   40000  \n",
       "538                 call   40000  \n",
       "537                  put   30000  \n",
       "544                 call   60000  \n",
       "551                  put   75000  \n",
       "\n",
       "[906 rows x 6 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deribit_current"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba802d44-75b2-4749-a258-354ff0392f6b",
   "metadata": {},
   "source": [
    "## Retrieve Implied Volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "600766d3-7637-48b1-b624-88450e35f785",
   "metadata": {},
   "outputs": [],
   "source": [
    "iv_asset_contracts = client.get_market_implied_volatility(\n",
    "    markets='deribit-*-option',\n",
    "    start_time = end_date,\n",
    "    limit_per_market=1,\n",
    "    page_size=10000\n",
    ").to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "66f08ff8-cb28-4425-8d80-0b16d63cfeab",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>time</th>\n",
       "      <th>database_time</th>\n",
       "      <th>iv_bid</th>\n",
       "      <th>iv_ask</th>\n",
       "      <th>iv_mark</th>\n",
       "      <th>exchange_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>deribit-BTC-14OCT24-54000-C-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:07.326104+00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0686</td>\n",
       "      <td>0.7228</td>\n",
       "      <td>2024-10-13 11:59:04.699000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>deribit-BTC-14OCT24-54000-P-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:05.326299+00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.2061</td>\n",
       "      <td>0.7228</td>\n",
       "      <td>2024-10-13 11:59:03.692000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>deribit-BTC-14OCT24-55000-C-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:02.516543+00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.864</td>\n",
       "      <td>0.6178</td>\n",
       "      <td>2024-10-13 11:59:00.671000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>deribit-BTC-14OCT24-55000-P-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:09.328580+00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0658</td>\n",
       "      <td>0.6178</td>\n",
       "      <td>2024-10-13 11:59:06.713000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>deribit-BTC-14OCT24-56000-C-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:05.326299+00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.6567</td>\n",
       "      <td>0.5622</td>\n",
       "      <td>2024-10-13 11:59:03.692000+00:00</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>1141</th>\n",
       "      <td>deribit-BTC-8NOV24-75000-P-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:15.518639+00:00</td>\n",
       "      <td>0.5005</td>\n",
       "      <td>0.6445</td>\n",
       "      <td>0.5916</td>\n",
       "      <td>2024-10-13 11:59:14.769000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1142</th>\n",
       "      <td>deribit-BTC-8NOV24-80000-C-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:20.519174+00:00</td>\n",
       "      <td>0.6078</td>\n",
       "      <td>0.6201</td>\n",
       "      <td>0.613</td>\n",
       "      <td>2024-10-13 11:59:18.797000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1143</th>\n",
       "      <td>deribit-BTC-8NOV24-80000-P-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:07.517497+00:00</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.6931</td>\n",
       "      <td>0.613</td>\n",
       "      <td>2024-10-13 11:59:04.699000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1144</th>\n",
       "      <td>deribit-BTC-8NOV24-90000-C-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:18.331618+00:00</td>\n",
       "      <td>0.6663</td>\n",
       "      <td>0.6836</td>\n",
       "      <td>0.6765</td>\n",
       "      <td>2024-10-13 11:59:16.783000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1145</th>\n",
       "      <td>deribit-BTC-8NOV24-90000-P-option</td>\n",
       "      <td>2024-10-13 11:59:00+00:00</td>\n",
       "      <td>2024-10-13 11:59:10.515713+00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.8475</td>\n",
       "      <td>0.6765</td>\n",
       "      <td>2024-10-13 11:59:08.309000+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>850 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  market                      time   \n",
       "296   deribit-BTC-14OCT24-54000-C-option 2024-10-13 11:59:00+00:00  \\\n",
       "297   deribit-BTC-14OCT24-54000-P-option 2024-10-13 11:59:00+00:00   \n",
       "298   deribit-BTC-14OCT24-55000-C-option 2024-10-13 11:59:00+00:00   \n",
       "299   deribit-BTC-14OCT24-55000-P-option 2024-10-13 11:59:00+00:00   \n",
       "300   deribit-BTC-14OCT24-56000-C-option 2024-10-13 11:59:00+00:00   \n",
       "...                                  ...                       ...   \n",
       "1141   deribit-BTC-8NOV24-75000-P-option 2024-10-13 11:59:00+00:00   \n",
       "1142   deribit-BTC-8NOV24-80000-C-option 2024-10-13 11:59:00+00:00   \n",
       "1143   deribit-BTC-8NOV24-80000-P-option 2024-10-13 11:59:00+00:00   \n",
       "1144   deribit-BTC-8NOV24-90000-C-option 2024-10-13 11:59:00+00:00   \n",
