marketdata.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "import spgci as ci\n",
    "import pandas as pd\n",
    "from datetime import date\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "mdd = ci.MarketData()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>assessment_frequency</th>\n",
       "      <th>bate_code</th>\n",
       "      <th>benchmark</th>\n",
       "      <th>holiday_schedule</th>\n",
       "      <th>commodity</th>\n",
       "      <th>contract_type</th>\n",
       "      <th>currency</th>\n",
       "      <th>decimal_places</th>\n",
       "      <th>...</th>\n",
       "      <th>derivative_position</th>\n",
       "      <th>mdc</th>\n",
       "      <th>quotation_style</th>\n",
       "      <th>delivery_region</th>\n",
       "      <th>delivery_region_basis</th>\n",
       "      <th>settlement_type</th>\n",
       "      <th>active</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>uom</th>\n",
       "      <th>day_of_publication</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IGBBL21</td>\n",
       "      <td>Henry Hub FDt Com</td>\n",
       "      <td>Daily (7 day)</td>\n",
       "      <td>[h, l, u, w]</td>\n",
       "      <td>Benchmark</td>\n",
       "      <td>CALUS00</td>\n",
       "      <td>Natural gas</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>[AGP, GD]</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Physical</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>MMB</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BGBBL21</td>\n",
       "      <td>Henry Hub FDt DlCt</td>\n",
       "      <td>Daily (7 day)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Natural gas</td>\n",
       "      <td>Spot</td>\n",
       "      <td>UNS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>[GD]</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Physical</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>CON</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IGBBL20</td>\n",
       "      <td>Henry Hub TDt Abs</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[h, l]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CALUS00</td>\n",
       "      <td>Natural gas</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>[GD]</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Physical</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>MMB</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BGBBL00</td>\n",
       "      <td>Henry Hub TDt DlCt</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CALUS00</td>\n",
       "      <td>Natural gas</td>\n",
       "      <td>Spot</td>\n",
       "      <td>UNS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>[AGP, GD]</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Physical</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>CON</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IGBBL00</td>\n",
       "      <td>Henry Hub TDt Com</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[h, l, u, w]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CALUS00</td>\n",
       "      <td>Natural gas</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>[AGP, GD]</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Henry Hub</td>\n",
       "      <td>Physical</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>MMB</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    symbol         description assessment_frequency     bate_code  benchmark  \\\n",
       "0  IGBBL21   Henry Hub FDt Com        Daily (7 day)  [h, l, u, w]  Benchmark   \n",
       "1  BGBBL21  Henry Hub FDt DlCt        Daily (7 day)           [u]        NaN   \n",
       "2  IGBBL20   Henry Hub TDt Abs      Daily (weekday)        [h, l]        NaN   \n",
       "3  BGBBL00  Henry Hub TDt DlCt      Daily (weekday)           [u]        NaN   \n",
       "4  IGBBL00   Henry Hub TDt Com      Daily (weekday)  [h, l, u, w]        NaN   \n",
       "\n",
       "  holiday_schedule    commodity contract_type currency  decimal_places  ...  \\\n",
       "0          CALUS00  Natural gas          Spot      USD             3.0  ...   \n",
       "1              NaN  Natural gas          Spot      UNS             NaN  ...   \n",
       "2          CALUS00  Natural gas          Spot      USD             3.0  ...   \n",
       "3          CALUS00  Natural gas          Spot      UNS             NaN  ...   \n",
       "4          CALUS00  Natural gas          Spot      USD             3.0  ...   \n",
       "\n",
       "  derivative_position        mdc quotation_style delivery_region  \\\n",
       "0                   1  [AGP, GD]            Flat       Henry Hub   \n",
       "1                   1       [GD]            Flat       Henry Hub   \n",
       "2                   1       [GD]            Flat       Henry Hub   \n",
       "3                   1  [AGP, GD]            Flat       Henry Hub   \n",
       "4                   1  [AGP, GD]            Flat       Henry Hub   \n",
       "\n",
       "  delivery_region_basis settlement_type           active         timestamp  \\\n",
       "0             Henry Hub        Physical  Active - Public  14:30 US Eastern   \n",
       "1             Henry Hub        Physical  Active - Public  14:30 US Eastern   \n",
       "2             Henry Hub        Physical  Active - Public  14:30 US Eastern   \n",
       "3             Henry Hub        Physical  Active - Public  14:30 US Eastern   \n",
       "4             Henry Hub        Physical  Active - Public  14:30 US Eastern   \n",
       "\n",
       "   uom day_of_publication  \n",
       "0  MMB                NaN  \n",
       "1  CON                NaN  \n",
       "2  MMB                NaN  \n",
       "3  CON   Daily (weekdays)  \n",
       "4  MMB   Daily (weekdays)  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hh = mdd.get_symbols(q=\"Henry Hub\", mdc='GD')\n",
    "hh.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bate</th>\n",
       "      <th>value</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>u</td>\n",
       "      <td>74.0</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-01-03 00:23:01</td>\n",
       "      <td>BGBBL00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>u</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-01-03 23:54:42</td>\n",
       "      <td>BGBBL00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>u</td>\n",
       "      <td>58.0</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-01-05 02:01:32</td>\n",
       "      <td>BGBBL00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>u</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-01-05 23:14:43</td>\n",
       "      <td>BGBBL00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>u</td>\n",
       "      <td>36.0</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-01-09 00:05:15</td>\n",
       "      <td>BGBBL00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  bate  value assessDate isCorrected             modDate   symbol\n",
       "0    u   74.0 2018-01-02           N 2018-01-03 00:23:01  BGBBL00\n",
       "1    u   54.0 2018-01-03           N 2018-01-03 23:54:42  BGBBL00\n",
       "2    u   58.0 2018-01-04           N 2018-01-05 02:01:32  BGBBL00\n",
       "3    u   40.0 2018-01-05           N 2018-01-05 23:14:43  BGBBL00\n",
       "4    u   36.0 2018-01-08           N 2018-01-09 00:05:15  BGBBL00"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = mdd.get_assessments_by_symbol_historical(symbol=hh.iloc[2:4]['symbol'], bate=['h', 'u'], assess_date_gte=date(2018, 1, 1), paginate=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2582 entries, 0 to 2581\n",
      "Data columns (total 6 columns):\n",
      " #   Column       Non-Null Count  Dtype         \n",
      "---  ------       --------------  -----         \n",
      " 0   bate         2582 non-null   object        \n",
      " 1   value        2582 non-null   float64       \n",
      " 2   assessDate   2582 non-null   datetime64[ns]\n",
      " 3   isCorrected  2582 non-null   object        \n",
      " 4   modDate      2582 non-null   datetime64[ns]\n",
      " 5   symbol       2582 non-null   object        \n",
      "dtypes: datetime64[ns](2), float64(1), object(3)\n",
      "memory usage: 121.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>symbol</th>\n",
       "      <th>BGBBL00</th>\n",
       "      <th>IGBBL20</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>assessDate</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>74.0</td>\n",
       "      <td>7.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>54.0</td>\n",
       "      <td>7.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>58.0</td>\n",
       "      <td>5.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>40.0</td>\n",
       "      <td>2.950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>36.0</td>\n",
       "      <td>2.925</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "symbol      BGBBL00  IGBBL20\n",
       "assessDate                  \n",
       "2018-01-02     74.0    7.500\n",
       "2018-01-03     54.0    7.700\n",
       "2018-01-04     58.0    5.000\n",
       "2018-01-05     40.0    2.950\n",
       "2018-01-08     36.0    2.925"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt = df.pivot_table(index='assessDate', columns='symbol', values='value')\n",
    "pt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pt.columns = ['Deal Count', 'Price ($/MMBtu)']\n",
    "pt.plot(subplots=True, sharex=True)\n",
    "plt.subplots_adjust(wspace=0, hspace=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>mdc</th>\n",
       "      <th>description</th>\n",
       "      <th>isSubscribed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1A</td>\n",
       "      <td>EWindow: Physical Crudes Asia</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1B</td>\n",
       "      <td>EWindow: Physical Products Asia</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1C</td>\n",
       "      <td>EWindow: Financial Asia</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2A</td>\n",
       "      <td>EWindow: Physical Crudes EMEA</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2B</td>\n",
       "      <td>EWindow: Physical Products EMEA</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  mdc                      description  isSubscribed\n",
       "0  1A    EWindow: Physical Crudes Asia          True\n",
       "1  1B  EWindow: Physical Products Asia          True\n",
       "2  1C          EWindow: Financial Asia          True\n",
       "3  2A    EWindow: Physical Crudes EMEA          True\n",
       "4  2B  EWindow: Physical Products EMEA          True"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdc = mdd.get_mdcs()\n",
    "mdc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>mdc</th>\n",
       "      <th>description</th>\n",
       "      <th>isSubscribed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AGP</td>\n",
       "      <td>MI Americas Gas &amp; Power</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>AN</td>\n",
       "      <td>Natural Gas: Americas Non-Platts data</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>CAG</td>\n",
       "      <td>MI Canadian Gas</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>CU</td>\n",
       "      <td>Futures/Nearbys: NYMEX CME RBOB Gasoline</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>EBM</td>\n",
       "      <td>Natural Gas: European Biomethane</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>EDC</td>\n",
       "      <td>M2MS: 120-month Gas forward curves North East</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>EG</td>\n",
       "      <td>Natural Gas: European Assessments</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>EGI</td>\n",
       "      <td>In-house: Natural Gas Euro Assmts Inact</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>EGP</td>\n",
       "      <td>MI EU Gas &amp; Power</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>EH</td>\n",
       "      <td>Natural Gas: European Exch/Other</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>EHI</td>\n",
