compose/docker/notebooks/Stock-Analysis-Intro-Extracting-Datasets.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetch and Extract Stock Datasets\n",
    "\n",
    "This notebook shows how to use the https://github.com/AlgoTraders/stock-analysis-engine repository to fetch and extract stock datasets from various sources. Once collected, the datasets are cached in Redis and archived in Minio (S3)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run this notebook to fetch, extract and plot Netflix **NFLX** stock datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetch Datsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "ticker = 'NFLX'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# fetch all datasets for the ticker\n",
    "from analysis_engine.fetch import fetch\n",
    "fetch_datasets = fetch(ticker=ticker)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.extract import extract\n",
    "datasets = extract(ticker=ticker)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extracted NFLX dataset with name: daily\n",
      "extracted NFLX dataset with name: minute\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extracted NFLX dataset with name: quote\n",
      "extracted NFLX dataset with name: stats\n",
      "extracted NFLX dataset with name: peers\n",
      "extracted NFLX dataset with name: news1\n",
      "extracted NFLX dataset with name: financials\n",
      "extracted NFLX dataset with name: earnings\n",
      "extracted NFLX dataset with name: dividends\n",
      "extracted NFLX dataset with name: company\n",
      "extracted NFLX dataset with name: calls\n",
      "extracted NFLX dataset with name: puts\n",
      "extracted NFLX dataset with name: pricing\n",
      "extracted NFLX dataset with name: news\n"
     ]
    }
   ],
   "source": [
    "import analysis_engine.charts as ae_charts\n",
    "from analysis_engine.consts import IEX_MINUTE_DATE_FORMAT\n",
    "for dataset_name in datasets[ticker]:\n",
    "    print('extracted {} dataset with name: {}'.format(ticker, dataset_name))\n",
    "    if dataset_name == 'minute':\n",
    "        minute_df = datasets[ticker][dataset_name]\n",
    "        image_res = ae_charts.plot_overlay_pricing_and_volume(\n",
    "            log_label='intro-nb-{}'.format(ticker),\n",
    "            ticker=ticker,\n",
    "            date_format=IEX_MINUTE_DATE_FORMAT,\n",
    "            df=minute_df,\n",
    "            show_plot=True)\n",
    "# note: re-run this block if it shows something like:\n",
    "# <Figure size 1500x1000 with 2 Axes> instead of a pricing chart"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Fetch also returns the collected datasets for all tickers**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fetch for NFLX created a dataset with name: daily\n",
      "fetch for NFLX created a dataset with name: minute\n",
      "fetch for NFLX created a dataset with name: quote\n",
      "fetch for NFLX created a dataset with name: stats\n",
      "fetch for NFLX created a dataset with name: peers\n",
      "fetch for NFLX created a dataset with name: news1\n",
      "fetch for NFLX created a dataset with name: financials\n",
      "fetch for NFLX created a dataset with name: earnings\n",
      "fetch for NFLX created a dataset with name: dividends\n",
      "fetch for NFLX created a dataset with name: company\n",
      "fetch for NFLX created a dataset with name: calls\n",
      "fetch for NFLX created a dataset with name: puts\n",
      "fetch for NFLX created a dataset with name: pricing\n",
      "fetch for NFLX created a dataset with name: news\n"
     ]
    }
   ],
   "source": [
    "for dataset_name in fetch_datasets[ticker]:\n",
    "    print('fetch for {} created a dataset with name: {}'.format(ticker, dataset_name))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advanced Developer Usage - Manually Extracting NFLX Datasets\n",
    "\n",
    "If you want to develop your own algorithms, you may need to extract datasets after they have been fetched and collected with the library's API. For background, the engine and library will automatically cache and archive datasets in Minio (S3)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Verify Datasets are in Redis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These commands assume you have the [redis client installed](https://redis.io/download):\n",
    "\n",
    "```\n",
    "./tools/redis-cli.sh\n",
    "127.0.0.1:6379> keys *\n",
    " 1) \"NFLX_2018-10-19_company\"\n",
    " 2) \"NFLX_2018-10-19_financials\"\n",
    " 3) \"NFLX_2018-10-19_peers\"\n",
    " 4) \"NFLX_2018-10-19_news\"\n",
    " 5) \"NFLX_2018-10-19_quote\"\n",
    " 6) \"NFLX_2018-10-19\"\n",
    " 7) \"NFLX_2018-10-19_news1\"\n",
    " 8) \"NFLX_2018-10-19_earnings\"\n",
    " 9) \"NFLX_2018-10-19_stats\"\n",
    "10) \"NFLX_2018-10-19_daily\"\n",
    "11) \"NFLX_2018-10-19_dividends\"\n",
    "12) \"NFLX_2018-10-19_minute\"\n",
    "13) \"NFLX_2018-10-19_options\"\n",
    "14) \"NFLX_2018-10-19_pricing\"\n",
    "127.0.0.1:6379>\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Verify Datasets are in Minio\n",
    "\n",
    "You can view the datasets in Minio (S3) by browsing to:\n",
    "\n",
    "http://localhost:9000/minio/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Imports and Logger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "from IPython.display import display\n",
    "from IPython.display import HTML\n",
    "from analysis_engine.api_requests import get_ds_dict\n",
    "from analysis_engine.consts import SUCCESS\n",
    "from analysis_engine.consts import ppj\n",
    "from analysis_engine.consts import IEX_DAILY_DATE_FORMAT\n",
    "from analysis_engine.consts import IEX_TICK_DATE_FORMAT\n",
    "from analysis_engine.utils import utc_now_str\n",
    "from analysis_engine.utils import get_last_close_str\n",
    "from spylunking.log.setup_logging import build_colorized_logger\n",
    "from analysis_engine.extract import extract\n",
    "\n",
    "log_label = 'intro-ds-1'\n",
    "log = build_colorized_logger(name=log_label, handler_name='jupyter')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select a Ticker and Date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "today_str = utc_now_str()\n",
    "last_close_str = get_last_close_str()\n",
    "\n",
    "log.info('Using ticker={} with last close={}'.format(ticker, last_close_str))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Cache Keys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cache_dict = get_ds_dict(ticker=ticker, label=log_label)\n",
    "log.info('Cache keys for ticker={} and last close={} cache_dict={}'.format(ticker, last_close_str, ppj(cache_dict)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Minute Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_minute_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, minute_df = extract_minute_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    log.info(\n",
    "        'ticker={} creating chart date={}'.format(\n",
    "            ticker,\n",
    "            today_str))\n",
    "    \"\"\"\n",
    "    Plot Pricing with the Volume Overlay:\n",
    "    \"\"\"\n",
    "    image_res = ae_charts.plot_overlay_pricing_and_volume(\n",
    "        log_label='intro-nb-{}'.format(ticker),\n",
    "        ticker=ticker,\n",
    "        date_format=IEX_MINUTE_DATE_FORMAT,\n",
    "        df=minute_df,\n",
    "        show_plot=True)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['minute']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting IEX Quote Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_quote_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, quote_df = extract_quote_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>avgTotalVolume</th>\n",
       "      <th>calculationPrice</th>\n",
       "      <th>change</th>\n",
       "      <th>changePercent</th>\n",
       "      <th>close</th>\n",
       "      <th>closeTime</th>\n",
       "      <th>close_time</th>\n",
       "      <th>companyName</th>\n",
       "      <th>date</th>\n",
       "      <th>delayedPrice</th>\n",
       "      <th>...</th>\n",
       "      <th>open</th>\n",
       "      <th>openTime</th>\n",
       "      <th>open_time</th>\n",
       "      <th>peRatio</th>\n",
       "      <th>previousClose</th>\n",
       "      <th>primaryExchange</th>\n",
       "      <th>sector</th>\n",
       "      <th>week52High</th>\n",
       "      <th>week52Low</th>\n",
       "      <th>ytdChange</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11383247</td>\n",
       "      <td>close</td>\n",
       "      <td>-14.04</td>\n",
       "      <td>-0.04049</td>\n",
       "      <td>332.67</td>\n",
       "      <td>2018-10-19T20:00:00.585Z</td>\n",
       "      <td>2018-10-19 20:00:00.585</td>\n",
       "      <td>Netflix Inc.</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>332.67</td>\n",
       "      <td>...</td>\n",
       "      <td>349.36</td>\n",
       "      <td>2018-10-19T13:30:00.731Z</td>\n",
       "      <td>2018-10-19 13:30:00.731</td>\n",
       "      <td>119.24</td>\n",
       "      <td>346.71</td>\n",
       "      <td>Nasdaq Global Select</td>\n",
       "      <td>Consumer Cyclical</td>\n",
       "      <td>423.2056</td>\n",
       "      <td>178.38</td>\n",
       "      <td>0.614008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   avgTotalVolume calculationPrice  change  changePercent   close  \\\n",
       "0        11383247            close  -14.04       -0.04049  332.67   \n",
       "\n",
       "                  closeTime              close_time   companyName       date  \\\n",
       "0  2018-10-19T20:00:00.585Z 2018-10-19 20:00:00.585  Netflix Inc. 2018-10-19   \n",
       "\n",
       "   delayedPrice    ...        open                  openTime  \\\n",
       "0        332.67    ...      349.36  2018-10-19T13:30:00.731Z   \n",
       "\n",
       "                open_time  peRatio previousClose       primaryExchange  \\\n",
       "0 2018-10-19 13:30:00.731   119.24        346.71  Nasdaq Global Select   \n",
       "\n",
       "              sector  week52High  week52Low  ytdChange  \n",
       "0  Consumer Cyclical    423.2056     178.38   0.614008  \n",
       "\n",
       "[1 rows x 45 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    log.info(\n",
    "        'ticker={} creating chart date={}'.format(\n",
    "            ticker,\n",
    "            today_str))\n",
    "    display(quote_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['quote']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Daily Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_daily_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, daily_df = extract_daily_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    log.info(\n",
    "        'ticker={} creating chart date={}'.format(\n",
    "            ticker,\n",
    "            today_str))\n",
    "    \"\"\"\n",
    "    Plot Pricing with the Volume Overlay:\n",
    "    \"\"\"\n",
    "    image_res = ae_charts.plot_overlay_pricing_and_volume(\n",
    "        log_label='intro-nb-{}'.format(ticker),\n",
    "        ticker=ticker,\n",
    "        date_format=IEX_DAILY_DATE_FORMAT,\n",
    "        df=daily_df,\n",
    "        show_plot=True)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['daily']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Stats Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_stats_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, stats_df = extract_stats_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>EBITDA</th>\n",
       "      <th>EPSSurpriseDollar</th>\n",
       "      <th>EPSSurprisePercent</th>\n",
       "      <th>beta</th>\n",
       "      <th>cash</th>\n",
       "      <th>companyName</th>\n",
       "      <th>consensusEPS</th>\n",
       "      <th>day200MovingAvg</th>\n",
       "      <th>day30ChangePercent</th>\n",
       "      <th>day50MovingAvg</th>\n",
       "      <th>...</th>\n",
       "      <th>shortInterest</th>\n",
       "      <th>shortRatio</th>\n",
       "      <th>ttmEPS</th>\n",
       "      <th>week52change</th>\n",
       "      <th>week52high</th>\n",
       "      <th>week52low</th>\n",
       "      <th>year1ChangePercent</th>\n",
       "      <th>year2ChangePercent</th>\n",
       "      <th>year5ChangePercent</th>\n",
       "      <th>ytdChangePercent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>149222000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.8824</td>\n",
       "      <td>1.050323</td>\n",
       "      <td>2822795000</td>\n",
       "      <td>Netflix Inc.</td>\n",
       "      <td>0.68</td>\n",
       "      <td>328.7879</td>\n",
       "      <td>-0.045177</td>\n",
       "      <td>353.8804</td>\n",
       "      <td>...</td>\n",
       "      <td>16396960</td>\n",
       "      <td>1.82</td>\n",
       "      <td>2.79</td>\n",
       "      <td>70.4863</td>\n",
       "      <td>423.2056</td>\n",
       "      <td>178.38</td>\n",
       "      <td>0.713381</td>\n",
       "      <td>1.69696</td>\n",
       "      <td>5.559882</td>\n",
       "      <td>0.654498</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 49 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      EBITDA  EPSSurpriseDollar  EPSSurprisePercent      beta        cash  \\\n",
       "0  149222000                NaN             30.8824  1.050323  2822795000   \n",
       "\n",
       "    companyName  consensusEPS  day200MovingAvg  day30ChangePercent  \\\n",
       "0  Netflix Inc.          0.68         328.7879           -0.045177   \n",
       "\n",
       "   day50MovingAvg        ...         shortInterest  shortRatio  ttmEPS  \\\n",
       "0        353.8804        ...              16396960        1.82    2.79   \n",
       "\n",
       "   week52change  week52high  week52low  year1ChangePercent  \\\n",
       "0       70.4863    423.2056     178.38            0.713381   \n",
       "\n",
       "   year2ChangePercent  year5ChangePercent  ytdChangePercent  \n",
       "0             1.69696            5.559882          0.654498  \n",
       "\n",