       "1145   deribit-BTC-8NOV24-90000-P-option 2024-10-13 11:59:00+00:00   \n",
       "\n",
       "                        database_time  iv_bid  iv_ask  iv_mark   \n",
       "296  2024-10-13 11:59:07.326104+00:00     0.0  2.0686   0.7228  \\\n",
       "297  2024-10-13 11:59:05.326299+00:00     0.0  1.2061   0.7228   \n",
       "298  2024-10-13 11:59:02.516543+00:00     0.0   1.864   0.6178   \n",
       "299  2024-10-13 11:59:09.328580+00:00     0.0  1.0658   0.6178   \n",
       "300  2024-10-13 11:59:05.326299+00:00     0.0  1.6567   0.5622   \n",
       "...                               ...     ...     ...      ...   \n",
       "1141 2024-10-13 11:59:15.518639+00:00  0.5005  0.6445   0.5916   \n",
       "1142 2024-10-13 11:59:20.519174+00:00  0.6078  0.6201    0.613   \n",
       "1143 2024-10-13 11:59:07.517497+00:00    0.49  0.6931    0.613   \n",
       "1144 2024-10-13 11:59:18.331618+00:00  0.6663  0.6836   0.6765   \n",
       "1145 2024-10-13 11:59:10.515713+00:00     0.0  0.8475   0.6765   \n",
       "\n",
       "                        exchange_time  \n",
       "296  2024-10-13 11:59:04.699000+00:00  \n",
       "297  2024-10-13 11:59:03.692000+00:00  \n",
       "298  2024-10-13 11:59:00.671000+00:00  \n",
       "299  2024-10-13 11:59:06.713000+00:00  \n",
       "300  2024-10-13 11:59:03.692000+00:00  \n",
       "...                               ...  \n",
       "1141 2024-10-13 11:59:14.769000+00:00  \n",
       "1142 2024-10-13 11:59:18.797000+00:00  \n",
       "1143 2024-10-13 11:59:04.699000+00:00  \n",
       "1144 2024-10-13 11:59:16.783000+00:00  \n",
       "1145 2024-10-13 11:59:08.309000+00:00  \n",
       "\n",
       "[850 rows x 7 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iv_asset_contracts = iv_asset_contracts.loc[iv_asset_contracts['market'].isin(deribit_current['market'].to_list())]\n",
    "iv_asset_contracts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a4c2e548-4671-42a9-ac5c-cd8eb875c8cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>iv_mark</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>deribit-BTC-14OCT24-54000-C-option</td>\n",
       "      <td>0.7228</td>\n",
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       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>deribit-BTC-14OCT24-54000-P-option</td>\n",
       "      <td>0.7228</td>\n",
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       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>deribit-BTC-14OCT24-55000-C-option</td>\n",
       "      <td>0.6178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>deribit-BTC-14OCT24-55000-P-option</td>\n",
       "      <td>0.6178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>deribit-BTC-14OCT24-56000-C-option</td>\n",
       "      <td>0.5622</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1141</th>\n",
       "      <td>deribit-BTC-8NOV24-75000-P-option</td>\n",
       "      <td>0.5916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1142</th>\n",
       "      <td>deribit-BTC-8NOV24-80000-C-option</td>\n",
       "      <td>0.613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1143</th>\n",
       "      <td>deribit-BTC-8NOV24-80000-P-option</td>\n",
       "      <td>0.613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1144</th>\n",
       "      <td>deribit-BTC-8NOV24-90000-C-option</td>\n",
       "      <td>0.6765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1145</th>\n",
       "      <td>deribit-BTC-8NOV24-90000-P-option</td>\n",
       "      <td>0.6765</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>850 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  market  iv_mark\n",
       "296   deribit-BTC-14OCT24-54000-C-option   0.7228\n",
       "297   deribit-BTC-14OCT24-54000-P-option   0.7228\n",
       "298   deribit-BTC-14OCT24-55000-C-option   0.6178\n",
       "299   deribit-BTC-14OCT24-55000-P-option   0.6178\n",
       "300   deribit-BTC-14OCT24-56000-C-option   0.5622\n",
       "...                                  ...      ...\n",
       "1141   deribit-BTC-8NOV24-75000-P-option   0.5916\n",
       "1142   deribit-BTC-8NOV24-80000-C-option    0.613\n",
       "1143   deribit-BTC-8NOV24-80000-P-option    0.613\n",
       "1144   deribit-BTC-8NOV24-90000-C-option   0.6765\n",
       "1145   deribit-BTC-8NOV24-90000-P-option   0.6765\n",
       "\n",
       "[850 rows x 2 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iv_only = iv_asset_contracts.drop(['time', 'database_time','iv_bid','iv_ask','exchange_time'], axis=1).drop_duplicates()\n",
    "iv_only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f11ab401-06c8-4220-add1-8fc6dab4947b",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged = pd.merge(deribit_current, iv_only, on=\"market\").drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "84fc4efa-4dff-4415-bfcd-62681b5a9115",
   "metadata": {},
   "outputs": [],
   "source": [
    "calls = pd.DataFrame(merged.loc[merged['option_contract_type'] == 'call'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "445c5f2e-97a0-442d-b6b2-d400ea950321",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>min_time</th>\n",
       "      <th>max_time</th>\n",
       "      <th>expiration</th>\n",
       "      <th>option_contract_type</th>\n",
       "      <th>strike</th>\n",