       "      <td>In-house: Natural Gas Euro Exch Inact</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>EMC</td>\n",
       "      <td>M2MS: 240-month Gas forward curves North East</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>GD</td>\n",
       "      <td>Natural Gas: N American Daily Assmts</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>GDC</td>\n",
       "      <td>M2MS: 120-month Gas forward curves US Gulf Coast</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>GDI</td>\n",
       "      <td>Natgas Poss GD Additions</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>GE</td>\n",
       "      <td>Natural Gas: Enerdata North America Daily Prices</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>GF</td>\n",
       "      <td>Natural Gas: European Fwd Assessments</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>GH</td>\n",
       "      <td>Natural Gas: Platts ICE Gas Indices Americas (...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>GI</td>\n",
       "      <td>Natural Gas: North American Preliminary Daily ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>GJ</td>\n",
       "      <td>Natural Gas: North American Preliminary Monthl...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>GL</td>\n",
       "      <td>Natural Gas: Enerdata North America Monthly Pr...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>GM</td>\n",
       "      <td>Natural Gas: US Monthly Assessments</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>GMC</td>\n",
       "      <td>M2MS: 240-month Gas forward curves US Gulf Coast</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>GMI</td>\n",
       "      <td>In-house: Natgas Poss GM Additions</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>GNI</td>\n",
       "      <td>In-house: Natural Gas NAmer Fwds(unused)</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>GS</td>\n",
       "      <td>Statistics: N Amer Natgas Storage</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>GX</td>\n",
       "      <td>Natural Gas: Gas Daily Mexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>MDC</td>\n",
       "      <td>M2MS: 120-month Gas forward curves MidContinent</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>MMC</td>\n",
       "      <td>M2MS: 240-month Gas forward curves Mid Continent</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334</th>\n",
       "      <td>MQN</td>\n",
       "      <td>M2M: North America Natural Gas Liquid Forward ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>PDC</td>\n",
       "      <td>M2MS: 120-month Gas forward curves PFC Hubs Only</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387</th>\n",
       "      <td>PMC</td>\n",
       "      <td>M2MS: 240-month Gas forward curves PFC Hubs Only</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>QDX</td>\n",
       "      <td>M2MS: 120-Month Gas forward curves Mexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>QGF</td>\n",
       "      <td>M2M: Natural Gas EMEA</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>QMX</td>\n",
       "      <td>M2MS: 240-Month Gas forward curves Mexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>RDC</td>\n",
       "      <td>M2MS: 120-month Gas forward curves Rockies and...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>RDGS</td>\n",
       "      <td>PRS Gas Group</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>RMC</td>\n",
       "      <td>M2MS: 240-month Gas forward curves Rockies and...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>TG</td>\n",
       "      <td>Futures/Nearbys: NYMEX RBOB Gasoline</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>TH</td>\n",
       "      <td>Futures/Nearbys: NYMEX Natural Gas</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>TK</td>\n",
       "      <td>Futures/Nearbys: ICE Gas Oil</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>TP</td>\n",
       "      <td>In-house: Futures ICE Natgas (future)</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>TQ</td>\n",
       "      <td>Futures/Nearbys: ICE Natural Gas</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>UDC</td>\n",
       "      <td>M2MS: 120-month Gas forward curves Upper Midwest</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>UMC</td>\n",
       "      <td>M2MS: 240-month Gas forward curves Upper Midwest</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      mdc                                        description  isSubscribed\n",
       "22    AGP                            MI Americas Gas & Power          True\n",
       "45     AN              Natural Gas: Americas Non-Platts data          True\n",
       "63    CAG                                    MI Canadian Gas          True\n",
       "88     CU           Futures/Nearbys: NYMEX CME RBOB Gasoline          True\n",
       "105   EBM                   Natural Gas: European Biomethane          True\n",
       "107   EDC      M2MS: 120-month Gas forward curves North East          True\n",
       "114    EG                  Natural Gas: European Assessments          True\n",
       "115   EGI            In-house: Natural Gas Euro Assmts Inact          True\n",
       "116   EGP                                  MI EU Gas & Power          True\n",
       "118    EH                   Natural Gas: European Exch/Other          True\n",
       "119   EHI              In-house: Natural Gas Euro Exch Inact          True\n",
       "123   EMC      M2MS: 240-month Gas forward curves North East          True\n",
       "150    GD               Natural Gas: N American Daily Assmts          True\n",
       "151   GDC   M2MS: 120-month Gas forward curves US Gulf Coast          True\n",
       "152   GDI                           Natgas Poss GD Additions          True\n",
       "153    GE   Natural Gas: Enerdata North America Daily Prices          True\n",
       "154    GF              Natural Gas: European Fwd Assessments          True\n",
       "155    GH  Natural Gas: Platts ICE Gas Indices Americas (...          True\n",
       "156    GI  Natural Gas: North American Preliminary Daily ...          True\n",
       "157    GJ  Natural Gas: North American Preliminary Monthl...          True\n",
       "158    GL  Natural Gas: Enerdata North America Monthly Pr...          True\n",
       "159    GM                Natural Gas: US Monthly Assessments          True\n",
       "160   GMC   M2MS: 240-month Gas forward curves US Gulf Coast          True\n",
       "161   GMI                 In-house: Natgas Poss GM Additions          True\n",
       "162   GNI           In-house: Natural Gas NAmer Fwds(unused)          True\n",
       "168    GS                  Statistics: N Amer Natgas Storage          True\n",
       "169    GX                      Natural Gas: Gas Daily Mexico          True\n",
       "314   MDC    M2MS: 120-month Gas forward curves MidContinent          True\n",
       "325   MMC   M2MS: 240-month Gas forward curves Mid Continent          True\n",
       "334   MQN  M2M: North America Natural Gas Liquid Forward ...          True\n",
       "374   PDC   M2MS: 120-month Gas forward curves PFC Hubs Only          True\n",
       "387   PMC   M2MS: 240-month Gas forward curves PFC Hubs Only          True\n",
       "400   QDX          M2MS: 120-Month Gas forward curves Mexico          True\n",
       "404   QGF                              M2M: Natural Gas EMEA          True\n",
       "422   QMX          M2MS: 240-Month Gas forward curves Mexico          True\n",
       "435   RDC  M2MS: 120-month Gas forward curves Rockies and...          True\n",
       "437  RDGS                                      PRS Gas Group          True\n",
       "456   RMC  M2MS: 240-month Gas forward curves Rockies and...          True\n",
       "526    TG               Futures/Nearbys: NYMEX RBOB Gasoline          True\n",
       "528    TH                 Futures/Nearbys: NYMEX Natural Gas          True\n",
       "530    TK                       Futures/Nearbys: ICE Gas Oil          True\n",
       "532    TP              In-house: Futures ICE Natgas (future)          True\n",
       "533    TQ                   Futures/Nearbys: ICE Natural Gas          True\n",
       "536   UDC   M2MS: 120-month Gas forward curves Upper Midwest          True\n",
       "544   UMC   M2MS: 240-month Gas forward curves Upper Midwest          True"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filt =  mdc['description'].str.contains(\"gas\",case=False)\n",
    "mdc[filt]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>bate</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>value</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>h</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>118.10</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 17:28:23</td>\n",
       "      <td>AAAXS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>h</td>\n",
       "      <td>2023-02-01</td>\n",
       "      <td>132.19</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-01 10:50:04</td>\n",
       "      <td>AAAXT00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>h</td>\n",
       "      <td>2023-03-04</td>\n",
       "      <td>677.90</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 15:03:54</td>\n",
       "      <td>AACMD00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>h</td>\n",
       "      <td>2018-05-29</td>\n",
       "      <td>44.85</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-05-25 17:23:41</td>\n",
       "      <td>AACTG21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>h</td>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>37.44</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-06-01 09:50:04</td>\n",
       "      <td>AACTH00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  bate assessDate   value isCorrected             modDate   symbol\n",
       "0    h 2023-03-03  118.10           N 2023-03-03 17:28:23  AAAXS00\n",
       "1    h 2023-02-01  132.19           N 2023-03-01 10:50:04  AAAXT00\n",
       "2    h 2023-03-04  677.90           N 2023-03-03 15:03:54  AACMD00\n",
       "3    h 2018-05-29   44.85           N 2018-05-25 17:23:41  AACTG21\n",
       "4    h 2018-05-01   37.44           N 2018-06-01 09:50:04  AACTH00"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "egp = mdd.get_assessments_by_mdc_current(mdc=\"EGP\", paginate=False, bate='h')\n",
    "egp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fetching...: 100%|██████████| 2/2 [00:00<00:00,  4.33it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>assessment_frequency</th>\n",
       "      <th>bate_code</th>\n",
       "      <th>holiday_schedule</th>\n",
       "      <th>commodity</th>\n",
       "      <th>contract_type</th>\n",
       "      <th>currency</th>\n",
       "      <th>curve_code</th>\n",
       "      <th>curve_name</th>\n",
       "      <th>...</th>\n",
       "      <th>active</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>uom</th>\n",
       "      <th>day_of_publication</th>\n",
       "      <th>delivery_region</th>\n",
       "      <th>fuel_efficiency</th>\n",
       "      <th>delivery_region_port_id</th>\n",
       "      <th>commodity_grade</th>\n",
       "      <th>delivery_region_basis_port_id</th>\n",
       "      <th>shipping_terms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EEXIC01</td>\n",
       "      <td>EEX Italy Base Vol MWh Mo03</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Electricity</td>\n",
       "      <td>Prompt</td>\n",
       "      <td>N/A</td>\n",
       "      <td>CN2PL</td>\n",
       "      <td>EEX Italy Base Future Volume</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EEXIC00</td>\n",
       "      <td>EEX Italy Base Eur/MWh Mo03</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Electricity</td>\n",
       "      <td>Prompt</td>\n",
       "      <td>EUR</td>\n",
       "      <td>CN2IB</td>\n",
       "      <td>EEX Italy Base Future</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EEXIG01</td>\n",
       "      <td>EEX Italy Base Vol MWh Yr02</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Electricity</td>\n",
       "      <td>Prompt</td>\n",