       "[1 rows x 49 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(stats_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['stats']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Peers Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_peers_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, peers_df = extract_peers_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>peer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BCE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AMZN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CMCSA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DIS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>VIAB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FOXA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    peer\n",
       "0    BCE\n",
       "1   AMZN\n",
       "2  CMCSA\n",
       "3   DISH\n",
       "4    DIS\n",
       "5      P\n",
       "6   VIAB\n",
       "7   FOXA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(peers_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['peers']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting News from IEX Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_news_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, news_iex_df = extract_news_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>headline</th>\n",
       "      <th>image</th>\n",
       "      <th>related</th>\n",
       "      <th>source</th>\n",
       "      <th>summary</th>\n",
       "      <th>url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Netflix's biggest daredevil move could be maki...</td>\n",
       "      <td>https://api.iextrading.com/1.0/stock/nflx/news...</td>\n",
       "      <td>DIS,NFLX,SNE,T</td>\n",
       "      <td>CNBC</td>\n",
       "      <td>No summary available.</td>\n",
       "      <td>https://api.iextrading.com/1.0/stock/nflx/arti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QQQ: The Netflix Effect</td>\n",
       "      <td>https://api.iextrading.com/1.0/stock/nflx/news...</td>\n",
       "      <td>AMZN,CON102,MU,NASDAQ01,NFLX,QQQ,RET10217,SPEC...</td>\n",
       "      <td>SeekingAlpha</td>\n",
       "      <td>Share values for the Invesco QQQ ETF ( QQQ ...</td>\n",
       "      <td>https://api.iextrading.com/1.0/stock/nflx/arti...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            headline  \\\n",
       "0  Netflix's biggest daredevil move could be maki...   \n",
       "1                            QQQ: The Netflix Effect   \n",
       "\n",
       "                                               image  \\\n",
       "0  https://api.iextrading.com/1.0/stock/nflx/news...   \n",
       "1  https://api.iextrading.com/1.0/stock/nflx/news...   \n",
       "\n",
       "                                             related        source  \\\n",
       "0                                     DIS,NFLX,SNE,T          CNBC   \n",
       "1  AMZN,CON102,MU,NASDAQ01,NFLX,QQQ,RET10217,SPEC...  SeekingAlpha   \n",
       "\n",
       "                                             summary  \\\n",
       "0                              No summary available.   \n",
       "1     Share values for the Invesco QQQ ETF ( QQQ ...   \n",
       "\n",
       "                                                 url  \n",
       "0  https://api.iextrading.com/1.0/stock/nflx/arti...  \n",
       "1  https://api.iextrading.com/1.0/stock/nflx/arti...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(news_iex_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['news1']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Financials Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_financials_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, financials_df = extract_financials_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>cashChange</th>\n",
       "      <th>cashFlow</th>\n",
       "      <th>costOfRevenue</th>\n",
       "      <th>currentAssets</th>\n",
       "      <th>currentCash</th>\n",
       "      <th>currentDebt</th>\n",
       "      <th>grossProfit</th>\n",
       "      <th>netIncome</th>\n",
       "      <th>operatingExpense</th>\n",
       "      <th>operatingGainsLosses</th>\n",
       "      <th>operatingIncome</th>\n",
       "      <th>operatingRevenue</th>\n",
       "      <th>researchAndDevelopment</th>\n",
       "      <th>shareholderEquity</th>\n",
       "      <th>symbol</th>\n",
       "      <th>totalAssets</th>\n",
       "      <th>totalCash</th>\n",
       "      <th>totalDebt</th>\n",
       "      <th>totalLiabilities</th>\n",
       "      <th>totalRevenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-829868000</td>\n",
       "      <td>-690411000</td>\n",
       "      <td>2412346000</td>\n",
       "      <td>8729981000</td>\n",
       "      <td>3078564000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1587028000</td>\n",
       "      <td>402835000</td>\n",
       "      <td>1106360000</td>\n",
       "      <td>-7670000</td>\n",
       "      <td>480668000</td>\n",
       "      <td>3999374000</td>\n",
       "      <td>327026000</td>\n",
       "      <td>5009653000</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>23366229000</td>\n",
       "      <td>3067534000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3999374000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1350857000</td>\n",
       "      <td>-518239000</td>\n",
       "      <td>2289867000</td>\n",
       "      <td>9346889000</td>\n",
       "      <td>3913994000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1617403000</td>\n",
       "      <td>384349000</td>\n",
       "      <td>1155190000</td>\n",
       "      <td>-85410000</td>\n",
       "      <td>462213000</td>\n",
       "      <td>3907270000</td>\n",
       "      <td>317213000</td>\n",
       "      <td>4496600000</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>22663537000</td>\n",
       "      <td>3906357000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3907270000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-230495000</td>\n",
       "      <td>-236757000</td>\n",
       "      <td>2196075000</td>\n",
       "      <td>7817576000</td>\n",
       "      <td>2599477000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1504781000</td>\n",
       "      <td>290124000</td>\n",
       "      <td>1058203000</td>\n",
       "      <td>41080000</td>\n",
       "      <td>446578000</td>\n",
       "      <td>3700856000</td>\n",
       "      <td>300730000</td>\n",
       "      <td>4020730000</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>20152797000</td>\n",
       "      <td>2593666000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3700856000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1074145000</td>\n",
       "      <td>-487957000</td>\n",
       "      <td>2107354000</td>\n",
       "      <td>7669974000</td>\n",
       "      <td>2822795000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1178401000</td>\n",
       "      <td>185517000</td>\n",
       "      <td>933098000</td>\n",
       "      <td>25740000</td>\n",
       "      <td>245303000</td>\n",
       "      <td>3285755000</td>\n",
       "      <td>273351000</td>\n",
       "      <td>3581956000</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>19012742000</td>\n",
       "      <td>2822795000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3285755000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cashChange   cashFlow  costOfRevenue  currentAssets  currentCash  \\\n",
       "0  -829868000 -690411000     2412346000     8729981000   3078564000   \n",
       "1  1350857000 -518239000     2289867000     9346889000   3913994000   \n",
       "2  -230495000 -236757000     2196075000     7817576000   2599477000   \n",
       "3  1074145000 -487957000     2107354000     7669974000   2822795000   \n",
       "\n",
       "   currentDebt  grossProfit  netIncome  operatingExpense  \\\n",
       "0          NaN   1587028000  402835000        1106360000   \n",
       "1          NaN   1617403000  384349000        1155190000   \n",
       "2          NaN   1504781000  290124000        1058203000   \n",
       "3          NaN   1178401000  185517000         933098000   \n",
       "\n",
       "   operatingGainsLosses  operatingIncome  operatingRevenue  \\\n",
       "0              -7670000        480668000        3999374000   \n",
       "1             -85410000        462213000        3907270000   \n",
       "2              41080000        446578000        3700856000   \n",
       "3              25740000        245303000        3285755000   \n",
       "\n",
       "   researchAndDevelopment  shareholderEquity symbol  totalAssets   totalCash  \\\n",
       "0               327026000         5009653000   NFLX  23366229000  3067534000   \n",
       "1               317213000         4496600000   NFLX  22663537000  3906357000   \n",
       "2               300730000         4020730000   NFLX  20152797000  2593666000   \n",
       "3               273351000         3581956000   NFLX  19012742000  2822795000   \n",
       "\n",
       "   totalDebt  totalLiabilities  totalRevenue  \n",
       "0        NaN               NaN    3999374000  \n",
       "1        NaN               NaN    3907270000  \n",
       "2        NaN               NaN    3700856000  \n",
       "3        NaN               NaN    3285755000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(financials_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['financials']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Earnings Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_earnings_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, earnings_df = extract_earnings_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>EPSSurpriseDollar</th>\n",
       "      <th>actualEPS</th>\n",
       "      <th>announceTime</th>\n",
       "      <th>consensusEPS</th>\n",
       "      <th>estimatedChangePercent</th>\n",
       "      <th>estimatedEPS</th>\n",
       "      <th>fiscalEndDate</th>\n",
       "      <th>fiscalPeriod</th>\n",
       "      <th>numberOfEstimates</th>\n",
       "      <th>symbol</th>\n",
       "      <th>symbolId</th>\n",
       "      <th>yearAgo</th>\n",
       "      <th>yearAgoChangePercent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.21</td>\n",
       "      <td>0.89</td>\n",
       "      <td>AMC</td>\n",
       "      <td>0.68</td>\n",
       "      <td>1.344828</td>\n",
       "      <td>0.68</td>\n",
       "      <td>2018-09-30T00:00:00.000Z</td>\n",
       "      <td>Q3 2018</td>\n",
       "      <td>14</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>4784</td>\n",
       "      <td>0.29</td>\n",
       "      <td>2.068966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.05</td>\n",
       "      <td>0.85</td>\n",
       "      <td>AMC</td>\n",
       "      <td>0.80</td>\n",
       "      <td>4.333333</td>\n",
       "      <td>0.80</td>\n",
       "      <td>2018-06-30T00:00:00.000Z</td>\n",
       "      <td>Q2 2018</td>\n",
       "      <td>19</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>4784</td>\n",
       "      <td>0.15</td>\n",
       "      <td>4.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.64</td>\n",
       "      <td>AMC</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.575000</td>\n",
       "      <td>0.63</td>\n",
       "      <td>2018-03-31T00:00:00.000Z</td>\n",
       "      <td>Q1 2018</td>\n",
       "      <td>16</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>4784</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.41</td>\n",
       "      <td>AMC</td>\n",
       "      <td>0.41</td>\n",
       "      <td>1.733333</td>\n",
       "      <td>0.41</td>\n",
       "      <td>2017-12-31T00:00:00.000Z</td>\n",
       "      <td>Q4 2017</td>\n",
       "      <td>16</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>4784</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.733333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   EPSSurpriseDollar  actualEPS announceTime  consensusEPS  \\\n",
       "0               0.21       0.89          AMC          0.68   \n",
       "1               0.05       0.85          AMC          0.80   \n",
       "2               0.01       0.64          AMC          0.63   \n",
       "3                NaN       0.41          AMC          0.41   \n",
       "\n",
       "   estimatedChangePercent  estimatedEPS             fiscalEndDate  \\\n",
       "0                1.344828          0.68  2018-09-30T00:00:00.000Z   \n",
       "1                4.333333          0.80  2018-06-30T00:00:00.000Z   \n",
       "2                0.575000          0.63  2018-03-31T00:00:00.000Z   \n",
       "3                1.733333          0.41  2017-12-31T00:00:00.000Z   \n",
       "\n",
       "  fiscalPeriod  numberOfEstimates symbol  symbolId  yearAgo  \\\n",
       "0      Q3 2018                 14   NFLX      4784     0.29   \n",
       "1      Q2 2018                 19   NFLX      4784     0.15   \n",
       "2      Q1 2018                 16   NFLX      4784     0.40   \n",
       "3      Q4 2017                 16   NFLX      4784     0.15   \n",
       "\n",
       "   yearAgoChangePercent  \n",
       "0              2.068966  \n",
       "1              4.666667  \n",
       "2              0.600000  \n",
       "3              1.733333  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(earnings_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['earnings']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Dividends Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_dividends_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, dividends_df = extract_dividends_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: []"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(dividends_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['dividends']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Company Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.iex.extract_df_from_redis import extract_company_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, company_df = extract_company_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>CEO</th>\n",
       "      <th>companyName</th>\n",
       "      <th>description</th>\n",
       "      <th>exchange</th>\n",
       "      <th>industry</th>\n",
       "      <th>issueType</th>\n",
       "      <th>sector</th>\n",
       "      <th>tags</th>\n",
       "      <th>website</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Reed Hastings</td>\n",
       "      <td>Netflix Inc.</td>\n",
       "      <td>Netflix Inc provides multimedia content throug...</td>\n",