       "      <th>iv_mark</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-BTC-14OCT24-66000-C-option</td>\n",
       "      <td>2024-10-11 08:01:00+00:00</td>\n",
       "      <td>2024-10-14 08:00:00+00:00</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>66000</td>\n",
       "      <td>0.4548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-BTC-14OCT24-65500-C-option</td>\n",
       "      <td>2024-10-11 17:35:00+00:00</td>\n",
       "      <td>2024-10-14 08:00:00+00:00</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>65500</td>\n",
       "      <td>0.4528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-BTC-14OCT24-65000-C-option</td>\n",
       "      <td>2024-10-11 08:01:00+00:00</td>\n",
       "      <td>2024-10-14 08:00:00+00:00</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>65000</td>\n",
       "      <td>0.4346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>deribit-BTC-14OCT24-64500-C-option</td>\n",
       "      <td>2024-10-11 08:01:00+00:00</td>\n",
       "      <td>2024-10-14 08:00:00+00:00</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>64500</td>\n",
       "      <td>0.3870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>deribit-BTC-14OCT24-64000-C-option</td>\n",
       "      <td>2024-10-11 08:01:00+00:00</td>\n",
       "      <td>2024-10-14 08:00:00+00:00</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>64000</td>\n",
       "      <td>0.3532</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>840</th>\n",
       "      <td>deribit-BTC-26SEP25-65000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>65000</td>\n",
       "      <td>0.5921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842</th>\n",
       "      <td>deribit-BTC-26SEP25-55000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>55000</td>\n",
       "      <td>0.5814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>844</th>\n",
       "      <td>deribit-BTC-26SEP25-50000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:16:00+00:00</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>50000</td>\n",
       "      <td>0.5846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>846</th>\n",
       "      <td>deribit-BTC-26SEP25-40000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>40000</td>\n",
       "      <td>0.5947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>deribit-BTC-26SEP25-60000-C-option</td>\n",
       "      <td>2024-09-26 08:02:00+00:00</td>\n",
       "      <td>2024-10-14 11:17:00+00:00</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>60000</td>\n",
       "      <td>0.5908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>425 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 market                  min_time   \n",
       "1    deribit-BTC-14OCT24-66000-C-option 2024-10-11 08:01:00+00:00  \\\n",
       "2    deribit-BTC-14OCT24-65500-C-option 2024-10-11 17:35:00+00:00   \n",
       "4    deribit-BTC-14OCT24-65000-C-option 2024-10-11 08:01:00+00:00   \n",
       "6    deribit-BTC-14OCT24-64500-C-option 2024-10-11 08:01:00+00:00   \n",
       "7    deribit-BTC-14OCT24-64000-C-option 2024-10-11 08:01:00+00:00   \n",
       "..                                  ...                       ...   \n",
       "840  deribit-BTC-26SEP25-65000-C-option 2024-09-26 08:02:00+00:00   \n",
       "842  deribit-BTC-26SEP25-55000-C-option 2024-09-26 08:02:00+00:00   \n",
       "844  deribit-BTC-26SEP25-50000-C-option 2024-09-26 08:02:00+00:00   \n",
       "846  deribit-BTC-26SEP25-40000-C-option 2024-09-26 08:02:00+00:00   \n",
       "848  deribit-BTC-26SEP25-60000-C-option 2024-09-26 08:02:00+00:00   \n",
       "\n",
       "                     max_time    expiration option_contract_type  strike   \n",
       "1   2024-10-14 08:00:00+00:00  Oct 14, 2024                 call   66000  \\\n",
       "2   2024-10-14 08:00:00+00:00  Oct 14, 2024                 call   65500   \n",
       "4   2024-10-14 08:00:00+00:00  Oct 14, 2024                 call   65000   \n",
       "6   2024-10-14 08:00:00+00:00  Oct 14, 2024                 call   64500   \n",
       "7   2024-10-14 08:00:00+00:00  Oct 14, 2024                 call   64000   \n",
       "..                        ...           ...                  ...     ...   \n",
       "840 2024-10-14 11:17:00+00:00  Sep 26, 2025                 call   65000   \n",
       "842 2024-10-14 11:17:00+00:00  Sep 26, 2025                 call   55000   \n",
       "844 2024-10-14 11:16:00+00:00  Sep 26, 2025                 call   50000   \n",
       "846 2024-10-14 11:17:00+00:00  Sep 26, 2025                 call   40000   \n",
       "848 2024-10-14 11:17:00+00:00  Sep 26, 2025                 call   60000   \n",
       "\n",
       "     iv_mark  \n",
       "1     0.4548  \n",
       "2     0.4528  \n",
       "4     0.4346  \n",
       "6     0.3870  \n",
       "7     0.3532  \n",
       "..       ...  \n",
       "840   0.5921  \n",
       "842   0.5814  \n",
       "844   0.5846  \n",
       "846   0.5947  \n",
       "848   0.5908  \n",
       "\n",
       "[425 rows x 7 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calls['expiration'] = pd.to_datetime(calls['expiration']).dt.strftime('%b %d, %Y')\n",
    "calls = calls.dropna(subset=['strike'])\n",
    "calls['strike'] = calls['strike'].astype('int64')\n",