       "      <td>N/A</td>\n",
       "      <td>CN2PL</td>\n",
       "      <td>EEX Italy Base Future Volume</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GPGTD00</td>\n",
       "      <td>France PEG DA Eur/Mwh</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Natural gas</td>\n",
       "      <td>Spot</td>\n",
       "      <td>EUR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Central Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CKFQ100</td>\n",
       "      <td>Cln UK 1 QA Spk Sprd 50%</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Spark spread</td>\n",
       "      <td>Forward</td>\n",
       "      <td>GBP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>IntercontinentalExchange</td>\n",
       "      <td>50%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    symbol                  description assessment_frequency  bate_code  \\\n",
       "0  EEXIC01  EEX Italy Base Vol MWh Mo03      Daily (weekday)        [u]   \n",
       "1  EEXIC00  EEX Italy Base Eur/MWh Mo03      Daily (weekday)        [c]   \n",
       "2  EEXIG01  EEX Italy Base Vol MWh Yr02      Daily (weekday)        [u]   \n",
       "3  GPGTD00        France PEG DA Eur/Mwh      Daily (weekday)  [c, h, l]   \n",
       "4  CKFQ100     Cln UK 1 QA Spk Sprd 50%      Daily (weekday)        [u]   \n",
       "\n",
       "  holiday_schedule     commodity contract_type currency curve_code  \\\n",
       "0          CALLN00   Electricity        Prompt      N/A      CN2PL   \n",
       "1          CALLN00   Electricity        Prompt      EUR      CN2IB   \n",
       "2          CALLN00   Electricity        Prompt      N/A      CN2PL   \n",
       "3          CALLN00   Natural gas          Spot      EUR        NaN   \n",
       "4          CALLN00  Spark spread       Forward      GBP        NaN   \n",
       "\n",
       "                     curve_name  ...           active timestamp  uom  \\\n",
       "0  EEX Italy Base Future Volume  ...  Active - Public  16:30 UK  MGW   \n",
       "1         EEX Italy Base Future  ...  Active - Public  16:30 UK  MGW   \n",
       "2  EEX Italy Base Future Volume  ...  Active - Public  16:30 UK  MGW   \n",
       "3                           NaN  ...  Active - Public  16:30 UK  MGW   \n",
       "4                           NaN  ...  Active - Public  16:30 UK  MGW   \n",
       "\n",
       "  day_of_publication           delivery_region fuel_efficiency  \\\n",
       "0                NaN                       NaN             NaN   \n",
       "1                NaN                       NaN             NaN   \n",
       "2                NaN                       NaN             NaN   \n",
       "3   Daily (weekdays)            Central Europe             NaN   \n",
       "4   Daily (weekdays)  IntercontinentalExchange             50%   \n",
       "\n",
       "  delivery_region_port_id commodity_grade delivery_region_basis_port_id  \\\n",
       "0                     NaN             NaN                           NaN   \n",
       "1                     NaN             NaN                           NaN   \n",
       "2                     NaN             NaN                           NaN   \n",
       "3                     NaN             NaN                           NaN   \n",
       "4                     NaN             NaN                           NaN   \n",
       "\n",
       "  shipping_terms  \n",
       "0            NaN  \n",
       "1            NaN  \n",
       "2            NaN  \n",
       "3            NaN  \n",
       "4            NaN  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "egp_sym = mdd.get_symbols(mdc=\"EGP\", assessment_frequency=[mdd.AssessmentFrequency.Daily, mdd.AssessmentFrequency.DailyWeekday], paginate=True, uom='M')\n",
    "egp_sym.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bate</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>value</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>assessment_frequency</th>\n",
       "      <th>bate_code</th>\n",
       "      <th>holiday_schedule</th>\n",
       "      <th>...</th>\n",
       "      <th>active</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>uom</th>\n",
       "      <th>day_of_publication</th>\n",
       "      <th>delivery_region</th>\n",
       "      <th>fuel_efficiency</th>\n",
       "      <th>delivery_region_port_id</th>\n",
       "      <th>commodity_grade</th>\n",
       "      <th>delivery_region_basis_port_id</th>\n",
       "      <th>shipping_terms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>h</td>\n",
       "      <td>2018-05-29</td>\n",
       "      <td>48.75</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-05-25 17:23:41</td>\n",
       "      <td>AACTK21</td>\n",
       "      <td>Germany DA Pk FDt Euro</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>#Not Applicable</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>12:00 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Transnet, TenneT Amprion, 50Hertz Trans</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>h</td>\n",
       "      <td>2018-05-29</td>\n",
       "      <td>54.25</td>\n",
       "      <td>N</td>\n",
       "      <td>2018-05-25 17:34:33</td>\n",
       "      <td>AACXG21</td>\n",
       "      <td>France DA Peak FDt Euro</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>#Not Applicable</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>12:00 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reseau de Transport d'Electricite (RTE)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>h</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>134.65</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 10:44:45</td>\n",
       "      <td>AADET00</td>\n",
       "      <td>UK GTMA DA Base TDt</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>National Grid PLC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>h</td>\n",
       "      <td>2022-12-30</td>\n",
       "      <td>147.80</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-12-30 12:07:32</td>\n",
       "      <td>AADET27</td>\n",
       "      <td>UK GTMA DA+1 Base TDt</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>National Grid PLC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>h</td>\n",
       "      <td>2022-12-23</td>\n",
       "      <td>150.15</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-12-23 12:02:18</td>\n",
       "      <td>AADET28</td>\n",
       "      <td>UK GTMA DA+2 Base TDt</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>MGW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>National Grid PLC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  bate assessDate   value isCorrected             modDate   symbol  \\\n",
       "0    h 2018-05-29   48.75           N 2018-05-25 17:23:41  AACTK21   \n",
       "1    h 2018-05-29   54.25           N 2018-05-25 17:34:33  AACXG21   \n",
       "2    h 2023-03-03  134.65           N 2023-03-03 10:44:45  AADET00   \n",
       "3    h 2022-12-30  147.80           N 2022-12-30 12:07:32  AADET27   \n",
       "4    h 2022-12-23  150.15           N 2022-12-23 12:02:18  AADET28   \n",
       "\n",
       "               description assessment_frequency  bate_code holiday_schedule  \\\n",
       "0   Germany DA Pk FDt Euro      Daily (weekday)  [c, h, l]  #Not Applicable   \n",
       "1  France DA Peak FDt Euro      Daily (weekday)  [c, h, l]  #Not Applicable   \n",
       "2      UK GTMA DA Base TDt      Daily (weekday)  [c, h, l]          CALLN00   \n",
       "3    UK GTMA DA+1 Base TDt      Daily (weekday)  [c, h, l]          CALLN00   \n",
       "4    UK GTMA DA+2 Base TDt      Daily (weekday)  [c, h, l]          CALLN00   \n",
       "\n",
       "   ...           active timestamp  uom day_of_publication  \\\n",
       "0  ...  Active - Public  12:00 UK  MGW                NaN   \n",
       "1  ...  Active - Public  12:00 UK  MGW                NaN   \n",
       "2  ...  Active - Public  16:30 UK  MGW   Daily (weekdays)   \n",
       "3  ...  Active - Public  16:30 UK  MGW                NaN   \n",
       "4  ...  Active - Public  16:30 UK  MGW                NaN   \n",
       "\n",
       "                           delivery_region  fuel_efficiency  \\\n",
       "0  Transnet, TenneT Amprion, 50Hertz Trans              NaN   \n",
       "1  Reseau de Transport d'Electricite (RTE)              NaN   \n",
       "2                        National Grid PLC              NaN   \n",
       "3                        National Grid PLC              NaN   \n",
       "4                        National Grid PLC              NaN   \n",
       "\n",
       "  delivery_region_port_id commodity_grade delivery_region_basis_port_id  \\\n",
       "0                     NaN             NaN                           NaN   \n",
       "1                     NaN             NaN                           NaN   \n",
       "2                     NaN             NaN                           NaN   \n",
       "3                     NaN             NaN                           NaN   \n",
       "4                     NaN             NaN                           NaN   \n",
       "\n",
       "  shipping_terms  \n",
       "0            NaN  \n",
       "1            NaN  \n",
       "2            NaN  \n",
       "3            NaN  \n",
       "4            NaN  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined = egp.merge(egp_sym, on='symbol')\n",
    "joined.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>value</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>modDate</th>\n",
       "      <th>currency</th>\n",
       "      <th>uom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>142.65</td>\n",
       "      <td>2023-03-06</td>\n",
       "      <td>2023-03-03 17:34:52</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>49</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>137.77</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>2023-03-03 17:35:09</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17</td>\n",
       "      <td>AADGV00</td>\n",
       "      <td>UK GTMA 1-Mo Pk</td>\n",
       "      <td>130.35</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>2023-03-03 17:34:47</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18</td>\n",
       "      <td>AADIJ00</td>\n",
       "      <td>UK GTMA 1-Mo Pk Euro</td>\n",
       "      <td>147.25</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>2023-03-03 17:35:09</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19</td>\n",
       "      <td>AADNN00</td>\n",
       "      <td>UK Base Weekend</td>\n",
       "      <td>118.90</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>2023-03-03 17:34:47</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>12</td>\n",
       "      <td>AADFC29</td>\n",
       "      <td>UK GTMA DA+3 Pk TDt</td>\n",
       "      <td>71.15</td>\n",
       "      <td>2018-12-21</td>\n",
       "      <td>2018-12-21 13:24:28</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>1</td>\n",
       "      <td>AACXG21</td>\n",
       "      <td>France DA Peak FDt Euro</td>\n",
       "      <td>54.25</td>\n",
       "      <td>2018-05-29</td>\n",
       "      <td>2018-05-25 17:34:33</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>0</td>\n",
       "      <td>AACTK21</td>\n",
       "      <td>Germany DA Pk FDt Euro</td>\n",
       "      <td>48.75</td>\n",
       "      <td>2018-05-29</td>\n",
       "      <td>2018-05-25 17:23:41</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>13</td>\n",
       "      <td>AADFC30</td>\n",
       "      <td>UK GTMA DA+4 Pk TDt</td>\n",
       "      <td>28.75</td>\n",
       "      <td>2010-08-12</td>\n",
       "      <td>2010-08-12 16:13:13</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>6</td>\n",
       "      <td>AADET30</td>\n",
       "      <td>UK GTMA DA+4 Base TDt</td>\n",
       "      <td>29.80</td>\n",
       "      <td>2010-08-12</td>\n",
       "      <td>2010-08-12 16:13:13</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index   symbol                     description   value assessDate  \\\n",
       "0        9  AADFC21               UK GTMA DA Pk FDt  142.65 2023-03-06   \n",