       "      <td>Nasdaq Global Select</td>\n",
       "      <td>Entertainment</td>\n",
       "      <td>cs</td>\n",
       "      <td>Consumer Cyclical</td>\n",
       "      <td>[Consumer Cyclical, Media - Diversified, Enter...</td>\n",
       "      <td>http://www.netflix.com</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             CEO   companyName  \\\n",
       "0  Reed Hastings  Netflix Inc.   \n",
       "\n",
       "                                         description              exchange  \\\n",
       "0  Netflix Inc provides multimedia content throug...  Nasdaq Global Select   \n",
       "\n",
       "        industry issueType             sector  \\\n",
       "0  Entertainment        cs  Consumer Cyclical   \n",
       "\n",
       "                                                tags                 website  \n",
       "0  [Consumer Cyclical, Media - Diversified, Enter...  http://www.netflix.com  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(company_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['company']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Option Calls Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.yahoo.extract_df_from_redis import extract_option_calls_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, option_calls_df = extract_option_calls_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>ask</th>\n",
       "      <th>bid</th>\n",
       "      <th>change</th>\n",
       "      <th>contractSize</th>\n",
       "      <th>contractSymbol</th>\n",
       "      <th>currency</th>\n",
       "      <th>expiration</th>\n",
       "      <th>impliedVolatility</th>\n",
       "      <th>inTheMoney</th>\n",
       "      <th>lastPrice</th>\n",
       "      <th>lastTradeDate</th>\n",
       "      <th>openInterest</th>\n",
       "      <th>percentChange</th>\n",
       "      <th>strike</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>109.10</td>\n",
       "      <td>108.05</td>\n",
       "      <td>-5.550003</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00225000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.793947</td>\n",
       "      <td>True</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1539959582</td>\n",
       "      <td>11</td>\n",
       "      <td>-4.094432</td>\n",
       "      <td>225</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>112.55</td>\n",
       "      <td>110.40</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00230000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>1.353763</td>\n",
       "      <td>True</td>\n",
       "      <td>122.08</td>\n",
       "      <td>1537214332</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>230</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>99.30</td>\n",
       "      <td>98.00</td>\n",
       "      <td>-15.650002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00235000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.729251</td>\n",
       "      <td>True</td>\n",
       "      <td>111.75</td>\n",
       "      <td>1539964516</td>\n",
       "      <td>7</td>\n",
       "      <td>-12.284145</td>\n",
       "      <td>235</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>94.45</td>\n",
       "      <td>93.15</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00240000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.711673</td>\n",
       "      <td>True</td>\n",
       "      <td>122.45</td>\n",
       "      <td>1539803206</td>\n",
       "      <td>20</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>240</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89.75</td>\n",
       "      <td>88.30</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00245000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.700198</td>\n",
       "      <td>True</td>\n",
       "      <td>104.80</td>\n",
       "      <td>1539879100</td>\n",
       "      <td>6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>245</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>84.85</td>\n",
       "      <td>83.75</td>\n",
       "      <td>-11.400002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00250000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.689945</td>\n",
       "      <td>True</td>\n",
       "      <td>89.60</td>\n",
       "      <td>1539972054</td>\n",
       "      <td>30</td>\n",
       "      <td>-11.287130</td>\n",
       "      <td>250</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>80.10</td>\n",
       "      <td>78.80</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00255000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.664798</td>\n",
       "      <td>True</td>\n",
       "      <td>82.62</td>\n",
       "      <td>1539622122</td>\n",
       "      <td>24</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>255</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>75.35</td>\n",
       "      <td>74.05</td>\n",
       "      <td>-12.500000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00260000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.646488</td>\n",
       "      <td>True</td>\n",
       "      <td>87.85</td>\n",
       "      <td>1539965323</td>\n",
       "      <td>61</td>\n",
       "      <td>-12.456403</td>\n",
       "      <td>260</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>70.65</td>\n",
       "      <td>69.35</td>\n",
       "      <td>-2.150002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00265000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.629398</td>\n",
       "      <td>True</td>\n",
       "      <td>70.65</td>\n",
       "      <td>1539976510</td>\n",
       "      <td>14</td>\n",
       "      <td>-2.953299</td>\n",
       "      <td>265</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>65.95</td>\n",
       "      <td>64.75</td>\n",
       "      <td>-27.860000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00270000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.612919</td>\n",
       "      <td>True</td>\n",
       "      <td>73.56</td>\n",
       "      <td>1539969611</td>\n",
       "      <td>35</td>\n",
       "      <td>-27.469927</td>\n",
       "      <td>270</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>61.20</td>\n",
       "      <td>60.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00275000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.587406</td>\n",
       "      <td>True</td>\n",
       "      <td>86.45</td>\n",
       "      <td>1539793733</td>\n",
       "      <td>32</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>275</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>56.50</td>\n",
       "      <td>55.65</td>\n",
       "      <td>-11.700005</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00280000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.572636</td>\n",
       "      <td>True</td>\n",
       "      <td>59.60</td>\n",
       "      <td>1539972289</td>\n",
       "      <td>145</td>\n",
       "      <td>-16.409544</td>\n",
       "      <td>280</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>52.20</td>\n",
       "      <td>51.05</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00285000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.558110</td>\n",
       "      <td>True</td>\n",
       "      <td>55.68</td>\n",
       "      <td>1539700878</td>\n",
       "      <td>239</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>285</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>47.70</td>\n",
       "      <td>46.90</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00290000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.545354</td>\n",
       "      <td>True</td>\n",
       "      <td>61.50</td>\n",
       "      <td>1539877121</td>\n",
       "      <td>152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>290</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>43.65</td>\n",
       "      <td>42.50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00295000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.532597</td>\n",
       "      <td>True</td>\n",
       "      <td>66.65</td>\n",
       "      <td>1539794785</td>\n",
       "      <td>145</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>295</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>39.15</td>\n",
       "      <td>38.45</td>\n",
       "      <td>-13.320000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00300000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.513677</td>\n",
       "      <td>True</td>\n",
       "      <td>39.69</td>\n",
       "      <td>1539978883</td>\n",
       "      <td>462</td>\n",
       "      <td>-25.127333</td>\n",
       "      <td>300</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>35.20</td>\n",
       "      <td>34.50</td>\n",
       "      <td>-19.899998</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00305000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.502385</td>\n",
       "      <td>True</td>\n",
       "      <td>36.45</td>\n",
       "      <td>1539977469</td>\n",
       "      <td>229</td>\n",
       "      <td>-35.314990</td>\n",
       "      <td>305</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>31.30</td>\n",
       "      <td>30.65</td>\n",
       "      <td>-12.230000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00310000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.499151</td>\n",
       "      <td>True</td>\n",
       "      <td>31.50</td>\n",
       "      <td>1539978905</td>\n",
       "      <td>453</td>\n",
       "      <td>-27.967068</td>\n",
       "      <td>310</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>27.60</td>\n",
       "      <td>26.95</td>\n",
       "      <td>-23.260002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00315000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.485387</td>\n",
       "      <td>True</td>\n",
       "      <td>27.39</td>\n",
       "      <td>1539979061</td>\n",
       "      <td>517</td>\n",
       "      <td>-45.923004</td>\n",
       "      <td>315</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>24.15</td>\n",
       "      <td>23.60</td>\n",
       "      <td>-10.950001</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00320000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.473821</td>\n",
       "      <td>True</td>\n",
       "      <td>24.61</td>\n",
       "      <td>1539978883</td>\n",
       "      <td>806</td>\n",
       "      <td>-30.793026</td>\n",
       "      <td>320</td>\n",
       "      <td>403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20.90</td>\n",
       "      <td>20.50</td>\n",
       "      <td>-10.500000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00325000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.462286</td>\n",
       "      <td>True</td>\n",
       "      <td>21.31</td>\n",
       "      <td>1539978042</td>\n",
       "      <td>815</td>\n",
       "      <td>-33.008488</td>\n",
       "      <td>325</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>17.95</td>\n",
       "      <td>17.55</td>\n",
       "      <td>-9.760000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00330000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.453130</td>\n",
       "      <td>True</td>\n",
       "      <td>17.74</td>\n",
       "      <td>1539979189</td>\n",
       "      <td>813</td>\n",
       "      <td>-35.490910</td>\n",
       "      <td>330</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>15.30</td>\n",
       "      <td>14.90</td>\n",
       "      <td>-9.329999</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00335000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.445928</td>\n",
       "      <td>False</td>\n",
       "      <td>14.97</td>\n",
       "      <td>1539979197</td>\n",
       "      <td>1851</td>\n",
       "      <td>-38.395058</td>\n",
       "      <td>335</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>12.85</td>\n",
       "      <td>12.50</td>\n",
       "      <td>-8.250000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00340000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.437567</td>\n",
       "      <td>False</td>\n",
       "      <td>12.65</td>\n",
       "      <td>1539979186</td>\n",
       "      <td>2974</td>\n",
       "      <td>-39.473686</td>\n",
       "      <td>340</td>\n",
       "      <td>556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10.70</td>\n",
       "      <td>10.30</td>\n",
       "      <td>-7.509999</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00345000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.430853</td>\n",
       "      <td>False</td>\n",
       "      <td>10.47</td>\n",
       "      <td>1539979049</td>\n",
       "      <td>1096</td>\n",
       "      <td>-41.768627</td>\n",
       "      <td>345</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>8.85</td>\n",
       "      <td>8.45</td>\n",
       "      <td>-6.800000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00350000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.425848</td>\n",
       "      <td>False</td>\n",
       "      <td>8.70</td>\n",
       "      <td>1539979145</td>\n",
       "      <td>14118</td>\n",
       "      <td>-43.870968</td>\n",
       "      <td>350</td>\n",
       "      <td>2265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7.20</td>\n",
       "      <td>6.90</td>\n",
       "      <td>-5.900000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00355000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.419867</td>\n",
       "      <td>False</td>\n",
       "      <td>7.10</td>\n",
       "      <td>1539979076</td>\n",
       "      <td>838</td>\n",
       "      <td>-45.384617</td>\n",
       "      <td>355</td>\n",
       "      <td>746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>5.85</td>\n",
       "      <td>5.55</td>\n",
       "      <td>-5.330000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00360000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.416449</td>\n",
       "      <td>False</td>\n",
       "      <td>5.67</td>\n",
       "      <td>1539979179</td>\n",
       "      <td>6479</td>\n",
       "      <td>-48.454544</td>\n",
       "      <td>360</td>\n",
       "      <td>740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>4.70</td>\n",
       "      <td>4.45</td>\n",