    "calls['iv_mark'] = calls['iv_mark'].astype('float64')\n",
    "calls['expiration'] = calls['expiration'].astype('category')\n",
    "calls = calls.dropna(subset=['strike', 'iv_mark'])\n",
    "calls = calls[np.isfinite(calls['strike']) & np.isfinite(calls['iv_mark'])]\n",
    "calls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "aa92ffc1-a9e1-498a-9d85-0e5c2c73a0b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "calls = calls.sort_values(by='expiration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "76c84223-fb08-44c1-a645-bb0b65217b7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "market                       string[python]\n",
       "min_time                datetime64[ns, UTC]\n",
       "max_time                datetime64[ns, UTC]\n",
       "expiration                         category\n",
       "option_contract_type         string[python]\n",
       "strike                                int64\n",
       "iv_mark                             float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calls.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a16fab5b-5b72-4cc5-a7c4-fb43ade8f6fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l = sns.lineplot(data=calls, x=\"strike\", y=\"iv_mark\", hue='expiration')\n",
    "l.set_xlabel(\"\\nStrike Price\", fontsize = 17)\n",
    "l.set_ylabel(\"Implied Volatility \\n\", fontsize = 17)\n",
    "l.set_xlim([0, calls['strike'].max()])\n",
    "\n",
    "l.set_xticks(l.get_xticks().tolist())\n",
    "l.set_xticklabels(['${:,.0f}'.format(x) for x in l.get_xticks().tolist()],fontsize=14)\n",
    "l.set_yticks(l.get_yticks().tolist())\n",
    "l.set_yticklabels(['{:.2f}'.format(y) for y in l.get_yticks().tolist()],fontsize=14)\n",
    "plt.setp(l.get_yticklabels()[0], visible=False)    \n",
    "leg = plt.legend(loc='upper right',ncol=2,fontsize=13.5)\n",
    "for text in leg.get_texts():\n",
    "    text.set_color(\"white\")\n",
    "l.set_title('\\n' + asset.upper() + ' Volatility Smiles\\n', fontsize = 25)\n",
    "plt.suptitle('\\n\\n         Deribit Options by Expiration',fontsize=16);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35d5eae8-59f7-4486-ac27-00d75ee658d3",
   "metadata": {},
   "source": [
    "# Plotting Calls vs. Puts by Open Interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c769817d-67e2-4072-b8a2-4704de75d291",
   "metadata": {},
   "outputs": [],
   "source": [
    "options_oi = client.get_market_open_interest(\n",
    "    markets='deribit-*-option',\n",
    "    limit_per_market=1,\n",
    "    paging_from='end',\n",
    "    start_time=end_date,\n",
    "    page_size=10000\n",
    ").to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5358e6e5-bd35-4e06-b73b-e76f75e6aa15",
   "metadata": {},
   "outputs": [],
   "source": [
    "options_oi['value_usd'] = pd.to_numeric(options_oi['value_usd'])\n",
    "options_oi = options_oi.loc[options_oi['value_usd'] > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5b12ab66-183c-4286-ac5b-2dcc4c965cee",
   "metadata": {},
   "outputs": [],
   "source": [
    "options_oi = options_oi.sort_values('value_usd',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fd4e33d4-88c6-45d1-9b54-aa9d01f94843",
   "metadata": {},
   "outputs": [],
   "source": [
    "oi_only = options_oi[['market','contract_count','value_usd']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "48239028-eeab-401f-9f62-bf56663f5a5c",
   "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>market</th>\n",
       "      <th>contract_count</th>\n",
       "      <th>value_usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2472</th>\n",
       "      <td>deribit-XRP_USDC-25OCT24-1-C-option</td>\n",
       "      <td>6196000.0</td>\n",
       "      <td>3336546000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2466</th>\n",
       "      <td>deribit-XRP_USDC-25OCT24-0d8-C-option</td>\n",
       "      <td>4684000.0</td>\n",
       "      <td>2521865600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2464</th>\n",
       "      <td>deribit-XRP_USDC-25OCT24-0d75-C-option</td>\n",
       "      <td>1766000.0</td>\n",
       "      <td>950814400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2470</th>\n",
       "      <td>deribit-XRP_USDC-25OCT24-0d9-C-option</td>\n",
       "      <td>1731000.0</td>\n",
       "      <td>932143500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>deribit-BTC-27DEC24-100000-C-option</td>\n",
       "      <td>9857.1</td>\n",
       "      <td>639750432.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>deribit-BNB_USDC-29NOV24-500-C-option</td>\n",
       "      <td>1.0</td>\n",
       "      <td>580.5411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>deribit-BNB_USDC-25OCT24-360-P-option</td>\n",
       "      <td>1.0</td>\n",
       "      <td>580.5411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>deribit-BNB_USDC-29NOV24-480-C-option</td>\n",
       "      <td>1.0</td>\n",
       "      <td>580.5396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>deribit-BNB_USDC-18OCT24-610-C-option</td>\n",
       "      <td>1.0</td>\n",
       "      <td>580.5389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>deribit-BNB_USDC-25OCT24-400-P-option</td>\n",
       "      <td>1.0</td>\n",