       "1       49  AAIKB00  UK/GTMA Baseload Season 3 Euro  137.77 2023-03-03   \n",
       "2       17  AADGV00                 UK GTMA 1-Mo Pk  130.35 2023-03-03   \n",
       "3       18  AADIJ00            UK GTMA 1-Mo Pk Euro  147.25 2023-03-03   \n",
       "4       19  AADNN00                 UK Base Weekend  118.90 2023-03-03   \n",
       "..     ...      ...                             ...     ...        ...   \n",
       "114     12  AADFC29             UK GTMA DA+3 Pk TDt   71.15 2018-12-21   \n",
       "115      1  AACXG21         France DA Peak FDt Euro   54.25 2018-05-29   \n",
       "116      0  AACTK21          Germany DA Pk FDt Euro   48.75 2018-05-29   \n",
       "117     13  AADFC30             UK GTMA DA+4 Pk TDt   28.75 2010-08-12   \n",
       "118      6  AADET30           UK GTMA DA+4 Base TDt   29.80 2010-08-12   \n",
       "\n",
       "                modDate currency  uom  \n",
       "0   2023-03-03 17:34:52      GBP  MGW  \n",
       "1   2023-03-03 17:35:09      EUR  MGW  \n",
       "2   2023-03-03 17:34:47      GBP  MGW  \n",
       "3   2023-03-03 17:35:09      EUR  MGW  \n",
       "4   2023-03-03 17:34:47      GBP  MGW  \n",
       "..                  ...      ...  ...  \n",
       "114 2018-12-21 13:24:28      GBP  MGW  \n",
       "115 2018-05-25 17:34:33      EUR  MGW  \n",
       "116 2018-05-25 17:23:41      EUR  MGW  \n",
       "117 2010-08-12 16:13:13      GBP  MGW  \n",
       "118 2010-08-12 16:13:13      GBP  MGW  \n",
       "\n",
       "[119 rows x 8 columns]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filt = joined['derivative_maturity_frequency'].isna()\n",
    "# joined = joined[filt]\n",
    "joined = joined[['symbol', 'description', 'value', 'assessDate', 'modDate', 'currency', 'uom']].sort_values(\"assessDate\", ascending=False).reset_index()\n",
    "joined\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bate</th>\n",
       "      <th>value</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>h</td>\n",
       "      <td>155.15</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>N</td>\n",
       "      <td>2021-12-31 13:57:32</td>\n",
       "      <td>AADFC21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>h</td>\n",
       "      <td>190.15</td>\n",
       "      <td>2022-01-04</td>\n",
       "      <td>N</td>\n",
       "      <td>2021-12-31 13:57:32</td>\n",
       "      <td>AADFC21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>h</td>\n",
       "      <td>198.15</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-04 18:17:39</td>\n",
       "      <td>AADFC21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>h</td>\n",
       "      <td>212.15</td>\n",
       "      <td>2022-01-06</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-05 17:20:04</td>\n",
       "      <td>AADFC21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>h</td>\n",
       "      <td>215.15</td>\n",
       "      <td>2022-01-07</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-06 17:32:21</td>\n",
       "      <td>AADFC21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  bate   value assessDate isCorrected             modDate   symbol\n",
       "0    h  155.15 2022-01-03           N 2021-12-31 13:57:32  AADFC21\n",
       "1    h  190.15 2022-01-04           N 2021-12-31 13:57:32  AADFC21\n",
       "2    h  198.15 2022-01-05           N 2022-01-04 18:17:39  AADFC21\n",
       "3    h  212.15 2022-01-06           N 2022-01-05 17:20:04  AADFC21\n",
       "4    h  215.15 2022-01-07           N 2022-01-06 17:32:21  AADFC21"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym_history = mdd.get_assessments_by_symbol_historical(symbol=joined.iloc[:10]['symbol'], assess_date_gte=date(2022, 1, 1), bate='h')\n",
    "sym_history.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bate</th>\n",
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       "      <th>assessDate</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
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       "      <th>description</th>\n",
       "      <th>assessment_frequency</th>\n",
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       "      <th>holiday_schedule</th>\n",
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       "      <th>fuel_efficiency</th>\n",
       "      <th>delivery_region_port_id</th>\n",
       "      <th>commodity_grade</th>\n",
       "      <th>delivery_region_basis_port_id</th>\n",
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       "      <td>National Grid PLC</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2022-01-05</td>\n",
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       "      <td>2022-01-04 18:17:39</td>\n",
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       "      <td>#Not Applicable</td>\n",
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       "      <td>Active - Public</td>\n",
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       "      <td>MGW</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>National Grid PLC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>h</td>\n",
       "      <td>212.15</td>\n",
       "      <td>2022-01-06</td>\n",
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       "      <td>[c, h, l]</td>\n",
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       "      <td>MGW</td>\n",
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       "      <td>National Grid PLC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>h</td>\n",
       "      <td>215.15</td>\n",
       "      <td>2022-01-07</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-06 17:32:21</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c, h, l]</td>\n",
       "      <td>#Not Applicable</td>\n",
       "      <td>...</td>\n",
       "      <td>Active - Public</td>\n",
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       "      <td>MGW</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>National Grid PLC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  bate   value assessDate isCorrected             modDate   symbol  \\\n",
       "0    h  155.15 2022-01-03           N 2021-12-31 13:57:32  AADFC21   \n",
       "1    h  190.15 2022-01-04           N 2021-12-31 13:57:32  AADFC21   \n",
       "2    h  198.15 2022-01-05           N 2022-01-04 18:17:39  AADFC21   \n",
       "3    h  212.15 2022-01-06           N 2022-01-05 17:20:04  AADFC21   \n",
       "4    h  215.15 2022-01-07           N 2022-01-06 17:32:21  AADFC21   \n",
       "\n",
       "         description assessment_frequency  bate_code holiday_schedule  ...  \\\n",
       "0  UK GTMA DA Pk FDt      Daily (weekday)  [c, h, l]  #Not Applicable  ...   \n",
       "1  UK GTMA DA Pk FDt      Daily (weekday)  [c, h, l]  #Not Applicable  ...   \n",
       "2  UK GTMA DA Pk FDt      Daily (weekday)  [c, h, l]  #Not Applicable  ...   \n",
       "3  UK GTMA DA Pk FDt      Daily (weekday)  [c, h, l]  #Not Applicable  ...   \n",
       "4  UK GTMA DA Pk FDt      Daily (weekday)  [c, h, l]  #Not Applicable  ...   \n",
       "\n",
       "            active timestamp  uom day_of_publication    delivery_region  \\\n",
       "0  Active - Public  12:00 UK  MGW   Daily (weekdays)  National Grid PLC   \n",
       "1  Active - Public  12:00 UK  MGW   Daily (weekdays)  National Grid PLC   \n",
       "2  Active - Public  12:00 UK  MGW   Daily (weekdays)  National Grid PLC   \n",
       "3  Active - Public  12:00 UK  MGW   Daily (weekdays)  National Grid PLC   \n",
       "4  Active - Public  12:00 UK  MGW   Daily (weekdays)  National Grid PLC   \n",
       "\n",
       "   fuel_efficiency delivery_region_port_id commodity_grade  \\\n",
       "0              NaN                     NaN             NaN   \n",
       "1              NaN                     NaN             NaN   \n",
       "2              NaN                     NaN             NaN   \n",
       "3              NaN                     NaN             NaN   \n",
       "4              NaN                     NaN             NaN   \n",
       "\n",
       "  delivery_region_basis_port_id shipping_terms  \n",
       "0                           NaN            NaN  \n",
       "1                           NaN            NaN  \n",
       "2                           NaN            NaN  \n",
       "3                           NaN            NaN  \n",
       "4                           NaN            NaN  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym_history = sym_history.merge(egp_sym, on='symbol')\n",
    "sym_history.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>description</th>\n",
       "      <th>UK Base Weekend</th>\n",
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       "    <tr>\n",
       "      <th>symbol</th>\n",
       "      <th>AADNN00</th>\n",
       "      <th>AADNP00</th>\n",
       "      <th>AADGV00</th>\n",
       "      <th>AADIJ00</th>\n",
       "      <th>AADNS00</th>\n",
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       "      <th>currency</th>\n",
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       "      <th>EUR</th>\n",
       "      <th>GBP</th>\n",
       "      <th>EUR</th>\n",
       "      <th>GBP</th>\n",
       "      <th>EUR</th>\n",
       "      <th>GBP</th>\n",
       "      <th>EUR</th>\n",
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       "    <tr>\n",
       "      <th>uom</th>\n",
       "      <th>MGW</th>\n",
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       "      <th>MGW</th>\n",
       "      <th>MGW</th>\n",
       "      <th>MGW</th>\n",
       "      <th>MGW</th>\n",
       "      <th>MGW</th>\n",
       "      <th>MGW</th>\n",
       "      <th>MGW</th>\n",
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       "    <tr>\n",
       "      <th>assessDate</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>2022-01-03</th>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>112.65</td>\n",
       "      <td>135.01</td>\n",
       "      <td>427.55</td>\n",
       "      <td>512.40</td>\n",
       "      <td>202.70</td>\n",
       "      <td>242.93</td>\n",
       "      <td>227.60</td>\n",
       "      <td>272.77</td>\n",
       "      <td>190.15</td>\n",
       "      <td>115.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>112.65</td>\n",
       "      <td>134.93</td>\n",
       "      <td>430.60</td>\n",
       "      <td>515.75</td>\n",
       "      <td>210.15</td>\n",
       "      <td>251.71</td>\n",
       "      <td>235.40</td>\n",
       "      <td>281.95</td>\n",
       "      <td>198.15</td>\n",
       "      <td>121.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>177.40</td>\n",
       "      <td>212.35</td>\n",
       "      <td>431.25</td>\n",
       "      <td>516.22</td>\n",
       "      <td>216.20</td>\n",
       "      <td>258.80</td>\n",
       "      <td>241.20</td>\n",
       "      <td>288.72</td>\n",
       "      <td>212.15</td>\n",
       "      <td>122.16</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>187.15</td>\n",
       "      <td>223.92</td>\n",
       "      <td>365.20</td>\n",
       "      <td>436.95</td>\n",
       "      <td>197.05</td>\n",
       "      <td>235.76</td>\n",
       "      <td>219.50</td>\n",
       "      <td>262.62</td>\n",
       "      <td>215.15</td>\n",
       "      <td>118.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>187.15</td>\n",
       "      <td>224.16</td>\n",
       "      <td>351.65</td>\n",
       "      <td>421.19</td>\n",
       "      <td>192.15</td>\n",
       "      <td>230.15</td>\n",
       "      <td>214.60</td>\n",
       "      <td>257.04</td>\n",
       "      <td>240.15</td>\n",
       "      <td>118.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-11</th>\n",
       "      <td>187.15</td>\n",
       "      <td>224.32</td>\n",
       "      <td>290.20</td>\n",
       "      <td>347.84</td>\n",
       "      <td>177.60</td>\n",
       "      <td>212.87</td>\n",
       "      <td>194.60</td>\n",
       "      <td>233.25</td>\n",
       "      <td>265.15</td>\n",
       "      <td>118.84</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-12</th>\n",