       "      <td>-4.560000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00365000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.413092</td>\n",
       "      <td>False</td>\n",
       "      <td>4.56</td>\n",
       "      <td>1539979197</td>\n",
       "      <td>1889</td>\n",
       "      <td>-50.000000</td>\n",
       "      <td>365</td>\n",
       "      <td>499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3.75</td>\n",
       "      <td>3.50</td>\n",
       "      <td>-3.880000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00370000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.410528</td>\n",
       "      <td>False</td>\n",
       "      <td>3.62</td>\n",
       "      <td>1539979165</td>\n",
       "      <td>3149</td>\n",
       "      <td>-51.733334</td>\n",
       "      <td>370</td>\n",
       "      <td>855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.66</td>\n",
       "      <td>0.60</td>\n",
       "      <td>-0.900000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00405000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.405035</td>\n",
       "      <td>False</td>\n",
       "      <td>0.62</td>\n",
       "      <td>1539979042</td>\n",
       "      <td>717</td>\n",
       "      <td>-59.210526</td>\n",
       "      <td>405</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.52</td>\n",
       "      <td>0.43</td>\n",
       "      <td>-0.690000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00410000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.407232</td>\n",
       "      <td>False</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1539979182</td>\n",
       "      <td>1581</td>\n",
       "      <td>-58.974354</td>\n",
       "      <td>410</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.43</td>\n",
       "      <td>0.33</td>\n",
       "      <td>-0.520000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00415000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.412848</td>\n",
       "      <td>False</td>\n",
       "      <td>0.40</td>\n",
       "      <td>1539978164</td>\n",
       "      <td>1485</td>\n",
       "      <td>-56.521736</td>\n",
       "      <td>415</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.34</td>\n",
       "      <td>0.26</td>\n",
       "      <td>-0.380000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00420000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.415533</td>\n",
       "      <td>False</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1539979192</td>\n",
       "      <td>1024</td>\n",
       "      <td>-53.521122</td>\n",
       "      <td>420</td>\n",
       "      <td>601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.29</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-0.290000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00425000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.422369</td>\n",
       "      <td>False</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1539976580</td>\n",
       "      <td>1552</td>\n",
       "      <td>-50.000000</td>\n",
       "      <td>425</td>\n",
       "      <td>392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.24</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-0.240000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00430000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.427740</td>\n",
       "      <td>False</td>\n",
       "      <td>0.21</td>\n",
       "      <td>1539978611</td>\n",
       "      <td>1626</td>\n",
       "      <td>-53.333336</td>\n",
       "      <td>430</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.21</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-0.220000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00435000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.435553</td>\n",
       "      <td>False</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1539978131</td>\n",
       "      <td>251</td>\n",
       "      <td>-55.000000</td>\n",
       "      <td>435</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.18</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-0.150000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00440000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.442388</td>\n",
       "      <td>False</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1539970965</td>\n",
       "      <td>505</td>\n",
       "      <td>-45.454548</td>\n",
       "      <td>440</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.17</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-0.110000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00445000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.454107</td>\n",
       "      <td>False</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1539975130</td>\n",
       "      <td>316</td>\n",
       "      <td>-40.740740</td>\n",
       "      <td>445</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.15</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.050000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00450000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.461919</td>\n",
       "      <td>False</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1539974606</td>\n",
       "      <td>1062</td>\n",
       "      <td>-24.999998</td>\n",
       "      <td>450</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.14</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00455000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.471685</td>\n",
       "      <td>False</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1539891938</td>\n",
       "      <td>246</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>455</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.13</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.080000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00460000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.481450</td>\n",
       "      <td>False</td>\n",
       "      <td>0.08</td>\n",
       "      <td>1539978122</td>\n",
       "      <td>345</td>\n",
       "      <td>-50.000000</td>\n",
       "      <td>460</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.12</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00465000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.491216</td>\n",
       "      <td>False</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1539876483</td>\n",
       "      <td>262</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>465</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.12</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00470000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.504888</td>\n",
       "      <td>False</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1539955862</td>\n",
       "      <td>372</td>\n",
       "      <td>13.333329</td>\n",
       "      <td>470</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.11</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00475000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.512700</td>\n",
       "      <td>False</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1539888945</td>\n",
       "      <td>175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>475</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.10</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.150000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00480000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.503911</td>\n",
       "      <td>False</td>\n",
       "      <td>0.08</td>\n",
       "      <td>1539975597</td>\n",
       "      <td>161</td>\n",
       "      <td>-65.217390</td>\n",
       "      <td>480</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.11</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00485000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.516606</td>\n",
       "      <td>False</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1539798209</td>\n",
       "      <td>38</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>485</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.13</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00490000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.525395</td>\n",
       "      <td>False</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1539969888</td>\n",
       "      <td>163</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>490</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.090000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00495000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.507817</td>\n",
       "      <td>False</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1539976923</td>\n",
       "      <td>157</td>\n",
       "      <td>-64.285720</td>\n",
       "      <td>495</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00500000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.544926</td>\n",
       "      <td>False</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1539870734</td>\n",
       "      <td>455</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00505000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.546880</td>\n",
       "      <td>False</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1539783007</td>\n",
       "      <td>120</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>505</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.27</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-0.170000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00510000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.650882</td>\n",
       "      <td>False</td>\n",
       "      <td>0.24</td>\n",
       "      <td>1539374101</td>\n",
       "      <td>65</td>\n",
       "      <td>-41.463417</td>\n",
       "      <td>510</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00515000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.564457</td>\n",
       "      <td>False</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1539786105</td>\n",
       "      <td>70</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>515</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00520000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.589848</td>\n",
       "      <td>False</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1539786202</td>\n",
       "      <td>80</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>520</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.13</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00525000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.605473</td>\n",
       "      <td>False</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1539615450</td>\n",
       "      <td>110</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>525</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>0.20</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-0.210000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00530000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.674808</td>\n",
       "      <td>False</td>\n",
       "      <td>0.28</td>\n",
       "      <td>1538758861</td>\n",
       "      <td>10</td>\n",
       "      <td>-75.000000</td>\n",
       "      <td>530</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>0.13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.080000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00535000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.623051</td>\n",
       "      <td>False</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1539978131</td>\n",
       "      <td>26</td>\n",
       "      <td>-88.888890</td>\n",
       "      <td>535</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>0.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00540000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.617191</td>\n",
       "      <td>False</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1539801808</td>\n",
       "      <td>118</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>540</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>0.09</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00545000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.623051</td>\n",
       "      <td>False</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1539802875</td>\n",
       "      <td>50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>545</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.07</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.060000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116C00550000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.632816</td>\n",
       "      <td>False</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1539976876</td>\n",
       "      <td>346</td>\n",
       "      <td>-75.000000</td>\n",
       "      <td>550</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ask     bid     change contractSize       contractSymbol currency  \\\n",
       "0   109.10  108.05  -5.550003      REGULAR  NFLX181116C00225000      USD   \n",
       "1   112.55  110.40   0.000000      REGULAR  NFLX181116C00230000      USD   \n",
       "2    99.30   98.00 -15.650002      REGULAR  NFLX181116C00235000      USD   \n",
       "3    94.45   93.15   0.000000      REGULAR  NFLX181116C00240000      USD   \n",
       "4    89.75   88.30   0.000000      REGULAR  NFLX181116C00245000      USD   \n",
       "5    84.85   83.75 -11.400002      REGULAR  NFLX181116C00250000      USD   \n",
       "6    80.10   78.80   0.000000      REGULAR  NFLX181116C00255000      USD   \n",
       "7    75.35   74.05 -12.500000      REGULAR  NFLX181116C00260000      USD   \n",
       "8    70.65   69.35  -2.150002      REGULAR  NFLX181116C00265000      USD   \n",
       "9    65.95   64.75 -27.860000      REGULAR  NFLX181116C00270000      USD   \n",
       "10   61.20   60.00   0.000000      REGULAR  NFLX181116C00275000      USD   \n",
       "11   56.50   55.65 -11.700005      REGULAR  NFLX181116C00280000      USD   \n",
       "12   52.20   51.05   0.000000      REGULAR  NFLX181116C00285000      USD   \n",
       "13   47.70   46.90   0.000000      REGULAR  NFLX181116C00290000      USD   \n",
       "14   43.65   42.50   0.000000      REGULAR  NFLX181116C00295000      USD   \n",
       "15   39.15   38.45 -13.320000      REGULAR  NFLX181116C00300000      USD   \n",
       "16   35.20   34.50 -19.899998      REGULAR  NFLX181116C00305000      USD   \n",
