V1/features/horizon/Using TraderMade FX spot price data in LUSID.ipynb

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   "source": [
    "from lusidtools.jupyter_tools import toggle_code\n",
    "\n",
    "\"\"\"Using TraderMade FX spot price data in LUSID\n",
    "\n",
    "This notebook shows you how to access TraderMade spot FX data in LUSID\n",
    "\n",
    "Attributes\n",
    "----------\n",
    "quotes\n",
    "\"\"\"\n",
    "\n",
    "toggle_code(\"Toggle Docstring\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using TraderMade FX spot price data in LUSID\n",
    "\n",
    "This notebook shows you how to access TraderMade spot FX data in LUSID. For some background, [TraderMade](https://tradermade.com/about) is a vendor of FX data who provide this FX data into your LUSID environment. Each day we load spot prices for 280+ currency pairs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LUSID Environment Initialised\n",
      "LUSID SDK Version:  0.6.11998.0\n"
     ]
    }
   ],
   "source": [
    "# Import LUSID APIs and Models\n",
    "import lusid\n",
    "import lusid.models as models\n",
    "\n",
    "# Import LUSID Python tools \n",
    "from lusidtools.pandas_utils.lusid_pandas import lusid_response_to_data_frame\n",
    "from lusidjam.refreshing_token import RefreshingToken\n",
    "\n",
    "# Import general system libraries\n",
    "from datetime import datetime, timedelta, time, date\n",
    "import pytz\n",
    "import uuid\n",
    "import os\n",
    "from datetime import datetime\n",
    "\n",
    "# Import data wrangling packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import json\n",
    "\n",
    "# Authenticate our user and create our API client\n",
    "secrets_path = os.getenv(\"FBN_SECRETS_PATH\")\n",
    "\n",
    "# Create API factory\n",
    "api_factory = lusid.utilities.ApiClientFactory(\n",
    "    token=RefreshingToken(),\n",
    "    api_secrets_filename = secrets_path,\n",
    "    app_name=\"LusidJupyterNotebook\")\n",
    "\n",
    "print ('LUSID Environment Initialised')\n",
    "print ('LUSID SDK Version: ', api_factory.build(lusid.api.ApplicationMetadataApi).get_lusid_versions().build_version)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup notebook configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import ploting libraries and configuration\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Use line magic function to enable matplotlib to work interactively with iPython\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# Set style to fivethirtyeight to create clean and clear looking graphs\n",
    "\n",
    "plt.style.use('fivethirtyeight')\n",
    "\n",
    "# Define a dictionary containing default plotting configurations\n",
    "\n",
    "params = {'legend.fontsize': 'small',\n",
    "          'figure.figsize': (12, 4.5),\n",
    "         'axes.labelsize': 'small',\n",
    "         'axes.titlesize': 'medium',\n",
    "         'xtick.labelsize': 'small',\n",
    "         'ytick.labelsize': 'small'}\n",
    "\n",
    "plt.rcParams.update(params)\n",
    "\n",
    "with open(r\"config/tm_dataframe_mappings.json\") as mappings_file:\n",
    "    json_mappings = json.load(mappings_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Declare a scope which contains TraderMade FX data\n",
    "\n",
    "The TraderMade FX data is loaded into LUSID each night into the <b>TraderMadeFxData</b> scope. You will need to make LUSID calls against this scope to access the TraderMade data. Please see this [page](https://support.finbourne.com/what-is-a-scope-in-lusid-and-how-is-it-used) for more information on scopes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "scope = \"TraderMadeFxData\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `tradermade_enabled` flag is used to indicate if TraderMade data has been enabled in the LUSID instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "tradermade_enabled = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_quotes(filter, fallback_csv, limit=5000):\n",
    "    if tradermade_enabled:        \n",
    "        quotes_response = quotes_api.list_quotes(scope=scope, filter=filter, limit=limit)\n",
    "        return lusid_response_to_data_frame(quotes_response, column_name_mapping=json_mappings)\n",
    "    else:\n",
    "        return pd.read_csv(fallback_csv, sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Call FX spot data using LUSID's APIs\n",
    "\n",
    "We can call the TraderMade data using the QuotesApi passing the <b>TraderMadeFxData</b> scope."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare a QuotesApi object\n",
    "quotes_api = api_factory.build(lusid.api.QuotesApi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare start date and end date string\n",
    "start_date = \"2019-12-27\" \n",
    "end_date = \"2020-03-27\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Call list_quotes to list out some quotes for 7 days in March 2020\n",
    "quotes_df = get_quotes(**{\n",
    "    \"filter\": f\"QuoteId.EffectiveAt gte 2020-03-19 and QuoteId.EffectiveAt lte {end_date}\",\n",
    "    \"fallback_csv\": \"data/fx_rates.txt\"\n",
    "})        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Provider</th>\n",
       "      <th>InstrumentID</th>\n",
       "      <th>InstrumentType</th>\n",
       "      <th>QuoteType</th>\n",
       "      <th>Field</th>\n",