       "      <td>188.15</td>\n",
       "      <td>225.52</td>\n",
       "      <td>261.20</td>\n",
       "      <td>313.08</td>\n",
       "      <td>171.55</td>\n",
       "      <td>205.62</td>\n",
       "      <td>190.55</td>\n",
       "      <td>228.40</td>\n",
       "      <td>235.15</td>\n",
       "      <td>114.95</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>185.15</td>\n",
       "      <td>221.79</td>\n",
       "      <td>260.80</td>\n",
       "      <td>312.41</td>\n",
       "      <td>185.25</td>\n",
       "      <td>221.91</td>\n",
       "      <td>200.20</td>\n",
       "      <td>239.82</td>\n",
       "      <td>219.15</td>\n",
       "      <td>113.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>192.15</td>\n",
       "      <td>230.04</td>\n",
       "      <td>277.60</td>\n",
       "      <td>332.34</td>\n",
       "      <td>194.85</td>\n",
       "      <td>233.27</td>\n",
       "      <td>209.80</td>\n",
       "      <td>251.17</td>\n",
       "      <td>412.15</td>\n",
       "      <td>116.31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "description UK Base Weekend UK Base Wknd Euro UK GTMA 1-Mo Pk  \\\n",
       "symbol              AADNN00           AADNP00         AADGV00   \n",
       "currency                GBP               EUR             GBP   \n",
       "uom                     MGW               MGW             MGW   \n",
       "assessDate                                                      \n",
       "2022-01-03              NaN               NaN             NaN   \n",
       "2022-01-04           112.65            135.01          427.55   \n",
       "2022-01-05           112.65            134.93          430.60   \n",
       "2022-01-06           177.40            212.35          431.25   \n",
       "2022-01-07           187.15            223.92          365.20   \n",
       "2022-01-10           187.15            224.16          351.65   \n",
       "2022-01-11           187.15            224.32          290.20   \n",
       "2022-01-12           188.15            225.52          261.20   \n",
       "2022-01-13           185.15            221.79          260.80   \n",
       "2022-01-14           192.15            230.04          277.60   \n",
       "\n",
       "description UK GTMA 1-Mo Pk Euro UK GTMA 2-Mo Base UK GTMA 2-Mo Base Euro  \\\n",
       "symbol                   AADIJ00           AADNS00                AADNU00   \n",
       "currency                     EUR               GBP                    EUR   \n",
       "uom                          MGW               MGW                    MGW   \n",
       "assessDate                                                                  \n",
       "2022-01-03                   NaN               NaN                    NaN   \n",
       "2022-01-04                512.40            202.70                 242.93   \n",
       "2022-01-05                515.75            210.15                 251.71   \n",
       "2022-01-06                516.22            216.20                 258.80   \n",
       "2022-01-07                436.95            197.05                 235.76   \n",
       "2022-01-10                421.19            192.15                 230.15   \n",
       "2022-01-11                347.84            177.60                 212.87   \n",
       "2022-01-12                313.08            171.55                 205.62   \n",
       "2022-01-13                312.41            185.25                 221.91   \n",
       "2022-01-14                332.34            194.85                 233.27   \n",
       "\n",
       "description UK GTMA 2-Mo Pk UK GTMA 2-Mo Pk Euro UK GTMA DA Pk FDt  \\\n",
       "symbol              AADXH00              AADXJ00           AADFC21   \n",
       "currency                GBP                  EUR               GBP   \n",
       "uom                     MGW                  MGW               MGW   \n",
       "assessDate                                                           \n",
       "2022-01-03              NaN                  NaN            155.15   \n",
       "2022-01-04           227.60               272.77            190.15   \n",
       "2022-01-05           235.40               281.95            198.15   \n",
       "2022-01-06           241.20               288.72            212.15   \n",
       "2022-01-07           219.50               262.62            215.15   \n",
       "2022-01-10           214.60               257.04            240.15   \n",
       "2022-01-11           194.60               233.25            265.15   \n",
       "2022-01-12           190.55               228.40            235.15   \n",
       "2022-01-13           200.20               239.82            219.15   \n",
       "2022-01-14           209.80               251.17            412.15   \n",
       "\n",
       "description UK/GTMA Baseload Season 3 Euro  \n",
       "symbol                             AAIKB00  \n",
       "currency                               EUR  \n",
       "uom                                    MGW  \n",
       "assessDate                                  \n",
       "2022-01-03                             NaN  \n",
       "2022-01-04                          115.71  \n",
       "2022-01-05                          121.81  \n",
       "2022-01-06                          122.16  \n",
       "2022-01-07                          118.03  \n",
       "2022-01-10                          118.88  \n",
       "2022-01-11                          118.84  \n",
       "2022-01-12                          114.95  \n",
       "2022-01-13                          113.98  \n",
       "2022-01-14                          116.31  "
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt = sym_history.pivot_table(index='assessDate', values='value', columns=['description', 'symbol', 'currency', 'uom'])\n",
    "pt.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pt.plot(subplots=True, sharex=True, sharey=True, layout=(5,2), figsize=(12,8));\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "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>description</th>\n",
       "      <th>symbol</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>value</th>\n",
       "      <th>currency</th>\n",
       "      <th>uom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>155.15</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>2022-01-04</td>\n",
       "      <td>190.15</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>198.15</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>2022-01-06</td>\n",
       "      <td>212.15</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>2022-01-07</td>\n",
       "      <td>215.15</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2947</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-02-27</td>\n",
       "      <td>146.66</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2948</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-02-28</td>\n",
       "      <td>144.95</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2949</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>142.92</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2950</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-02</td>\n",
       "      <td>141.46</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2951</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>137.77</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2952 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         description   symbol assessDate   value currency  uom\n",
       "0                  UK GTMA DA Pk FDt  AADFC21 2022-01-03  155.15      GBP  MGW\n",
       "1                  UK GTMA DA Pk FDt  AADFC21 2022-01-04  190.15      GBP  MGW\n",
       "2                  UK GTMA DA Pk FDt  AADFC21 2022-01-05  198.15      GBP  MGW\n",
       "3                  UK GTMA DA Pk FDt  AADFC21 2022-01-06  212.15      GBP  MGW\n",
       "4                  UK GTMA DA Pk FDt  AADFC21 2022-01-07  215.15      GBP  MGW\n",
       "...                              ...      ...        ...     ...      ...  ...\n",
       "2947  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-02-27  146.66      EUR  MGW\n",
       "2948  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-02-28  144.95      EUR  MGW\n",
       "2949  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-01  142.92      EUR  MGW\n",
       "2950  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-02  141.46      EUR  MGW\n",
       "2951  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-03  137.77      EUR  MGW\n",
       "\n",
       "[2952 rows x 6 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym_history = sym_history[['description', 'symbol', 'assessDate', 'value', 'currency', 'uom']]\n",
    "sym_history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>assessment_frequency</th>\n",
       "      <th>bate_code</th>\n",
       "      <th>holiday_schedule</th>\n",
       "      <th>commodity</th>\n",
       "      <th>contract_type</th>\n",
       "      <th>currency</th>\n",
       "      <th>decimal_places</th>\n",
       "      <th>publication_frequency_code</th>\n",
       "      <th>...</th>\n",
       "      <th>mdc</th>\n",
       "      <th>day_of_publication</th>\n",
       "      <th>quotation_style</th>\n",
       "      <th>delivery_region</th>\n",
       "      <th>delivery_region_basis</th>\n",
       "      <th>settlement_type</th>\n",
       "      <th>active</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>uom</th>\n",
       "      <th>exchange</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>JPYUS00</td>\n",
       "      <td>JPY-USD Spot NY</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[h, l, u]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX, MET, NFM]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QRERA00</td>\n",
       "      <td>QAR-USD at 16:30 Singapore</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAFCW00</td>\n",
       "      <td>Euro/US$ forex rate 4:30 London</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[AGS, FX, RIC]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>UNS</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>GBP-USD Spot NY</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX, MET, NFM]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AUU1200</td>\n",
       "      <td>AUD-USD at 12:00 GMT</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>12:00 GMT</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CADUS00</td>\n",
       "      <td>CAD/USD Spot Forex US Close</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALUS00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ORERA00</td>\n",
       "      <td>OMR-USD at 16:30 Singapore</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>EUU1200</td>\n",
       "      <td>EUR-USD at 12:00 GMT</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>12:00 GMT</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AAWFT00</td>\n",
       "      <td>AUD-US Dollar</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[h, l, u]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX, RPR]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>UNS</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AUDUS00</td>\n",
       "      <td>AUD-USD Spot NY</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[h, l, u]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX, MET, NFM]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>BCUSD00</td>\n",
       "      <td>BOCAN US$ per Can$ EOD</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALCA00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 US Eastern</td>\n",
       "      <td>N/A</td>\n",
       "      <td>Bank of Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>IDRUS00</td>\n",
       "      <td>IDR-US Dollar Spot</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SRERA00</td>\n",
       "      <td>SAR-USD at 16:30 Singapore</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>AAWFU00</td>\n",