       "17   31.30   30.65 -12.230000      REGULAR  NFLX181116C00310000      USD   \n",
       "18   27.60   26.95 -23.260002      REGULAR  NFLX181116C00315000      USD   \n",
       "19   24.15   23.60 -10.950001      REGULAR  NFLX181116C00320000      USD   \n",
       "20   20.90   20.50 -10.500000      REGULAR  NFLX181116C00325000      USD   \n",
       "21   17.95   17.55  -9.760000      REGULAR  NFLX181116C00330000      USD   \n",
       "22   15.30   14.90  -9.329999      REGULAR  NFLX181116C00335000      USD   \n",
       "23   12.85   12.50  -8.250000      REGULAR  NFLX181116C00340000      USD   \n",
       "24   10.70   10.30  -7.509999      REGULAR  NFLX181116C00345000      USD   \n",
       "25    8.85    8.45  -6.800000      REGULAR  NFLX181116C00350000      USD   \n",
       "26    7.20    6.90  -5.900000      REGULAR  NFLX181116C00355000      USD   \n",
       "27    5.85    5.55  -5.330000      REGULAR  NFLX181116C00360000      USD   \n",
       "28    4.70    4.45  -4.560000      REGULAR  NFLX181116C00365000      USD   \n",
       "29    3.75    3.50  -3.880000      REGULAR  NFLX181116C00370000      USD   \n",
       "..     ...     ...        ...          ...                  ...      ...   \n",
       "36    0.66    0.60  -0.900000      REGULAR  NFLX181116C00405000      USD   \n",
       "37    0.52    0.43  -0.690000      REGULAR  NFLX181116C00410000      USD   \n",
       "38    0.43    0.33  -0.520000      REGULAR  NFLX181116C00415000      USD   \n",
       "39    0.34    0.26  -0.380000      REGULAR  NFLX181116C00420000      USD   \n",
       "40    0.29    0.20  -0.290000      REGULAR  NFLX181116C00425000      USD   \n",
       "41    0.24    0.20  -0.240000      REGULAR  NFLX181116C00430000      USD   \n",
       "42    0.21    0.12  -0.220000      REGULAR  NFLX181116C00435000      USD   \n",
       "43    0.18    0.10  -0.150000      REGULAR  NFLX181116C00440000      USD   \n",
       "44    0.17    0.07  -0.110000      REGULAR  NFLX181116C00445000      USD   \n",
       "45    0.15    0.05  -0.050000      REGULAR  NFLX181116C00450000      USD   \n",
       "46    0.14    0.04   0.000000      REGULAR  NFLX181116C00455000      USD   \n",
       "47    0.13    0.05  -0.080000      REGULAR  NFLX181116C00460000      USD   \n",
       "48    0.12    0.03   0.000000      REGULAR  NFLX181116C00465000      USD   \n",
       "49    0.12    0.02   0.020000      REGULAR  NFLX181116C00470000      USD   \n",
       "50    0.11    0.02   0.000000      REGULAR  NFLX181116C00475000      USD   \n",
       "51    0.10    0.05  -0.150000      REGULAR  NFLX181116C00480000      USD   \n",
       "52    0.11    0.04   0.000000      REGULAR  NFLX181116C00485000      USD   \n",
       "53    0.13    0.01   0.000000      REGULAR  NFLX181116C00490000      USD   \n",
       "54    0.04    0.00  -0.090000      REGULAR  NFLX181116C00495000      USD   \n",
       "55    0.13    0.00   0.000000      REGULAR  NFLX181116C00500000      USD   \n",
       "56    0.11    0.00   0.000000      REGULAR  NFLX181116C00505000      USD   \n",
       "57    0.27    0.17  -0.170000      REGULAR  NFLX181116C00510000      USD   \n",
       "58    0.10    0.00   0.000000      REGULAR  NFLX181116C00515000      USD   \n",
       "59    0.13    0.00   0.000000      REGULAR  NFLX181116C00520000      USD   \n",
       "60    0.13    0.01   0.000000      REGULAR  NFLX181116C00525000      USD   \n",
       "61    0.20    0.12  -0.210000      REGULAR  NFLX181116C00530000      USD   \n",
       "62    0.13    0.00  -0.080000      REGULAR  NFLX181116C00535000      USD   \n",
       "63    0.10    0.00   0.000000      REGULAR  NFLX181116C00540000      USD   \n",
       "64    0.09    0.00   0.000000      REGULAR  NFLX181116C00545000      USD   \n",
       "65    0.07    0.02  -0.060000      REGULAR  NFLX181116C00550000      USD   \n",
       "\n",
       "    expiration  impliedVolatility  inTheMoney  lastPrice  lastTradeDate  \\\n",
       "0   1542326400           0.793947        True     130.00     1539959582   \n",
       "1   1542326400           1.353763        True     122.08     1537214332   \n",
       "2   1542326400           0.729251        True     111.75     1539964516   \n",
       "3   1542326400           0.711673        True     122.45     1539803206   \n",
       "4   1542326400           0.700198        True     104.80     1539879100   \n",
       "5   1542326400           0.689945        True      89.60     1539972054   \n",
       "6   1542326400           0.664798        True      82.62     1539622122   \n",
       "7   1542326400           0.646488        True      87.85     1539965323   \n",
       "8   1542326400           0.629398        True      70.65     1539976510   \n",
       "9   1542326400           0.612919        True      73.56     1539969611   \n",
       "10  1542326400           0.587406        True      86.45     1539793733   \n",
       "11  1542326400           0.572636        True      59.60     1539972289   \n",
       "12  1542326400           0.558110        True      55.68     1539700878   \n",
       "13  1542326400           0.545354        True      61.50     1539877121   \n",
       "14  1542326400           0.532597        True      66.65     1539794785   \n",
       "15  1542326400           0.513677        True      39.69     1539978883   \n",
       "16  1542326400           0.502385        True      36.45     1539977469   \n",
       "17  1542326400           0.499151        True      31.50     1539978905   \n",
       "18  1542326400           0.485387        True      27.39     1539979061   \n",
       "19  1542326400           0.473821        True      24.61     1539978883   \n",
       "20  1542326400           0.462286        True      21.31     1539978042   \n",
       "21  1542326400           0.453130        True      17.74     1539979189   \n",
       "22  1542326400           0.445928       False      14.97     1539979197   \n",
       "23  1542326400           0.437567       False      12.65     1539979186   \n",
       "24  1542326400           0.430853       False      10.47     1539979049   \n",
       "25  1542326400           0.425848       False       8.70     1539979145   \n",
       "26  1542326400           0.419867       False       7.10     1539979076   \n",
       "27  1542326400           0.416449       False       5.67     1539979179   \n",
       "28  1542326400           0.413092       False       4.56     1539979197   \n",
       "29  1542326400           0.410528       False       3.62     1539979165   \n",
       "..         ...                ...         ...        ...            ...   \n",
       "36  1542326400           0.405035       False       0.62     1539979042   \n",
       "37  1542326400           0.407232       False       0.48     1539979182   \n",
       "38  1542326400           0.412848       False       0.40     1539978164   \n",
       "39  1542326400           0.415533       False       0.33     1539979192   \n",
       "40  1542326400           0.422369       False       0.29     1539976580   \n",
       "41  1542326400           0.427740       False       0.21     1539978611   \n",
       "42  1542326400           0.435553       False       0.18     1539978131   \n",
       "43  1542326400           0.442388       False       0.18     1539970965   \n",
       "44  1542326400           0.454107       False       0.16     1539975130   \n",
       "45  1542326400           0.461919       False       0.15     1539974606   \n",
       "46  1542326400           0.471685       False       0.18     1539891938   \n",
       "47  1542326400           0.481450       False       0.08     1539978122   \n",
       "48  1542326400           0.491216       False       0.19     1539876483   \n",
       "49  1542326400           0.504888       False       0.17     1539955862   \n",
       "50  1542326400           0.512700       False       0.11     1539888945   \n",
       "51  1542326400           0.503911       False       0.08     1539975597   \n",
       "52  1542326400           0.516606       False       0.19     1539798209   \n",
       "53  1542326400           0.525395       False       0.09     1539969888   \n",
       "54  1542326400           0.507817       False       0.05     1539976923   \n",
       "55  1542326400           0.544926       False       0.12     1539870734   \n",
       "56  1542326400           0.546880       False       0.30     1539783007   \n",
       "57  1542326400           0.650882       False       0.24     1539374101   \n",
       "58  1542326400           0.564457       False       0.16     1539786105   \n",
       "59  1542326400           0.589848       False       0.17     1539786202   \n",
       "60  1542326400           0.605473       False       0.16     1539615450   \n",
       "61  1542326400           0.674808       False       0.28     1538758861   \n",
       "62  1542326400           0.623051       False       0.01     1539978131   \n",
       "63  1542326400           0.617191       False       0.09     1539801808   \n",
       "64  1542326400           0.623051       False       0.09     1539802875   \n",
       "65  1542326400           0.632816       False       0.02     1539976876   \n",
       "\n",
       "    openInterest  percentChange  strike  volume  \n",
       "0             11      -4.094432     225       8  \n",
       "1              2       0.000000     230       1  \n",
       "2              7     -12.284145     235       1  \n",
       "3             20       0.000000     240       2  \n",
       "4              6       0.000000     245       1  \n",
       "5             30     -11.287130     250      38  \n",
       "6             24       0.000000     255       6  \n",
       "7             61     -12.456403     260       1  \n",
       "8             14      -2.953299     265       1  \n",
       "9             35     -27.469927     270       1  \n",
       "10            32       0.000000     275       5  \n",
       "11           145     -16.409544     280       8  \n",
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       "13           152       0.000000     290      10  \n",
       "14           145       0.000000     295       1  \n",
       "15           462     -25.127333     300     374  \n",
       "16           229     -35.314990     305      18  \n",
       "17           453     -27.967068     310      52  \n",
       "18           517     -45.923004     315      38  \n",
       "19           806     -30.793026     320     403  \n",
       "20           815     -33.008488     325      44  \n",
       "21           813     -35.490910     330     144  \n",
       "22          1851     -38.395058     335     220  \n",
       "23          2974     -39.473686     340     556  \n",
       "24          1096     -41.768627     345     319  \n",
       "25         14118     -43.870968     350    2265  \n",
       "26           838     -45.384617     355     746  \n",
       "27          6479     -48.454544     360     740  \n",
       "28          1889     -50.000000     365     499  \n",
       "29          3149     -51.733334     370     855  \n",
       "..           ...            ...     ...     ...  \n",
       "36           717     -59.210526     405     151  \n",
       "37          1581     -58.974354     410     318  \n",
       "38          1485     -56.521736     415     243  \n",
       "39          1024     -53.521122     420     601  \n",
       "40          1552     -50.000000     425     392  \n",
       "41          1626     -53.333336     430     201  \n",
       "42           251     -55.000000     435      20  \n",
       "43           505     -45.454548     440      21  \n",
       "44           316     -40.740740     445      41  \n",
       "45          1062     -24.999998     450      49  \n",
       "46           246       0.000000     455      29  \n",
       "47           345     -50.000000     460       3  \n",
       "48           262       0.000000     465      32  \n",
       "49           372      13.333329     470       1  \n",
       "50           175       0.000000     475      23  \n",
       "51           161     -65.217390     480      12  \n",
       "52            38       0.000000     485       2  \n",
       "53           163       0.000000     490       9  \n",
       "54           157     -64.285720     495       5  \n",
       "55           455       0.000000     500       1  \n",
       "56           120       0.000000     505       1  \n",
       "57            65     -41.463417     510       1  \n",
       "58            70       0.000000     515       5  \n",
       "59            80       0.000000     520      20  \n",
       "60           110       0.000000     525     100  \n",
       "61            10     -75.000000     530       3  \n",
       "62            26     -88.888890     535       2  \n",
       "63           118       0.000000     540      10  \n",
       "64            50       0.000000     545      34  \n",
       "65           346     -75.000000     550      11  \n",
       "\n",
       "[66 rows x 15 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(option_calls_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['options']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Option Puts Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.yahoo.extract_df_from_redis import extract_option_puts_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, option_puts_df = extract_option_puts_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ask</th>\n",
       "      <th>bid</th>\n",
       "      <th>change</th>\n",
       "      <th>contractSize</th>\n",
       "      <th>contractSymbol</th>\n",
       "      <th>currency</th>\n",
       "      <th>expiration</th>\n",
       "      <th>impliedVolatility</th>\n",
       "      <th>inTheMoney</th>\n",
       "      <th>lastPrice</th>\n",
       "      <th>lastTradeDate</th>\n",
       "      <th>openInterest</th>\n",
       "      <th>percentChange</th>\n",
       "      <th>strike</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.50</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.110000</td>\n",
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       "      <td>NFLX181116P00220000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
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       "    <tr>\n",
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       "      <td>0.55</td>\n",