       "      <td>580.5389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1646 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      market  contract_count     value_usd\n",
       "2472     deribit-XRP_USDC-25OCT24-1-C-option       6196000.0  3336546000.0\n",
       "2466   deribit-XRP_USDC-25OCT24-0d8-C-option       4684000.0  2521865600.0\n",
       "2464  deribit-XRP_USDC-25OCT24-0d75-C-option       1766000.0   950814400.0\n",
       "2470   deribit-XRP_USDC-25OCT24-0d9-C-option       1731000.0   932143500.0\n",
       "798      deribit-BTC-27DEC24-100000-C-option          9857.1  639750432.75\n",
       "...                                      ...             ...           ...\n",
       "264    deribit-BNB_USDC-29NOV24-500-C-option             1.0      580.5411\n",
       "207    deribit-BNB_USDC-25OCT24-360-P-option             1.0      580.5411\n",
       "262    deribit-BNB_USDC-29NOV24-480-C-option             1.0      580.5396\n",
       "180    deribit-BNB_USDC-18OCT24-610-C-option             1.0      580.5389\n",
       "209    deribit-BNB_USDC-25OCT24-400-P-option             1.0      580.5389\n",
       "\n",
       "[1646 rows x 3 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oi_only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "edd1f736-e0b9-42c9-bd5f-e7347fa865a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "asset_deribit_oi = deribit_current[['market','expiration','strike','option_contract_type']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "71d1b3af-22ed-44ce-8eb3-0cc3b6970f17",
   "metadata": {},
   "outputs": [],
   "source": [
    "oi_merged = pd.merge(asset_deribit_oi, oi_only, on=\"market\").drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "cabe7db6-aeb8-40cf-ac07-72e63f47a22e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>market</th>\n",
       "      <th>expiration</th>\n",
       "      <th>strike</th>\n",
       "      <th>option_contract_type</th>\n",
       "      <th>contract_count</th>\n",
       "      <th>value_usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-BTC-14OCT24-66000-P-option</td>\n",
       "      <td>2024-10-14T08:00:00.000000000Z</td>\n",
       "      <td>66000</td>\n",
       "      <td>put</td>\n",
       "      <td>0.4</td>\n",
       "      <td>25728.316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-BTC-14OCT24-66000-C-option</td>\n",
       "      <td>2024-10-14T08:00:00.000000000Z</td>\n",
       "      <td>66000</td>\n",
       "      <td>call</td>\n",
       "      <td>29.2</td>\n",
       "      <td>1878176.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-BTC-14OCT24-65500-C-option</td>\n",
       "      <td>2024-10-14T08:00:00.000000000Z</td>\n",
       "      <td>65500</td>\n",
       "      <td>call</td>\n",
       "      <td>28.1</td>\n",
       "      <td>1807422.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>deribit-BTC-14OCT24-65000-C-option</td>\n",
       "      <td>2024-10-14T08:00:00.000000000Z</td>\n",
       "      <td>65000</td>\n",
       "      <td>call</td>\n",
       "      <td>58.5</td>\n",
       "      <td>3762784.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-BTC-14OCT24-64000-P-option</td>\n",
       "      <td>2024-10-14T08:00:00.000000000Z</td>\n",
       "      <td>64000</td>\n",
       "      <td>put</td>\n",
       "      <td>23.3</td>\n",
       "      <td>1498671.145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>715</th>\n",
       "      <td>deribit-BTC-26SEP25-50000-C-option</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>50000</td>\n",
       "      <td>call</td>\n",
       "      <td>0.5</td>\n",
       "      <td>32451.195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>716</th>\n",
       "      <td>deribit-BTC-26SEP25-40000-P-option</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>40000</td>\n",
       "      <td>put</td>\n",
       "      <td>35.6</td>\n",
       "      <td>2310525.084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>deribit-BTC-26SEP25-30000-P-option</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>30000</td>\n",
       "      <td>put</td>\n",
       "      <td>44.9</td>\n",
       "      <td>2914122.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>718</th>\n",
       "      <td>deribit-BTC-26SEP25-60000-C-option</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>60000</td>\n",
       "      <td>call</td>\n",
       "      <td>3.3</td>\n",
       "      <td>214056.744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>719</th>\n",
       "      <td>deribit-BTC-26SEP25-75000-P-option</td>\n",
       "      <td>2025-09-26T08:00:00.000000000Z</td>\n",
       "      <td>75000</td>\n",
       "      <td>put</td>\n",
       "      <td>4.0</td>\n",
       "      <td>259609.96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>720 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 market                      expiration   \n",
       "0    deribit-BTC-14OCT24-66000-P-option  2024-10-14T08:00:00.000000000Z  \\\n",
       "1    deribit-BTC-14OCT24-66000-C-option  2024-10-14T08:00:00.000000000Z   \n",
       "2    deribit-BTC-14OCT24-65500-C-option  2024-10-14T08:00:00.000000000Z   \n",
       "3    deribit-BTC-14OCT24-65000-C-option  2024-10-14T08:00:00.000000000Z   \n",
       "4    deribit-BTC-14OCT24-64000-P-option  2024-10-14T08:00:00.000000000Z   \n",