       "      <td>Euro-US Dollar</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[h, l, u]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX, RPR]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>UNS</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>EURUS00</td>\n",
       "      <td>EUR-USD Spot NY</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX, MET, NFM]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>14:30 US Eastern</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BCADD00</td>\n",
       "      <td>Euro/US Dollar at London MOC</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Prompt</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>CADUD00</td>\n",
       "      <td>CAD/USD Spot Forex London Close</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>UAEDR00</td>\n",
       "      <td>AED-USD at 16:30 Singapore</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALSG00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 Singapore</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>AACOP00</td>\n",
       "      <td>Euro-USD Spot</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Spot</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[EGP, FX]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>UNS</td>\n",
       "      <td>NEX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>BCADB00</td>\n",
       "      <td>British Pound/US Dollar at London MOC (NextGen...</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[c]</td>\n",
       "      <td>CALLN00</td>\n",
       "      <td>Currency</td>\n",
       "      <td>Prompt</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>Daily (weekdays)</td>\n",
       "      <td>Flat</td>\n",
       "      <td>Global</td>\n",
       "      <td>Global</td>\n",
       "      <td>Financial</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:30 UK</td>\n",
       "      <td>N/A</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>EUUSD00</td>\n",
       "      <td>ECB US$ per Euro</td>\n",
       "      <td>Daily (weekday)</td>\n",
       "      <td>[u]</td>\n",
       "      <td>#Not Applicable</td>\n",
       "      <td>Currency</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USD</td>\n",
       "      <td>5</td>\n",
       "      <td>DW</td>\n",
       "      <td>...</td>\n",
       "      <td>[FX]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Active - Public</td>\n",
       "      <td>16:00 Central European Time</td>\n",
       "      <td>UNS</td>\n",
       "      <td>ECB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     symbol                                        description  \\\n",
       "0   JPYUS00                                    JPY-USD Spot NY   \n",
       "1   QRERA00                         QAR-USD at 16:30 Singapore   \n",
       "2   AAFCW00                    Euro/US$ forex rate 4:30 London   \n",
       "3   GBPUS00                                    GBP-USD Spot NY   \n",
       "4   AUU1200                               AUD-USD at 12:00 GMT   \n",
       "5   CADUS00                        CAD/USD Spot Forex US Close   \n",
       "6   ORERA00                         OMR-USD at 16:30 Singapore   \n",
       "7   EUU1200                               EUR-USD at 12:00 GMT   \n",
       "8   AAWFT00                                      AUD-US Dollar   \n",
       "9   AUDUS00                                    AUD-USD Spot NY   \n",
       "10  BCUSD00                             BOCAN US$ per Can$ EOD   \n",
       "11  IDRUS00                                 IDR-US Dollar Spot   \n",
       "12  SRERA00                         SAR-USD at 16:30 Singapore   \n",
       "13  AAWFU00                                     Euro-US Dollar   \n",
       "14  EURUS00                                    EUR-USD Spot NY   \n",
       "15  BCADD00                       Euro/US Dollar at London MOC   \n",
       "16  CADUD00                    CAD/USD Spot Forex London Close   \n",
       "17  UAEDR00                         AED-USD at 16:30 Singapore   \n",
       "18  AACOP00                                      Euro-USD Spot   \n",
       "19  BCADB00  British Pound/US Dollar at London MOC (NextGen...   \n",
       "20  EUUSD00                                   ECB US$ per Euro   \n",
       "\n",
       "   assessment_frequency  bate_code holiday_schedule commodity contract_type  \\\n",
       "0       Daily (weekday)  [h, l, u]          CALSG00  Currency          Spot   \n",
       "1       Daily (weekday)        [c]          CALSG00  Currency          Spot   \n",
       "2       Daily (weekday)        [u]          CALLN00  Currency           NaN   \n",
       "3       Daily (weekday)        [u]          CALLN00  Currency          Spot   \n",
       "4       Daily (weekday)        [c]          CALLN00  Currency          Spot   \n",
       "5       Daily (weekday)        [u]          CALUS00  Currency          Spot   \n",
       "6       Daily (weekday)        [c]          CALSG00  Currency          Spot   \n",
       "7       Daily (weekday)        [c]          CALLN00  Currency          Spot   \n",
       "8       Daily (weekday)  [h, l, u]          CALSG00  Currency           NaN   \n",
       "9       Daily (weekday)  [h, l, u]          CALSG00  Currency          Spot   \n",
       "10      Daily (weekday)        [u]          CALCA00  Currency           NaN   \n",
       "11      Daily (weekday)        [c]          CALSG00  Currency          Spot   \n",
       "12      Daily (weekday)        [c]          CALSG00  Currency          Spot   \n",
       "13      Daily (weekday)  [h, l, u]          CALSG00  Currency           NaN   \n",
       "14      Daily (weekday)        [u]          CALLN00  Currency          Spot   \n",
       "15      Daily (weekday)        [c]          CALLN00  Currency        Prompt   \n",
       "16      Daily (weekday)        [c]          CALLN00  Currency          Spot   \n",
       "17      Daily (weekday)        [c]          CALSG00  Currency          Spot   \n",
       "18      Daily (weekday)        [u]          CALLN00  Currency          Spot   \n",
       "19      Daily (weekday)        [c]          CALLN00  Currency        Prompt   \n",
       "20      Daily (weekday)        [u]  #Not Applicable  Currency           NaN   \n",
       "\n",
       "   currency  decimal_places publication_frequency_code  ...             mdc  \\\n",
       "0       USD               4                         DW  ...  [FX, MET, NFM]   \n",
       "1       USD               4                         DW  ...            [FX]   \n",
       "2       USD               4                         DW  ...  [AGS, FX, RIC]   \n",
       "3       USD               4                         DW  ...  [FX, MET, NFM]   \n",
       "4       USD               4                         DW  ...            [FX]   \n",
       "5       USD               4                         DW  ...            [FX]   \n",
       "6       USD               4                         DW  ...            [FX]   \n",
       "7       USD               4                         DW  ...            [FX]   \n",
       "8       USD               4                         DW  ...       [FX, RPR]   \n",
       "9       USD               4                         DW  ...  [FX, MET, NFM]   \n",
       "10      USD               4                         DW  ...            [FX]   \n",
       "11      USD               4                         DW  ...            [FX]   \n",
       "12      USD               4                         DW  ...            [FX]   \n",
       "13      USD               4                         DW  ...       [FX, RPR]   \n",
       "14      USD               4                         DW  ...  [FX, MET, NFM]   \n",
       "15      USD               4                         DW  ...            [FX]   \n",
       "16      USD               4                         DW  ...            [FX]   \n",
       "17      USD               4                         DW  ...            [FX]   \n",
       "18      USD               4                         DW  ...       [EGP, FX]   \n",
       "19      USD               4                         DW  ...            [FX]   \n",
       "20      USD               5                         DW  ...            [FX]   \n",
       "\n",
       "   day_of_publication quotation_style delivery_region delivery_region_basis  \\\n",
       "0    Daily (weekdays)            Flat          Global                Global   \n",
       "1                 NaN            Flat          Global                Global   \n",
       "2    Daily (weekdays)             NaN          Global                Global   \n",
       "3    Daily (weekdays)            Flat          Global                Global   \n",
       "4                 NaN            Flat          Global                Global   \n",
       "5    Daily (weekdays)            Flat          Global                Global   \n",
       "6                 NaN            Flat          Global                Global   \n",
       "7                 NaN            Flat          Global                Global   \n",
       "8    Daily (weekdays)             NaN          Global                Global   \n",
       "9    Daily (weekdays)            Flat          Global                Global   \n",
       "10                NaN             NaN          Global                Global   \n",
       "11                NaN            Flat          Global                Global   \n",
       "12                NaN            Flat          Global                Global   \n",
       "13   Daily (weekdays)             NaN          Global                Global   \n",
       "14   Daily (weekdays)            Flat          Global                Global   \n",
       "15   Daily (weekdays)            Flat          Global                Global   \n",
       "16   Daily (weekdays)            Flat          Global                Global   \n",
       "17                NaN            Flat          Global                Global   \n",
       "18   Daily (weekdays)            Flat          Europe                Europe   \n",
       "19   Daily (weekdays)            Flat          Global                Global   \n",
       "20                NaN             NaN          Europe                Europe   \n",
       "\n",
       "   settlement_type           active                    timestamp  uom  \\\n",
       "0        Financial  Active - Public             14:30 US Eastern  N/A   \n",
       "1        Financial  Active - Public              16:30 Singapore  N/A   \n",
       "2              NaN  Active - Public                     16:30 UK  UNS   \n",
       "3        Financial  Active - Public             14:30 US Eastern  N/A   \n",
       "4        Financial  Active - Public                    12:00 GMT  N/A   \n",
       "5        Financial  Active - Public             14:30 US Eastern  N/A   \n",
       "6        Financial  Active - Public              16:30 Singapore  N/A   \n",
       "7        Financial  Active - Public                    12:00 GMT  N/A   \n",
       "8              NaN  Active - Public              16:30 Singapore  UNS   \n",
       "9        Financial  Active - Public             14:30 US Eastern  N/A   \n",
       "10             NaN  Active - Public             16:30 US Eastern  N/A   \n",
       "11       Financial  Active - Public              16:30 Singapore  N/A   \n",
       "12       Financial  Active - Public              16:30 Singapore  N/A   \n",
       "13             NaN  Active - Public              16:30 Singapore  UNS   \n",
       "14       Financial  Active - Public             14:30 US Eastern  N/A   \n",
       "15       Financial  Active - Public                     16:30 UK  N/A   \n",
       "16       Financial  Active - Public                     16:30 UK  N/A   \n",
       "17       Financial  Active - Public              16:30 Singapore  N/A   \n",
       "18       Financial  Active - Public                     16:30 UK  UNS   \n",
       "19       Financial  Active - Public                     16:30 UK  N/A   \n",
       "20             NaN  Active - Public  16:00 Central European Time  UNS   \n",
       "\n",
       "          exchange  \n",
       "0              NaN  \n",
       "1              NaN  \n",