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       "      <td>0.720706</td>\n",
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       "      <td>225</td>\n",
       "      <td>264</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.64</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00230000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.704105</td>\n",
       "      <td>False</td>\n",
       "      <td>0.57</td>\n",
       "      <td>1539978200</td>\n",
       "      <td>155</td>\n",
       "      <td>32.558136</td>\n",
       "      <td>230</td>\n",
       "      <td>46</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.75</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.160000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00235000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.687503</td>\n",
       "      <td>False</td>\n",
       "      <td>0.66</td>\n",
       "      <td>1539973824</td>\n",
       "      <td>177</td>\n",
       "      <td>32.000004</td>\n",
       "      <td>235</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.87</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00240000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.669925</td>\n",
       "      <td>False</td>\n",
       "      <td>0.83</td>\n",
       "      <td>1539976206</td>\n",
       "      <td>396</td>\n",
       "      <td>43.103450</td>\n",
       "      <td>240</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.01</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00245000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.653568</td>\n",
       "      <td>False</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1539978308</td>\n",
       "      <td>433</td>\n",
       "      <td>35.714287</td>\n",
       "      <td>245</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.16</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.360000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00250000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.635013</td>\n",
       "      <td>False</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1539979175</td>\n",
       "      <td>2336</td>\n",
       "      <td>45.569614</td>\n",
       "      <td>250</td>\n",
       "      <td>269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.39</td>\n",
       "      <td>1.29</td>\n",
       "      <td>0.330000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00255000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.623295</td>\n",
       "      <td>False</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1539978298</td>\n",
       "      <td>397</td>\n",
       "      <td>34.020607</td>\n",
       "      <td>255</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.61</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00260000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.606449</td>\n",
       "      <td>False</td>\n",
       "      <td>1.51</td>\n",
       "      <td>1539978681</td>\n",
       "      <td>397</td>\n",
       "      <td>36.036034</td>\n",
       "      <td>260</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.88</td>\n",
       "      <td>1.76</td>\n",
       "      <td>0.540000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00265000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.591069</td>\n",
       "      <td>False</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1539978980</td>\n",
       "      <td>602</td>\n",
       "      <td>42.857140</td>\n",
       "      <td>265</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.20</td>\n",
       "      <td>2.07</td>\n",
       "      <td>0.540000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00270000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.576176</td>\n",
       "      <td>False</td>\n",
       "      <td>2.07</td>\n",
       "      <td>1539978865</td>\n",
       "      <td>1023</td>\n",
       "      <td>35.294117</td>\n",
       "      <td>270</td>\n",
       "      <td>398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.57</td>\n",
       "      <td>2.48</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00275000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.562749</td>\n",
       "      <td>False</td>\n",
       "      <td>2.35</td>\n",
       "      <td>1539978835</td>\n",
       "      <td>1172</td>\n",
       "      <td>30.555552</td>\n",
       "      <td>275</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2.99</td>\n",
       "      <td>2.86</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00280000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.546269</td>\n",
       "      <td>False</td>\n",
       "      <td>2.95</td>\n",
       "      <td>1539979109</td>\n",
       "      <td>1463</td>\n",
       "      <td>41.826930</td>\n",
       "      <td>280</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3.55</td>\n",
       "      <td>3.35</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00285000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.533086</td>\n",
       "      <td>False</td>\n",
       "      <td>3.31</td>\n",
       "      <td>1539978630</td>\n",
       "      <td>1564</td>\n",
       "      <td>35.655730</td>\n",
       "      <td>285</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4.20</td>\n",
       "      <td>3.95</td>\n",
       "      <td>1.180000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00290000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.520452</td>\n",
       "      <td>False</td>\n",
       "      <td>4.03</td>\n",
       "      <td>1539979103</td>\n",
       "      <td>1275</td>\n",
       "      <td>41.403520</td>\n",
       "      <td>290</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4.90</td>\n",
       "      <td>4.65</td>\n",
       "      <td>1.480000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00295000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.506841</td>\n",
       "      <td>False</td>\n",
       "      <td>4.85</td>\n",
       "      <td>1539979165</td>\n",
       "      <td>1616</td>\n",
       "      <td>43.916916</td>\n",
       "      <td>295</td>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5.70</td>\n",
       "      <td>5.50</td>\n",
       "      <td>1.660000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00300000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.497503</td>\n",
       "      <td>False</td>\n",
       "      <td>5.60</td>\n",
       "      <td>1539979161</td>\n",
       "      <td>3765</td>\n",
       "      <td>42.131977</td>\n",
       "      <td>300</td>\n",
       "      <td>1370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>6.75</td>\n",
       "      <td>6.50</td>\n",
       "      <td>1.970000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00305000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.487493</td>\n",
       "      <td>False</td>\n",
       "      <td>6.65</td>\n",
       "      <td>1539979159</td>\n",
       "      <td>1153</td>\n",
       "      <td>42.094025</td>\n",
       "      <td>305</td>\n",
       "      <td>527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>7.90</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.370000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00310000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.475591</td>\n",
       "      <td>False</td>\n",
       "      <td>7.78</td>\n",
       "      <td>1539979197</td>\n",
       "      <td>1717</td>\n",
       "      <td>43.807774</td>\n",
       "      <td>310</td>\n",
       "      <td>1016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>9.25</td>\n",
       "      <td>9.00</td>\n",
       "      <td>2.980000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00315000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.464666</td>\n",
       "      <td>False</td>\n",
       "      <td>9.13</td>\n",
       "      <td>1539979197</td>\n",
       "      <td>6093</td>\n",
       "      <td>48.455284</td>\n",
       "      <td>315</td>\n",
       "      <td>3343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10.85</td>\n",
       "      <td>10.55</td>\n",
       "      <td>3.150000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00320000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.455572</td>\n",
       "      <td>False</td>\n",
       "      <td>10.65</td>\n",
       "      <td>1539979135</td>\n",
       "      <td>3873</td>\n",
       "      <td>41.999996</td>\n",
       "      <td>320</td>\n",
       "      <td>1383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>12.60</td>\n",
       "      <td>12.35</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00325000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.444708</td>\n",
       "      <td>False</td>\n",
       "      <td>12.55</td>\n",
       "      <td>1539979161</td>\n",
       "      <td>2884</td>\n",
       "      <td>43.428574</td>\n",
       "      <td>325</td>\n",
       "      <td>892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>14.70</td>\n",
       "      <td>14.35</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00330000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.437323</td>\n",
       "      <td>False</td>\n",
       "      <td>14.60</td>\n",
       "      <td>1539979147</td>\n",
       "      <td>3749</td>\n",
       "      <td>42.439030</td>\n",
       "      <td>330</td>\n",
       "      <td>1109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>17.10</td>\n",
       "      <td>16.65</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00335000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.431555</td>\n",
       "      <td>True</td>\n",
       "      <td>16.75</td>\n",
       "      <td>1539979096</td>\n",
       "      <td>2363</td>\n",
       "      <td>39.583336</td>\n",
       "      <td>335</td>\n",
       "      <td>812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>19.65</td>\n",
       "      <td>19.25</td>\n",
       "      <td>5.179999</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00340000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.423132</td>\n",
       "      <td>True</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1539978991</td>\n",
       "      <td>4503</td>\n",
       "      <td>37.755096</td>\n",
       "      <td>340</td>\n",
       "      <td>1156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>22.55</td>\n",
       "      <td>22.10</td>\n",
       "      <td>6.280001</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00345000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.417425</td>\n",
       "      <td>True</td>\n",
       "      <td>22.33</td>\n",
       "      <td>1539979135</td>\n",
       "      <td>2004</td>\n",
       "      <td>39.127730</td>\n",
       "      <td>345</td>\n",
       "      <td>884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>25.80</td>\n",
       "      <td>25.20</td>\n",
       "      <td>6.949999</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00350000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.414801</td>\n",
       "      <td>True</td>\n",
       "      <td>25.30</td>\n",
       "      <td>1539979011</td>\n",
       "      <td>13129</td>\n",
       "      <td>37.874650</td>\n",
       "      <td>350</td>\n",
       "      <td>515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>29.25</td>\n",
       "      <td>28.55</td>\n",
       "      <td>8.650000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00355000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.411322</td>\n",
       "      <td>True</td>\n",
       "      <td>29.10</td>\n",
       "      <td>1539979188</td>\n",
       "      <td>1217</td>\n",
       "      <td>42.298283</td>\n",
       "      <td>355</td>\n",
       "      <td>685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>32.90</td>\n",
       "      <td>32.15</td>\n",
       "      <td>8.519999</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00360000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.407232</td>\n",
       "      <td>True</td>\n",
       "      <td>32.35</td>\n",
       "      <td>1539979040</td>\n",
       "      <td>4889</td>\n",
       "      <td>35.753246</td>\n",
       "      <td>360</td>\n",
       "      <td>309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>36.85</td>\n",
       "      <td>36.05</td>\n",
       "      <td>10.209999</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00365000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.406683</td>\n",
       "      <td>True</td>\n",
       "      <td>36.00</td>\n",
       "      <td>1539979001</td>\n",
       "      <td>1024</td>\n",
       "      <td>39.588980</td>\n",
       "      <td>365</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>45.25</td>\n",
       "      <td>44.35</td>\n",
       "      <td>3.399998</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00375000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.406317</td>\n",
       "      <td>True</td>\n",
       "      <td>36.10</td>\n",
       "      <td>1539968382</td>\n",
       "      <td>1457</td>\n",
       "      <td>10.397546</td>\n",
       "      <td>375</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>49.65</td>\n",
       "      <td>48.70</td>\n",
       "      <td>11.660000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00380000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.406134</td>\n",
       "      <td>True</td>\n",
       "      <td>47.84</td>\n",
       "      <td>1539977926</td>\n",
       "      <td>1166</td>\n",
       "      <td>32.227750</td>\n",
       "      <td>380</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>54.25</td>\n",
       "      <td>53.30</td>\n",
       "      <td>12.240002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00385000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.411261</td>\n",
       "      <td>True</td>\n",
       "      <td>52.65</td>\n",
       "      <td>1539977066</td>\n",
       "      <td>362</td>\n",
       "      <td>30.289537</td>\n",
       "      <td>385</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>58.80</td>\n",
       "      <td>57.90</td>\n",
       "      <td>14.250000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00390000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.408331</td>\n",
       "      <td>True</td>\n",
       "      <td>57.55</td>\n",
       "      <td>1539978976</td>\n",