       "..                                  ...                             ...   \n",
       "715  deribit-BTC-26SEP25-50000-C-option  2025-09-26T08:00:00.000000000Z   \n",
       "716  deribit-BTC-26SEP25-40000-P-option  2025-09-26T08:00:00.000000000Z   \n",
       "717  deribit-BTC-26SEP25-30000-P-option  2025-09-26T08:00:00.000000000Z   \n",
       "718  deribit-BTC-26SEP25-60000-C-option  2025-09-26T08:00:00.000000000Z   \n",
       "719  deribit-BTC-26SEP25-75000-P-option  2025-09-26T08:00:00.000000000Z   \n",
       "\n",
       "     strike option_contract_type  contract_count    value_usd  \n",
       "0     66000                  put             0.4    25728.316  \n",
       "1     66000                 call            29.2   1878176.12  \n",
       "2     65500                 call            28.1   1807422.91  \n",
       "3     65000                 call            58.5   3762784.35  \n",
       "4     64000                  put            23.3  1498671.145  \n",
       "..      ...                  ...             ...          ...  \n",
       "715   50000                 call             0.5    32451.195  \n",
       "716   40000                  put            35.6  2310525.084  \n",
       "717   30000                  put            44.9   2914122.25  \n",
       "718   60000                 call             3.3   214056.744  \n",
       "719   75000                  put             4.0    259609.96  \n",
       "\n",
       "[720 rows x 6 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oi_merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "19e355a1-dc31-4e31-a422-b6853a879d2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>expiration</th>\n",
       "      <th>strike</th>\n",
       "      <th>option_contract_type</th>\n",
       "      <th>contract_count</th>\n",
       "      <th>value_usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-BTC-14OCT24-66000-P-option</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>66000</td>\n",
       "      <td>put</td>\n",
       "      <td>0.4</td>\n",
       "      <td>25728.316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-BTC-14OCT24-66000-C-option</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>66000</td>\n",
       "      <td>call</td>\n",
       "      <td>29.2</td>\n",
       "      <td>1878176.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-BTC-14OCT24-65500-C-option</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>65500</td>\n",
       "      <td>call</td>\n",
       "      <td>28.1</td>\n",
       "      <td>1807422.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>deribit-BTC-14OCT24-65000-C-option</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>65000</td>\n",
       "      <td>call</td>\n",
       "      <td>58.5</td>\n",
       "      <td>3762784.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-BTC-14OCT24-64000-P-option</td>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>64000</td>\n",
       "      <td>put</td>\n",
       "      <td>23.3</td>\n",
       "      <td>1498671.145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>715</th>\n",
       "      <td>deribit-BTC-26SEP25-50000-C-option</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>50000</td>\n",
       "      <td>call</td>\n",
       "      <td>0.5</td>\n",
       "      <td>32451.195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>716</th>\n",
       "      <td>deribit-BTC-26SEP25-40000-P-option</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>40000</td>\n",
       "      <td>put</td>\n",
       "      <td>35.6</td>\n",
       "      <td>2310525.084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>deribit-BTC-26SEP25-30000-P-option</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>30000</td>\n",
       "      <td>put</td>\n",
       "      <td>44.9</td>\n",
       "      <td>2914122.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>718</th>\n",
       "      <td>deribit-BTC-26SEP25-60000-C-option</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>60000</td>\n",
       "      <td>call</td>\n",
       "      <td>3.3</td>\n",
       "      <td>214056.744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>719</th>\n",
       "      <td>deribit-BTC-26SEP25-75000-P-option</td>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>75000</td>\n",
       "      <td>put</td>\n",
       "      <td>4.0</td>\n",
       "      <td>259609.96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>720 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 market    expiration  strike   \n",
       "0    deribit-BTC-14OCT24-66000-P-option  Oct 14, 2024   66000  \\\n",
       "1    deribit-BTC-14OCT24-66000-C-option  Oct 14, 2024   66000   \n",
       "2    deribit-BTC-14OCT24-65500-C-option  Oct 14, 2024   65500   \n",
       "3    deribit-BTC-14OCT24-65000-C-option  Oct 14, 2024   65000   \n",
       "4    deribit-BTC-14OCT24-64000-P-option  Oct 14, 2024   64000   \n",
       "..                                  ...           ...     ...   \n",
       "715  deribit-BTC-26SEP25-50000-C-option  Sep 26, 2025   50000   \n",
       "716  deribit-BTC-26SEP25-40000-P-option  Sep 26, 2025   40000   \n",
       "717  deribit-BTC-26SEP25-30000-P-option  Sep 26, 2025   30000   \n",