       "2              NaN  \n",
       "3              NaN  \n",
       "4              NaN  \n",
       "5              NaN  \n",
       "6              NaN  \n",
       "7              NaN  \n",
       "8              NaN  \n",
       "9              NaN  \n",
       "10  Bank of Canada  \n",
       "11             NaN  \n",
       "12             NaN  \n",
       "13             NaN  \n",
       "14             NaN  \n",
       "15             NaN  \n",
       "16             NaN  \n",
       "17             NaN  \n",
       "18             NEX  \n",
       "19             NaN  \n",
       "20             ECB  \n",
       "\n",
       "[21 rows x 21 columns]"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fx_sym = mdd.get_symbols(mdc='FX', assessment_frequency=mdd.AssessmentFrequency.DailyWeekday, currency=\"USD\")\n",
    "fx_sym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bate</th>\n",
       "      <th>value</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1293</td>\n",
       "      <td>2022-01-04</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-04 16:51:05</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1327</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-05 16:53:05</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1307</td>\n",
       "      <td>2022-01-06</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-06 16:53:15</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1343</td>\n",
       "      <td>2022-01-07</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-07 16:50:06</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1325</td>\n",
       "      <td>2022-01-10</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-10 16:46:15</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>u</td>\n",
       "      <td>1.2025</td>\n",
       "      <td>2023-02-27</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-02-27 16:53:17</td>\n",
       "      <td>GBPUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>u</td>\n",
       "      <td>1.2116</td>\n",
       "      <td>2023-02-28</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-02-28 16:49:25</td>\n",
       "      <td>GBPUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>u</td>\n",
       "      <td>1.2020</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-01 16:58:16</td>\n",
       "      <td>GBPUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1944</td>\n",
       "      <td>2023-03-02</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-02 16:50:00</td>\n",
       "      <td>GBPUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>587</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1978</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 16:43:10</td>\n",
       "      <td>GBPUS00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>588 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bate   value assessDate isCorrected             modDate   symbol\n",
       "0      u  1.1293 2022-01-04           N 2022-01-04 16:51:05  EURUS00\n",
       "1      u  1.1327 2022-01-05           N 2022-01-05 16:53:05  EURUS00\n",
       "2      u  1.1307 2022-01-06           N 2022-01-06 16:53:15  EURUS00\n",
       "3      u  1.1343 2022-01-07           N 2022-01-07 16:50:06  EURUS00\n",
       "4      u  1.1325 2022-01-10           N 2022-01-10 16:46:15  EURUS00\n",
       "..   ...     ...        ...         ...                 ...      ...\n",
       "583    u  1.2025 2023-02-27           N 2023-02-27 16:53:17  GBPUS00\n",
       "584    u  1.2116 2023-02-28           N 2023-02-28 16:49:25  GBPUS00\n",
       "585    u  1.2020 2023-03-01           N 2023-03-01 16:58:16  GBPUS00\n",
       "586    u  1.1944 2023-03-02           N 2023-03-02 16:50:00  GBPUS00\n",
       "587    u  1.1978 2023-03-03           N 2023-03-03 16:43:10  GBPUS00\n",
       "\n",
       "[588 rows x 6 columns]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "symbols = [\"GBPUS00\", \"EURUS00\"]\n",
    "fx_assessments = mdd.get_assessments_by_symbol_historical(symbol=symbols, assess_date_gte=date(2022, 1, 1))\n",
    "fx_assessments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bate</th>\n",
       "      <th>value</th>\n",
       "      <th>assessDate</th>\n",
       "      <th>isCorrected</th>\n",
       "      <th>modDate</th>\n",
       "      <th>symbol</th>\n",
       "      <th>currency</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1293</td>\n",
       "      <td>2022-01-04</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-04 16:51:05</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1327</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-05 16:53:05</td>\n",
       "      <td>EURUS00</td>\n",
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       "      <th>2</th>\n",
       "      <td>u</td>\n",
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       "      <td>2022-01-06</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-06 16:53:15</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1343</td>\n",
       "      <td>2022-01-07</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-07 16:50:06</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1325</td>\n",
       "      <td>2022-01-10</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-10 16:46:15</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>EUR</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",
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       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>u</td>\n",
       "      <td>1.2025</td>\n",
       "      <td>2023-02-27</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-02-27 16:53:17</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>u</td>\n",
       "      <td>1.2116</td>\n",
       "      <td>2023-02-28</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-02-28 16:49:25</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>u</td>\n",
       "      <td>1.2020</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-01 16:58:16</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1944</td>\n",
       "      <td>2023-03-02</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-02 16:50:00</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>587</th>\n",
       "      <td>u</td>\n",
       "      <td>1.1978</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 16:43:10</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>588 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bate   value assessDate isCorrected             modDate   symbol currency\n",
       "0      u  1.1293 2022-01-04           N 2022-01-04 16:51:05  EURUS00      EUR\n",
       "1      u  1.1327 2022-01-05           N 2022-01-05 16:53:05  EURUS00      EUR\n",
       "2      u  1.1307 2022-01-06           N 2022-01-06 16:53:15  EURUS00      EUR\n",
       "3      u  1.1343 2022-01-07           N 2022-01-07 16:50:06  EURUS00      EUR\n",
       "4      u  1.1325 2022-01-10           N 2022-01-10 16:46:15  EURUS00      EUR\n",
       "..   ...     ...        ...         ...                 ...      ...      ...\n",
       "583    u  1.2025 2023-02-27           N 2023-02-27 16:53:17  GBPUS00      GBP\n",
       "584    u  1.2116 2023-02-28           N 2023-02-28 16:49:25  GBPUS00      GBP\n",
       "585    u  1.2020 2023-03-01           N 2023-03-01 16:58:16  GBPUS00      GBP\n",
       "586    u  1.1944 2023-03-02           N 2023-03-02 16:50:00  GBPUS00      GBP\n",
       "587    u  1.1978 2023-03-03           N 2023-03-03 16:43:10  GBPUS00      GBP\n",
       "\n",
       "[588 rows x 7 columns]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fx_assessments['currency'] = fx_assessments['symbol'].apply(lambda x: \"EUR\" if x == \"EURUS00\" else \"GBP\")\n",
    "fx_assessments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>155.15</td>\n",
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       "      <td>UK GTMA DA Pk FDt</td>\n",
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       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
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       "      <td>212.15</td>\n",
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       "      <td>GBPUS00</td>\n",
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       "      <td>2022-01-07</td>\n",
       "      <td>215.15</td>\n",
       "      <td>GBP</td>\n",
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       "      <td>2022-01-07 16:50:06</td>\n",
       "      <td>GBPUS00</td>\n",
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       "    <tr>\n",
       "      <th>2947</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-02-27</td>\n",
       "      <td>146.66</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0589</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-02-27 16:53:17</td>\n",
       "      <td>EURUS00</td>\n",
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       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-02-28</td>\n",
       "      <td>144.95</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0610</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-02-28 16:49:25</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2949</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>142.92</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0673</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-01 16:58:16</td>\n",
       "      <td>EURUS00</td>\n",
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       "    <tr>\n",
       "      <th>2950</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-02</td>\n",
       "      <td>141.46</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0597</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-02 16:50:00</td>\n",
       "      <td>EURUS00</td>\n",
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       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>137.77</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0603</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 16:43:10</td>\n",
       "      <td>EURUS00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2952 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         description   symbol assessDate   value currency  \\\n",
       "0                  UK GTMA DA Pk FDt  AADFC21 2022-01-03  155.15      GBP   \n",
       "1                  UK GTMA DA Pk FDt  AADFC21 2022-01-04  190.15      GBP   \n",
       "2                  UK GTMA DA Pk FDt  AADFC21 2022-01-05  198.15      GBP   \n",
       "3                  UK GTMA DA Pk FDt  AADFC21 2022-01-06  212.15      GBP   \n",
       "4                  UK GTMA DA Pk FDt  AADFC21 2022-01-07  215.15      GBP   \n",
       "...                              ...      ...        ...     ...      ...   \n",
       "2947  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-02-27  146.66      EUR   \n",
       "2948  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-02-28  144.95      EUR   \n",
       "2949  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-01  142.92      EUR   \n",
       "2950  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-02  141.46      EUR   \n",
       "2951  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-03  137.77      EUR   \n",
       "\n",
       "      uom bate  value_fx isCorrected             modDate symbol_fx  \n",
       "0     MGW  NaN       NaN         NaN                 NaT       NaN  \n",
       "1     MGW    u    1.3537           N 2022-01-04 16:51:05   GBPUS00  \n",
       "2     MGW    u    1.3567           N 2022-01-05 16:53:05   GBPUS00  \n",
       "3     MGW    u    1.3537           N 2022-01-06 16:53:15   GBPUS00  \n",
       "4     MGW    u    1.3571           N 2022-01-07 16:50:06   GBPUS00  \n",
       "...   ...  ...       ...         ...                 ...       ...  \n",
       "2947  MGW    u    1.0589           N 2023-02-27 16:53:17   EURUS00  \n",
       "2948  MGW    u    1.0610           N 2023-02-28 16:49:25   EURUS00  \n",
       "2949  MGW    u    1.0673           N 2023-03-01 16:58:16   EURUS00  \n",
       "2950  MGW    u    1.0597           N 2023-03-02 16:50:00   EURUS00  \n",