       "      <td>269</td>\n",
       "      <td>32.909930</td>\n",
       "      <td>390</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>63.75</td>\n",
       "      <td>62.40</td>\n",
       "      <td>20.400002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00395000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.428717</td>\n",
       "      <td>True</td>\n",
       "      <td>59.70</td>\n",
       "      <td>1539973385</td>\n",
       "      <td>231</td>\n",
       "      <td>51.908405</td>\n",
       "      <td>395</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>68.40</td>\n",
       "      <td>67.40</td>\n",
       "      <td>14.860001</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00400000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.424322</td>\n",
       "      <td>True</td>\n",
       "      <td>67.00</td>\n",
       "      <td>1539976612</td>\n",
       "      <td>197</td>\n",
       "      <td>28.500193</td>\n",
       "      <td>400</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>73.40</td>\n",
       "      <td>72.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00405000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.446173</td>\n",
       "      <td>True</td>\n",
       "      <td>47.00</td>\n",
       "      <td>1539803987</td>\n",
       "      <td>198</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>405</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>78.20</td>\n",
       "      <td>77.10</td>\n",
       "      <td>12.910000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00410000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.448370</td>\n",
       "      <td>True</td>\n",
       "      <td>75.50</td>\n",
       "      <td>1539972442</td>\n",
       "      <td>186</td>\n",
       "      <td>20.626297</td>\n",
       "      <td>410</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>83.15</td>\n",
       "      <td>82.00</td>\n",
       "      <td>12.010002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00415000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.463384</td>\n",
       "      <td>True</td>\n",
       "      <td>68.16</td>\n",
       "      <td>1539964770</td>\n",
       "      <td>132</td>\n",
       "      <td>21.389141</td>\n",
       "      <td>415</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>88.05</td>\n",
       "      <td>87.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00420000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.471685</td>\n",
       "      <td>True</td>\n",
       "      <td>59.75</td>\n",
       "      <td>1539869953</td>\n",
       "      <td>116</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>420</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>93.05</td>\n",
       "      <td>91.95</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00425000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.490484</td>\n",
       "      <td>True</td>\n",
       "      <td>68.90</td>\n",
       "      <td>1539871087</td>\n",
       "      <td>82</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>425</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>98.10</td>\n",
       "      <td>96.70</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00430000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.515386</td>\n",
       "      <td>True</td>\n",
       "      <td>64.79</td>\n",
       "      <td>1539791280</td>\n",
       "      <td>86</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>430</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>103.05</td>\n",
       "      <td>101.90</td>\n",
       "      <td>11.199997</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00435000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.527348</td>\n",
       "      <td>True</td>\n",
       "      <td>83.00</td>\n",
       "      <td>1539956082</td>\n",
       "      <td>30</td>\n",
       "      <td>15.598881</td>\n",
       "      <td>435</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>108.20</td>\n",
       "      <td>106.75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00440000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.563969</td>\n",
       "      <td>True</td>\n",
       "      <td>76.70</td>\n",
       "      <td>1539786192</td>\n",
       "      <td>26</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>440</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>112.60</td>\n",
       "      <td>111.10</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00445000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.483892</td>\n",
       "      <td>True</td>\n",
       "      <td>122.10</td>\n",
       "      <td>1538068839</td>\n",
       "      <td>39</td>\n",
       "      <td>45.045044</td>\n",
       "      <td>445</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>118.20</td>\n",
       "      <td>116.75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00450000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.599858</td>\n",
       "      <td>True</td>\n",
       "      <td>88.95</td>\n",
       "      <td>1539802114</td>\n",
       "      <td>47</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>450</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>123.10</td>\n",
       "      <td>121.75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00455000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.604252</td>\n",
       "      <td>True</td>\n",
       "      <td>88.75</td>\n",
       "      <td>1539785203</td>\n",
       "      <td>22</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>455</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>128.20</td>\n",
       "      <td>126.75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00460000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.634281</td>\n",
       "      <td>True</td>\n",
       "      <td>112.75</td>\n",
       "      <td>1539891328</td>\n",
       "      <td>19</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>460</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>133.20</td>\n",
       "      <td>131.75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00465000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.503911</td>\n",
       "      <td>True</td>\n",
       "      <td>100.01</td>\n",
       "      <td>1539786468</td>\n",
       "      <td>6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>465</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>138.05</td>\n",
       "      <td>136.75</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00470000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.646732</td>\n",
       "      <td>True</td>\n",
       "      <td>97.21</td>\n",
       "      <td>1539784431</td>\n",
       "      <td>14</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>470</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>136.95</td>\n",
       "      <td>134.50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00475000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>132.20</td>\n",
       "      <td>1539264458</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>475</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>146.95</td>\n",
       "      <td>144.95</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00485000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>114.65</td>\n",
       "      <td>1532145396</td>\n",
       "      <td>7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>485</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>156.90</td>\n",
       "      <td>154.15</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00495000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>121.65</td>\n",
       "      <td>1532145396</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>495</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>168.05</td>\n",
       "      <td>164.30</td>\n",
       "      <td>29.580002</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00500000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.739016</td>\n",
       "      <td>True</td>\n",
       "      <td>157.85</td>\n",
       "      <td>1539014239</td>\n",
       "      <td>0</td>\n",
       "      <td>18.739310</td>\n",
       "      <td>500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>182.05</td>\n",
       "      <td>179.20</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00520000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>142.95</td>\n",
       "      <td>1532145396</td>\n",
       "      <td>26</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>520</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>192.00</td>\n",
       "      <td>195.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00530000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>152.55</td>\n",
       "      <td>1532145396</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>530</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>196.90</td>\n",
       "      <td>199.65</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00535000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>157.40</td>\n",
       "      <td>1532145396</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>535</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>201.95</td>\n",
       "      <td>199.10</td>\n",
       "      <td>47.090010</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00540000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>205.99</td>\n",
       "      <td>1539196817</td>\n",
       "      <td>2</td>\n",
       "      <td>22.860338</td>\n",
       "      <td>540</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>212.95</td>\n",
       "      <td>209.30</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00545000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.844728</td>\n",
       "      <td>True</td>\n",
       "      <td>168.95</td>\n",
       "      <td>1532145396</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>545</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>211.95</td>\n",
       "      <td>209.10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>NFLX181116P00550000</td>\n",
       "      <td>USD</td>\n",
       "      <td>1542326400</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>True</td>\n",
       "      <td>184.98</td>\n",
       "      <td>1537370855</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>550</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ask     bid     change contractSize       contractSymbol currency  \\\n",
       "0     0.50    0.39   0.110000      REGULAR  NFLX181116P00220000      USD   \n",
       "1     0.55    0.48   0.150000      REGULAR  NFLX181116P00225000      USD   \n",
       "2     0.64    0.57   0.140000      REGULAR  NFLX181116P00230000      USD   \n",
       "3     0.75    0.67   0.160000      REGULAR  NFLX181116P00235000      USD   \n",
       "4     0.87    0.78   0.250000      REGULAR  NFLX181116P00240000      USD   \n",
       "5     1.01    0.92   0.250000      REGULAR  NFLX181116P00245000      USD   \n",
       "6     1.16    1.06   0.360000      REGULAR  NFLX181116P00250000      USD   \n",
       "7     1.39    1.29   0.330000      REGULAR  NFLX181116P00255000      USD   \n",
       "8     1.61    1.50   0.400000      REGULAR  NFLX181116P00260000      USD   \n",
       "9     1.88    1.76   0.540000      REGULAR  NFLX181116P00265000      USD   \n",
       "10    2.20    2.07   0.540000      REGULAR  NFLX181116P00270000      USD   \n",
       "11    2.57    2.48   0.550000      REGULAR  NFLX181116P00275000      USD   \n",
       "12    2.99    2.86   0.870000      REGULAR  NFLX181116P00280000      USD   \n",
       "13    3.55    3.35   0.870000      REGULAR  NFLX181116P00285000      USD   \n",
       "14    4.20    3.95   1.180000      REGULAR  NFLX181116P00290000      USD   \n",
       "15    4.90    4.65   1.480000      REGULAR  NFLX181116P00295000      USD   \n",
       "16    5.70    5.50   1.660000      REGULAR  NFLX181116P00300000      USD   \n",
       "17    6.75    6.50   1.970000      REGULAR  NFLX181116P00305000      USD   \n",
       "18    7.90    7.60   2.370000      REGULAR  NFLX181116P00310000      USD   \n",
       "19    9.25    9.00   2.980000      REGULAR  NFLX181116P00315000      USD   \n",
       "20   10.85   10.55   3.150000      REGULAR  NFLX181116P00320000      USD   \n",
       "21   12.60   12.35   3.800000      REGULAR  NFLX181116P00325000      USD   \n",
       "22   14.70   14.35   4.350000      REGULAR  NFLX181116P00330000      USD   \n",
       "23   17.10   16.65   4.750000      REGULAR  NFLX181116P00335000      USD   \n",
       "24   19.65   19.25   5.179999      REGULAR  NFLX181116P00340000      USD   \n",
       "25   22.55   22.10   6.280001      REGULAR  NFLX181116P00345000      USD   \n",
       "26   25.80   25.20   6.949999      REGULAR  NFLX181116P00350000      USD   \n",
       "27   29.25   28.55   8.650000      REGULAR  NFLX181116P00355000      USD   \n",
       "28   32.90   32.15   8.519999      REGULAR  NFLX181116P00360000      USD   \n",
       "29   36.85   36.05  10.209999      REGULAR  NFLX181116P00365000      USD   \n",
       "..     ...     ...        ...          ...                  ...      ...   \n",
       "31   45.25   44.35   3.399998      REGULAR  NFLX181116P00375000      USD   \n",
       "32   49.65   48.70  11.660000      REGULAR  NFLX181116P00380000      USD   \n",
       "33   54.25   53.30  12.240002      REGULAR  NFLX181116P00385000      USD   \n",
       "34   58.80   57.90  14.250000      REGULAR  NFLX181116P00390000      USD   \n",
       "35   63.75   62.40  20.400002      REGULAR  NFLX181116P00395000      USD   \n",
       "36   68.40   67.40  14.860001      REGULAR  NFLX181116P00400000      USD   \n",
       "37   73.40   72.00   0.000000      REGULAR  NFLX181116P00405000      USD   \n",
       "38   78.20   77.10  12.910000      REGULAR  NFLX181116P00410000      USD   \n",
       "39   83.15   82.00  12.010002      REGULAR  NFLX181116P00415000      USD   \n",
       "40   88.05   87.00   0.000000      REGULAR  NFLX181116P00420000      USD   \n",
       "41   93.05   91.95   0.000000      REGULAR  NFLX181116P00425000      USD   \n",
       "42   98.10   96.70   0.000000      REGULAR  NFLX181116P00430000      USD   \n",
       "43  103.05  101.90  11.199997      REGULAR  NFLX181116P00435000      USD   \n",