       "718  deribit-BTC-26SEP25-60000-C-option  Sep 26, 2025   60000   \n",
       "719  deribit-BTC-26SEP25-75000-P-option  Sep 26, 2025   75000   \n",
       "\n",
       "    option_contract_type  contract_count    value_usd  \n",
       "0                    put             0.4    25728.316  \n",
       "1                   call            29.2   1878176.12  \n",
       "2                   call            28.1   1807422.91  \n",
       "3                   call            58.5   3762784.35  \n",
       "4                    put            23.3  1498671.145  \n",
       "..                   ...             ...          ...  \n",
       "715                 call             0.5    32451.195  \n",
       "716                  put            35.6  2310525.084  \n",
       "717                  put            44.9   2914122.25  \n",
       "718                 call             3.3   214056.744  \n",
       "719                  put             4.0    259609.96  \n",
       "\n",
       "[720 rows x 6 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oi_merged.expiration = pd.to_datetime(oi_merged.expiration).dt.strftime('%b %d, %Y')\n",
    "oi_merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9e4bddf4-3a33-4909-90da-2a9bb863b60e",
   "metadata": {},
   "outputs": [],
   "source": [
    "oi_merged_sum = oi_merged.groupby(\n",
    "        ['expiration', 'option_contract_type']).value_usd.sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "033ad47f-f842-48ff-bedc-bc08f4aed570",
   "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>expiration</th>\n",
       "      <th>option_contract_type</th>\n",
       "      <th>value_usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dec 27, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>3976075356.066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Dec 27, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>1547475225.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jun 27, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>257199454.401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jun 27, 2025</td>\n",
       "      <td>put</td>\n",
       "      <td>102482941.943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mar 28, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>1832745173.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mar 28, 2025</td>\n",
       "      <td>put</td>\n",
       "      <td>377168731.527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Nov 01, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>114413038.068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nov 01, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>95059169.425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Nov 08, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>815723403.183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nov 08, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>474329954.222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Nov 29, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>1057375382.035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Nov 29, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>618304103.234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>53592281.995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Oct 14, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>41197556.425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Oct 15, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>43747321.212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oct 15, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>50689062.709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Oct 16, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>12439904.649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Oct 16, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>19913998.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Oct 17, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>1394908.603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Oct 17, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>2867831.131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Oct 18, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>540029643.818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Oct 18, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>377542611.758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Oct 25, 2024</td>\n",
       "      <td>call</td>\n",
       "      <td>2411334424.658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Oct 25, 2024</td>\n",
       "      <td>put</td>\n",
       "      <td>1448247780.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>call</td>\n",
       "      <td>73607162.108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sep 26, 2025</td>\n",
       "      <td>put</td>\n",
       "      <td>17304638.405</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      expiration option_contract_type       value_usd\n",
       "0   Dec 27, 2024                 call  3976075356.066\n",
       "1   Dec 27, 2024                  put   1547475225.01\n",
       "2   Jun 27, 2025                 call   257199454.401\n",
       "3   Jun 27, 2025                  put   102482941.943\n",
       "4   Mar 28, 2025                 call  1832745173.065\n",