       "2951  MGW    u    1.0603           N 2023-03-03 16:43:10   EURUS00  \n",
       "\n",
       "[2952 rows x 11 columns]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined = sym_history.merge(fx_assessments, on=['assessDate', 'currency'], how='left', suffixes=('', '_fx'))\n",
    "joined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
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       "      <td>198.15</td>\n",
       "      <td>GBP</td>\n",
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       "      <td>1.3567</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-05 16:53:05</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>268.830105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
       "      <td>2022-01-06</td>\n",
       "      <td>212.15</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.3537</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-06 16:53:15</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>287.187455</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>UK GTMA DA Pk FDt</td>\n",
       "      <td>AADFC21</td>\n",
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       "      <td>215.15</td>\n",
       "      <td>GBP</td>\n",
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       "      <td>u</td>\n",
       "      <td>1.3571</td>\n",
       "      <td>N</td>\n",
       "      <td>2022-01-07 16:50:06</td>\n",
       "      <td>GBPUS00</td>\n",
       "      <td>291.980065</td>\n",
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       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
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       "      <td>2023-02-27</td>\n",
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       "      <td>EUR</td>\n",
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       "      <td>N</td>\n",
       "      <td>2023-02-27 16:53:17</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>155.298274</td>\n",
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       "    <tr>\n",
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       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-02-28</td>\n",
       "      <td>144.95</td>\n",
       "      <td>EUR</td>\n",
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       "      <td>N</td>\n",
       "      <td>2023-02-28 16:49:25</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>153.791950</td>\n",
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       "    <tr>\n",
       "      <th>2949</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>142.92</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0673</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-01 16:58:16</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>152.538516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2950</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-02</td>\n",
       "      <td>141.46</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0597</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-02 16:50:00</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>149.905162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2951</th>\n",
       "      <td>UK/GTMA Baseload Season 3 Euro</td>\n",
       "      <td>AAIKB00</td>\n",
       "      <td>2023-03-03</td>\n",
       "      <td>137.77</td>\n",
       "      <td>EUR</td>\n",
       "      <td>MGW</td>\n",
       "      <td>u</td>\n",
       "      <td>1.0603</td>\n",
       "      <td>N</td>\n",
       "      <td>2023-03-03 16:43:10</td>\n",
       "      <td>EURUS00</td>\n",
       "      <td>146.077531</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2952 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         description   symbol assessDate   value currency  \\\n",
       "0                  UK GTMA DA Pk FDt  AADFC21 2022-01-03  155.15      GBP   \n",
       "1                  UK GTMA DA Pk FDt  AADFC21 2022-01-04  190.15      GBP   \n",
       "2                  UK GTMA DA Pk FDt  AADFC21 2022-01-05  198.15      GBP   \n",
       "3                  UK GTMA DA Pk FDt  AADFC21 2022-01-06  212.15      GBP   \n",
       "4                  UK GTMA DA Pk FDt  AADFC21 2022-01-07  215.15      GBP   \n",
       "...                              ...      ...        ...     ...      ...   \n",
       "2947  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-02-27  146.66      EUR   \n",
       "2948  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-02-28  144.95      EUR   \n",
       "2949  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-01  142.92      EUR   \n",
       "2950  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-02  141.46      EUR   \n",
       "2951  UK/GTMA Baseload Season 3 Euro  AAIKB00 2023-03-03  137.77      EUR   \n",
       "\n",
       "      uom bate  value_fx isCorrected             modDate symbol_fx   value_usd  \n",
       "0     MGW  NaN       NaN         NaN                 NaT       NaN         NaN  \n",
       "1     MGW    u    1.3537           N 2022-01-04 16:51:05   GBPUS00  257.406055  \n",
       "2     MGW    u    1.3567           N 2022-01-05 16:53:05   GBPUS00  268.830105  \n",
       "3     MGW    u    1.3537           N 2022-01-06 16:53:15   GBPUS00  287.187455  \n",
       "4     MGW    u    1.3571           N 2022-01-07 16:50:06   GBPUS00  291.980065  \n",
       "...   ...  ...       ...         ...                 ...       ...         ...  \n",
       "2947  MGW    u    1.0589           N 2023-02-27 16:53:17   EURUS00  155.298274  \n",
       "2948  MGW    u    1.0610           N 2023-02-28 16:49:25   EURUS00  153.791950  \n",
       "2949  MGW    u    1.0673           N 2023-03-01 16:58:16   EURUS00  152.538516  \n",
       "2950  MGW    u    1.0597           N 2023-03-02 16:50:00   EURUS00  149.905162  \n",
       "2951  MGW    u    1.0603           N 2023-03-03 16:43:10   EURUS00  146.077531  \n",
       "\n",
       "[2952 rows x 12 columns]"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined['value_usd'] = joined['value'] * joined['value_fx']\n",
    "joined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>description</th>\n",
       "      <th>UK Base Weekend</th>\n",
       "      <th>UK Base Wknd Euro</th>\n",
       "      <th>UK GTMA 1-Mo Pk</th>\n",
       "      <th>UK GTMA 1-Mo Pk Euro</th>\n",
       "      <th>UK GTMA 2-Mo Base</th>\n",
       "      <th>UK GTMA 2-Mo Base Euro</th>\n",
       "      <th>UK GTMA 2-Mo Pk</th>\n",
       "      <th>UK GTMA 2-Mo Pk Euro</th>\n",
       "      <th>UK GTMA DA Pk FDt</th>\n",
       "      <th>UK/GTMA Baseload Season 3 Euro</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symbol</th>\n",
       "      <th>AADNN00</th>\n",
       "      <th>AADNP00</th>\n",
       "      <th>AADGV00</th>\n",
       "      <th>AADIJ00</th>\n",
       "      <th>AADNS00</th>\n",
       "      <th>AADNU00</th>\n",
       "      <th>AADXH00</th>\n",
       "      <th>AADXJ00</th>\n",
       "      <th>AADFC21</th>\n",
       "      <th>AAIKB00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>assessDate</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>152.494305</td>\n",
       "      <td>152.466793</td>\n",
       "      <td>578.774435</td>\n",
       "      <td>578.653320</td>\n",
       "      <td>274.394990</td>\n",
       "      <td>274.340849</td>\n",
       "      <td>308.10212</td>\n",
       "      <td>308.039161</td>\n",
       "      <td>257.406055</td>\n",
       "      <td>130.671303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>152.832255</td>\n",
       "      <td>152.835211</td>\n",
       "      <td>584.195020</td>\n",
       "      <td>584.190025</td>\n",
       "      <td>285.110505</td>\n",
       "      <td>285.111917</td>\n",
       "      <td>319.36718</td>\n",
       "      <td>319.364765</td>\n",
       "      <td>268.830105</td>\n",
       "      <td>137.974187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>240.146380</td>\n",
       "      <td>240.104145</td>\n",
       "      <td>583.783125</td>\n",
       "      <td>583.689954</td>\n",
       "      <td>292.669940</td>\n",
       "      <td>292.625160</td>\n",
       "      <td>326.51244</td>\n",
       "      <td>326.455704</td>\n",
       "      <td>287.187455</td>\n",
       "      <td>138.126312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>253.981265</td>\n",
       "      <td>253.992456</td>\n",
       "      <td>495.612920</td>\n",
       "      <td>495.632385</td>\n",
       "      <td>267.416555</td>\n",
       "      <td>267.422568</td>\n",
       "      <td>297.88345</td>\n",
       "      <td>297.889866</td>\n",
       "      <td>291.980065</td>\n",
       "      <td>133.881429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>253.906405</td>\n",
       "      <td>253.861200</td>\n",
       "      <td>477.083555</td>\n",
       "      <td>476.997675</td>\n",
       "      <td>260.689905</td>\n",
       "      <td>260.644875</td>\n",
       "      <td>291.14782</td>\n",
       "      <td>291.097800</td>\n",
       "      <td>325.811505</td>\n",
       "      <td>134.631600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "description UK Base Weekend UK Base Wknd Euro UK GTMA 1-Mo Pk  \\\n",
       "symbol              AADNN00           AADNP00         AADGV00   \n",
       "assessDate                                                      \n",
       "2022-01-04       152.494305        152.466793      578.774435   \n",
       "2022-01-05       152.832255        152.835211      584.195020   \n",
       "2022-01-06       240.146380        240.104145      583.783125   \n",
       "2022-01-07       253.981265        253.992456      495.612920   \n",
       "2022-01-10       253.906405        253.861200      477.083555   \n",
       "\n",
       "description UK GTMA 1-Mo Pk Euro UK GTMA 2-Mo Base UK GTMA 2-Mo Base Euro  \\\n",
       "symbol                   AADIJ00           AADNS00                AADNU00   \n",
       "assessDate                                                                  \n",
       "2022-01-04            578.653320        274.394990             274.340849   \n",
       "2022-01-05            584.190025        285.110505             285.111917   \n",
       "2022-01-06            583.689954        292.669940             292.625160   \n",
       "2022-01-07            495.632385        267.416555             267.422568   \n",
       "2022-01-10            476.997675        260.689905             260.644875   \n",
       "\n",
       "description UK GTMA 2-Mo Pk UK GTMA 2-Mo Pk Euro UK GTMA DA Pk FDt  \\\n",
       "symbol              AADXH00              AADXJ00           AADFC21   \n",
       "assessDate                                                           \n",
       "2022-01-04        308.10212           308.039161        257.406055   \n",
       "2022-01-05        319.36718           319.364765        268.830105   \n",
       "2022-01-06        326.51244           326.455704        287.187455   \n",
       "2022-01-07        297.88345           297.889866        291.980065   \n",
       "2022-01-10        291.14782           291.097800        325.811505   \n",
       "\n",
       "description UK/GTMA Baseload Season 3 Euro  \n",
       "symbol                             AAIKB00  \n",
       "assessDate                                  \n",
       "2022-01-04                      130.671303  \n",
       "2022-01-05                      137.974187  \n",
       "2022-01-06                      138.126312  \n",
       "2022-01-07                      133.881429  \n",
       "2022-01-10                      134.631600  "
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt = joined.pivot_table(index='assessDate', values='value_usd', columns=['description', 'symbol'])\n",
    "pt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pt.plot(subplots=True, sharex=True, sharey=True, layout=(5,2), figsize=(12,8), title=\"Nat Gas Prices ($/MGW)\");\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "spgci-wcAZ9YZM-py3.10",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "1014a47c46ae5114be3ec7f7a897beb70a9451d83abead7da29661e49e5f5c35"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}