       "44  108.20  106.75   0.000000      REGULAR  NFLX181116P00440000      USD   \n",
       "45  112.60  111.10  55.000000      REGULAR  NFLX181116P00445000      USD   \n",
       "46  118.20  116.75   0.000000      REGULAR  NFLX181116P00450000      USD   \n",
       "47  123.10  121.75   0.000000      REGULAR  NFLX181116P00455000      USD   \n",
       "48  128.20  126.75   0.000000      REGULAR  NFLX181116P00460000      USD   \n",
       "49  133.20  131.75   0.000000      REGULAR  NFLX181116P00465000      USD   \n",
       "50  138.05  136.75   0.000000      REGULAR  NFLX181116P00470000      USD   \n",
       "51  136.95  134.50   0.000000      REGULAR  NFLX181116P00475000      USD   \n",
       "52  146.95  144.95   0.000000      REGULAR  NFLX181116P00485000      USD   \n",
       "53  156.90  154.15   0.000000      REGULAR  NFLX181116P00495000      USD   \n",
       "54  168.05  164.30  29.580002      REGULAR  NFLX181116P00500000      USD   \n",
       "55  182.05  179.20   0.000000      REGULAR  NFLX181116P00520000      USD   \n",
       "56  192.00  195.00   0.000000      REGULAR  NFLX181116P00530000      USD   \n",
       "57  196.90  199.65   0.000000      REGULAR  NFLX181116P00535000      USD   \n",
       "58  201.95  199.10  47.090010      REGULAR  NFLX181116P00540000      USD   \n",
       "59  212.95  209.30   0.000000      REGULAR  NFLX181116P00545000      USD   \n",
       "60  211.95  209.10   0.000000      REGULAR  NFLX181116P00550000      USD   \n",
       "\n",
       "    expiration  impliedVolatility  inTheMoney  lastPrice  lastTradeDate  \\\n",
       "0   1542326400           0.739260       False       0.42     1539978976   \n",
       "1   1542326400           0.720706       False       0.50     1539975880   \n",
       "2   1542326400           0.704105       False       0.57     1539978200   \n",
       "3   1542326400           0.687503       False       0.66     1539973824   \n",
       "4   1542326400           0.669925       False       0.83     1539976206   \n",
       "5   1542326400           0.653568       False       0.95     1539978308   \n",
       "6   1542326400           0.635013       False       1.15     1539979175   \n",
       "7   1542326400           0.623295       False       1.30     1539978298   \n",
       "8   1542326400           0.606449       False       1.51     1539978681   \n",
       "9   1542326400           0.591069       False       1.80     1539978980   \n",
       "10  1542326400           0.576176       False       2.07     1539978865   \n",
       "11  1542326400           0.562749       False       2.35     1539978835   \n",
       "12  1542326400           0.546269       False       2.95     1539979109   \n",
       "13  1542326400           0.533086       False       3.31     1539978630   \n",
       "14  1542326400           0.520452       False       4.03     1539979103   \n",
       "15  1542326400           0.506841       False       4.85     1539979165   \n",
       "16  1542326400           0.497503       False       5.60     1539979161   \n",
       "17  1542326400           0.487493       False       6.65     1539979159   \n",
       "18  1542326400           0.475591       False       7.78     1539979197   \n",
       "19  1542326400           0.464666       False       9.13     1539979197   \n",
       "20  1542326400           0.455572       False      10.65     1539979135   \n",
       "21  1542326400           0.444708       False      12.55     1539979161   \n",
       "22  1542326400           0.437323       False      14.60     1539979147   \n",
       "23  1542326400           0.431555        True      16.75     1539979096   \n",
       "24  1542326400           0.423132        True      18.90     1539978991   \n",
       "25  1542326400           0.417425        True      22.33     1539979135   \n",
       "26  1542326400           0.414801        True      25.30     1539979011   \n",
       "27  1542326400           0.411322        True      29.10     1539979188   \n",
       "28  1542326400           0.407232        True      32.35     1539979040   \n",
       "29  1542326400           0.406683        True      36.00     1539979001   \n",
       "..         ...                ...         ...        ...            ...   \n",
       "31  1542326400           0.406317        True      36.10     1539968382   \n",
       "32  1542326400           0.406134        True      47.84     1539977926   \n",
       "33  1542326400           0.411261        True      52.65     1539977066   \n",
       "34  1542326400           0.408331        True      57.55     1539978976   \n",
       "35  1542326400           0.428717        True      59.70     1539973385   \n",
       "36  1542326400           0.424322        True      67.00     1539976612   \n",
       "37  1542326400           0.446173        True      47.00     1539803987   \n",
       "38  1542326400           0.448370        True      75.50     1539972442   \n",
       "39  1542326400           0.463384        True      68.16     1539964770   \n",
       "40  1542326400           0.471685        True      59.75     1539869953   \n",
       "41  1542326400           0.490484        True      68.90     1539871087   \n",
       "42  1542326400           0.515386        True      64.79     1539791280   \n",
       "43  1542326400           0.527348        True      83.00     1539956082   \n",
       "44  1542326400           0.563969        True      76.70     1539786192   \n",
       "45  1542326400           0.483892        True     122.10     1538068839   \n",
       "46  1542326400           0.599858        True      88.95     1539802114   \n",
       "47  1542326400           0.604252        True      88.75     1539785203   \n",
       "48  1542326400           0.634281        True     112.75     1539891328   \n",
       "49  1542326400           0.503911        True     100.01     1539786468   \n",
       "50  1542326400           0.646732        True      97.21     1539784431   \n",
       "51  1542326400           0.000010        True     132.20     1539264458   \n",
       "52  1542326400           0.000010        True     114.65     1532145396   \n",
       "53  1542326400           0.000010        True     121.65     1532145396   \n",
       "54  1542326400           0.739016        True     157.85     1539014239   \n",
       "55  1542326400           0.000010        True     142.95     1532145396   \n",
       "56  1542326400           0.000010        True     152.55     1532145396   \n",
       "57  1542326400           0.000010        True     157.40     1532145396   \n",
       "58  1542326400           0.000010        True     205.99     1539196817   \n",
       "59  1542326400           0.844728        True     168.95     1532145396   \n",
       "60  1542326400           0.000010        True     184.98     1537370855   \n",
       "\n",
       "    openInterest  percentChange  strike  volume  \n",
       "0            359      35.483868     220     292  \n",
       "1            433      42.857147     225     264  \n",
       "2            155      32.558136     230      46  \n",
       "3            177      32.000004     235      20  \n",
       "4            396      43.103450     240       9  \n",
       "5            433      35.714287     245      67  \n",
       "6           2336      45.569614     250     269  \n",
       "7            397      34.020607     255      37  \n",
       "8            397      36.036034     260      24  \n",
       "9            602      42.857140     265      48  \n",
       "10          1023      35.294117     270     398  \n",
       "11          1172      30.555552     275      90  \n",
       "12          1463      41.826930     280     154  \n",
       "13          1564      35.655730     285     257  \n",
       "14          1275      41.403520     290     374  \n",
       "15          1616      43.916916     295     266  \n",
       "16          3765      42.131977     300    1370  \n",
       "17          1153      42.094025     305     527  \n",
       "18          1717      43.807774     310    1016  \n",
       "19          6093      48.455284     315    3343  \n",
       "20          3873      41.999996     320    1383  \n",
       "21          2884      43.428574     325     892  \n",
       "22          3749      42.439030     330    1109  \n",
       "23          2363      39.583336     335     812  \n",
       "24          4503      37.755096     340    1156  \n",
       "25          2004      39.127730     345     884  \n",
       "26         13129      37.874650     350     515  \n",
       "27          1217      42.298283     355     685  \n",
       "28          4889      35.753246     360     309  \n",
       "29          1024      39.588980     365      51  \n",
       "..           ...            ...     ...     ...  \n",
       "31          1457      10.397546     375       7  \n",
       "32          1166      32.227750     380      26  \n",
       "33           362      30.289537     385      13  \n",
       "34           269      32.909930     390      48  \n",
       "35           231      51.908405     395       1  \n",
       "36           197      28.500193     400      26  \n",
       "37           198       0.000000     405      42  \n",
       "38           186      20.626297     410       9  \n",
       "39           132      21.389141     415       6  \n",
       "40           116       0.000000     420       4  \n",
       "41            82       0.000000     425       1  \n",
       "42            86       0.000000     430       7  \n",
       "43            30      15.598881     435       1  \n",
       "44            26       0.000000     440       2  \n",
       "45            39      45.045044     445       2  \n",
       "46            47       0.000000     450      22  \n",
       "47            22       0.000000     455       3  \n",
       "48            19       0.000000     460       1  \n",
       "49             6       0.000000     465      20  \n",
       "50            14       0.000000     470      10  \n",
       "51             1       0.000000     475       1  \n",
       "52             7       0.000000     485       7  \n",
       "53             2       0.000000     495       2  \n",
       "54             0      18.739310     500       1  \n",
       "55            26       0.000000     520      26  \n",
       "56             1       0.000000     530       1  \n",
       "57             3       0.000000     535       3  \n",
       "58             2      22.860338     540       2  \n",
       "59             1       0.000000     545       1  \n",
       "60             0       0.000000     550      23  \n",
       "\n",
       "[61 rows x 15 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(option_puts_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['options']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Pricing from Yahoo Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.yahoo.extract_df_from_redis import extract_pricing_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, pricing_df = extract_pricing_dataset(cache_dict)\n",
    "log.info('extracting - done - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>language</th>\n",
       "      <th>region</th>\n",
       "      <th>quoteType</th>\n",
       "      <th>quoteSourceName</th>\n",
       "      <th>currency</th>\n",
       "      <th>regularMarketPrice</th>\n",
       "      <th>regularMarketTime</th>\n",
       "      <th>regularMarketChange</th>\n",
       "      <th>regularMarketOpen</th>\n",
       "      <th>regularMarketDayHigh</th>\n",
       "      <th>...</th>\n",
       "      <th>market</th>\n",
       "      <th>symbol</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>date</th>\n",
       "      <th>market_time</th>\n",
       "      <th>post_market_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>en-US</td>\n",
       "      <td>US</td>\n",
       "      <td>EQUITY</td>\n",
       "      <td>Delayed Quote</td>\n",
       "      <td>USD</td>\n",
       "      <td>332.67</td>\n",
       "      <td>1539979202</td>\n",
       "      <td>-14.039978</td>\n",
       "      <td>351.0</td>\n",
       "      <td>355.8</td>\n",
       "      <td>...</td>\n",
       "      <td>us_market</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>355.8</td>\n",
       "      <td>332.2</td>\n",
       "      <td>351.0</td>\n",
       "      <td>346.71</td>\n",
       "      <td>16373692</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>2018-10-19 20:00:02</td>\n",
       "      <td>2018-10-19 23:59:31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  language region quoteType quoteSourceName currency  regularMarketPrice  \\\n",
       "0    en-US     US    EQUITY   Delayed Quote      USD              332.67   \n",
       "\n",
       "   regularMarketTime  regularMarketChange  regularMarketOpen  \\\n",
       "0         1539979202           -14.039978              351.0   \n",
       "\n",
       "   regularMarketDayHigh         ...              market  symbol   high    low  \\\n",
       "0                 355.8         ...           us_market    NFLX  355.8  332.2   \n",
       "\n",
       "    open   close    volume        date          market_time  \\\n",
       "0  351.0  346.71  16373692  2018-10-19  2018-10-19 20:00:02   \n",
       "\n",
       "      post_market_time  \n",
       "0  2018-10-19 23:59:31  \n",
       "\n",
       "[1 rows x 74 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(pricing_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['pricing']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting News from Yahoo Cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from analysis_engine.yahoo.extract_df_from_redis import extract_yahoo_news_dataset\n",
    "\n",
    "log.info('extracting - start - ticker={}'.format(ticker))\n",
    "extract_status, news_yahoo_df = extract_yahoo_news_dataset(cache_dict)\n",
    "log.info('extracting - end - ticker={}'.format(ticker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERROR - ticker=NFLX - did not extract a dataset from redis_key=NFLX_2018-10-19_news\n"
     ]
    }
   ],
   "source": [
    "if extract_status == SUCCESS:\n",
    "    display(news_yahoo_df)\n",
    "else:\n",
    "    log.error('ticker={} - did not extract a dataset from redis_key={}'.format(ticker, cache_dict['news']))"
   ]
  }
 ],
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