       "5   Mar 28, 2025                  put   377168731.527\n",
       "6   Nov 01, 2024                 call   114413038.068\n",
       "7   Nov 01, 2024                  put    95059169.425\n",
       "8   Nov 08, 2024                 call   815723403.183\n",
       "9   Nov 08, 2024                  put   474329954.222\n",
       "10  Nov 29, 2024                 call  1057375382.035\n",
       "11  Nov 29, 2024                  put   618304103.234\n",
       "12  Oct 14, 2024                 call    53592281.995\n",
       "13  Oct 14, 2024                  put    41197556.425\n",
       "14  Oct 15, 2024                 call    43747321.212\n",
       "15  Oct 15, 2024                  put    50689062.709\n",
       "16  Oct 16, 2024                 call    12439904.649\n",
       "17  Oct 16, 2024                  put     19913998.62\n",
       "18  Oct 17, 2024                 call     1394908.603\n",
       "19  Oct 17, 2024                  put     2867831.131\n",
       "20  Oct 18, 2024                 call   540029643.818\n",
       "21  Oct 18, 2024                  put   377542611.758\n",
       "22  Oct 25, 2024                 call  2411334424.658\n",
       "23  Oct 25, 2024                  put   1448247780.39\n",
       "24  Sep 26, 2025                 call    73607162.108\n",
       "25  Sep 26, 2025                  put    17304638.405"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oi_merged_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "93a41c9a-b55d-49f7-beb8-73eceff2d0e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "calls_oi = pd.DataFrame(oi_merged_sum.loc[oi_merged_sum['option_contract_type'] == 'call'])\n",
    "puts_oi = pd.DataFrame(oi_merged_sum.loc[oi_merged_sum['option_contract_type'] == 'put'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a3f71c72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert 'expiration' to datetime and extract month\n",
    "calls_oi['expiration'] = pd.to_datetime(calls_oi['expiration'])\n",
    "calls_oi['Expiration Month'] = calls_oi['expiration'].dt.month\n",
    "\n",
    "puts_oi['expiration'] = pd.to_datetime(puts_oi['expiration'])\n",
    "puts_oi['Expiration Month'] = puts_oi['expiration'].dt.month\n",
    "\n",
    "# Group by 'expiration_month' and sum 'value_usd'\n",
    "calls_oi_grouped = calls_oi.groupby('Expiration Month')['value_usd'].sum()\n",
    "puts_oi_grouped = puts_oi.groupby('Expiration Month')['value_usd'].sum()\n",
    "\n",
    "# Convert Series to DataFrame and reset index\n",
    "calls_oi_df = calls_oi_grouped.reset_index()\n",
    "puts_oi_df = puts_oi_grouped.reset_index()\n",
    "\n",
    "# Replace month numbers with month names\n",
    "calls_oi_df['Expiration Month'] = calls_oi_df['Expiration Month'].apply(lambda x: calendar.month_name[x])\n",
    "puts_oi_df['Expiration Month'] = puts_oi_df['Expiration Month'].apply(lambda x: calendar.month_name[x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "90a62fd3-d8cb-4a78-9db2-6025f1ea66e1",
   "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>Expiration Month</th>\n",
       "      <th>value_usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>March</td>\n",
       "      <td>1832745173.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>June</td>\n",
       "      <td>257199454.401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>September</td>\n",
       "      <td>73607162.108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>October</td>\n",
       "      <td>3062538484.935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>November</td>\n",
       "      <td>1987511823.286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>December</td>\n",
       "      <td>3976075356.066</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Expiration Month       value_usd\n",
       "0            March  1832745173.065\n",
       "1             June   257199454.401\n",
       "2        September    73607162.108\n",
       "3          October  3062538484.935\n",
       "4         November  1987511823.286\n",
       "5         December  3976075356.066"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calls_oi_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "183f2821-3881-4f20-92a9-2bb0e852cabc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-10-14 12:59:01 INFO     Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n",
      "2024-10-14 12:59:01 INFO     Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add a new column to distinguish between calls and puts\n",
    "calls_oi_df['type'] = 'calls'\n",
    "puts_oi_df['type'] = 'puts'\n",
    "\n",
    "# Concatenate the dataframes\n",
    "df = pd.concat([calls_oi_df, puts_oi_df])\n",
    "df = df.rename(columns={\"value_usd\": \"Open Interest (USD)\"})\n",
    "\n",
    "# Plot the bars side by side\n",
    "p = sns.barplot(data=df, x='Expiration Month', y='Open Interest (USD)', hue='type', palette=['green', 'red'])\n",
    "p.set_title('\\nBTC Options Open Interest (USD)\\nby Expiration Month\\n',fontsize=16)\n",
    "# Format y-axis in billions\n",
    "fmt = '${x:,.0f}B'\n",
    "p.legend_.remove()\n",
    "\n",
    "tick = mtick.FuncFormatter(lambda x, pos: '${:,.2f}B'.format(x*1e-9))\n",
    "p.yaxis.set_major_formatter(tick)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}