       "      <th>EffectiveAt</th>\n",
       "      <th>Value</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TraderMade</td>\n",
       "      <td>USD/JPY</td>\n",
       "      <td>CurrencyPair</td>\n",
       "      <td>Price</td>\n",
       "      <td>close</td>\n",
       "      <td>2020-03-24T00:00:00.0000000+00:00</td>\n",
       "      <td>111.19600</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TraderMade</td>\n",
       "      <td>USD/JPY</td>\n",
       "      <td>CurrencyPair</td>\n",
       "      <td>Price</td>\n",
       "      <td>close</td>\n",
       "      <td>2020-03-23T00:00:00.0000000+00:00</td>\n",
       "      <td>111.24736</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "     Provider InstrumentID InstrumentType QuoteType  Field  \\\n",
       "0  TraderMade      USD/JPY   CurrencyPair     Price  close   \n",
       "1  TraderMade      USD/JPY   CurrencyPair     Price  close   \n",
       "\n",
       "                         EffectiveAt      Value Unit  \n",
       "0  2020-03-24T00:00:00.0000000+00:00  111.19600  USD  \n",
       "1  2020-03-23T00:00:00.0000000+00:00  111.24736  USD  "
      ]
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     "metadata": {},
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    }
   ],
   "source": [
    "quotes_df.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note - please contact support@lusid.com if you have no FX data in the <b>TraderMadeFxData</b> scope."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We load quotes for 280+ currency pairs a day "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "quotes_df = get_quotes(**{\n",
    "    \"filter\": f\"QuoteId.EffectiveAt eq 2020-03-23\", \n",
    "    \"fallback_csv\": \"data/fx_rates_day.txt\"\n",
    "})        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CurrencyPair</th>\n",
       "      <th>CurrencyPair</th>\n",
       "      <th>CurrencyPair</th>\n",
       "      <th>CurrencyPair</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AED/EUR</td>\n",
       "      <td>AED/GBP</td>\n",
       "      <td>AED/USD</td>\n",
       "      <td>ARS/USD</td>\n",
       "      <td>AUD/BRL</td>\n",
       "      <td>AUD/CAD</td>\n",
       "      <td>AUD/CHF</td>\n",
       "      <td>AUD/DKK</td>\n",
       "      <td>AUD/EUR</td>\n",
       "      <td>AUD/GBP</td>\n",
       "      <td>AUD/JPY</td>\n",
       "      <td>AUD/MXN</td>\n",
       "      <td>AUD/NOK</td>\n",
       "      <td>AUD/NZD</td>\n",
       "      <td>AUD/RUB</td>\n",
       "      <td>AUD/SEK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AUD/SGD</td>\n",
       "      <td>AUD/USD</td>\n",
       "      <td>BRL/AUD</td>\n",
       "      <td>BRL/COP</td>\n",
       "      <td>BRL/EUR</td>\n",
       "      <td>BRL/GBP</td>\n",
       "      <td>BRL/JPY</td>\n",
       "      <td>BRL/MXN</td>\n",
       "      <td>BRL/USD</td>\n",
       "      <td>CAD/AUD</td>\n",
       "      <td>CAD/CHF</td>\n",
       "      <td>CAD/EUR</td>\n",
       "      <td>CAD/GBP</td>\n",
       "      <td>CAD/JPY</td>\n",
       "      <td>CAD/MXN</td>\n",
       "      <td>CAD/NOK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CAD/NZD</td>\n",
       "      <td>CAD/SEK</td>\n",
       "      <td>CAD/USD</td>\n",
       "      <td>CHF/AUD</td>\n",
       "      <td>CHF/CAD</td>\n",
       "      <td>CHF/DKK</td>\n",
       "      <td>CHF/EUR</td>\n",
       "      <td>CHF/GBP</td>\n",
       "      <td>CHF/ISK</td>\n",
       "      <td>CHF/JPY</td>\n",
       "      <td>CHF/NOK</td>\n",
       "      <td>CHF/NZD</td>\n",
       "      <td>CHF/PLN</td>\n",
       "      <td>CHF/SEK</td>\n",
       "      <td>CHF/TRY</td>\n",
       "      <td>CHF/USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHF/ZAR</td>\n",
       "      <td>CLP/EUR</td>\n",
       "      <td>CLP/USD</td>\n",
       "      <td>CNY/USD</td>\n",
       "      <td>COP/BRL</td>\n",
       "      <td>COP/EUR</td>\n",
       "      <td>COP/USD</td>\n",
       "      <td>CZK/EUR</td>\n",
       "      <td>CZK/GBP</td>\n",
       "      <td>CZK/SEK</td>\n",
       "      <td>CZK/USD</td>\n",
       "      <td>DKK/AUD</td>\n",
       "      <td>DKK/CHF</td>\n",
       "      <td>DKK/EUR</td>\n",
       "      <td>DKK/GBP</td>\n",
       "      <td>DKK/JPY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DKK/NOK</td>\n",
       "      <td>DKK/NZD</td>\n",
       "      <td>DKK/SEK</td>\n",
       "      <td>DKK/USD</td>\n",
       "      <td>EUR/AED</td>\n",
       "      <td>EUR/AUD</td>\n",
       "      <td>EUR/BRL</td>\n",
       "      <td>EUR/CAD</td>\n",
       "      <td>EUR/CHF</td>\n",
       "      <td>EUR/CLP</td>\n",
       "      <td>EUR/COP</td>\n",
       "      <td>EUR/CZK</td>\n",
       "      <td>EUR/DKK</td>\n",
       "      <td>EUR/GBP</td>\n",
       "      <td>EUR/HKD</td>\n",
       "      <td>EUR/HRK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>EUR/HUF</td>\n",
       "      <td>EUR/IDR</td>\n",
       "      <td>EUR/ILS</td>\n",
       "      <td>EUR/INR</td>\n",
       "      <td>EUR/ISK</td>\n",
       "      <td>EUR/JPY</td>\n",
       "      <td>EUR/KRW</td>\n",
       "      <td>EUR/MAD</td>\n",
       "      <td>EUR/MXN</td>\n",
       "      <td>EUR/MYR</td>\n",
       "      <td>EUR/NOK</td>\n",
       "      <td>EUR/NZD</td>\n",
       "      <td>EUR/PEN</td>\n",
       "      <td>EUR/PHP</td>\n",
       "      <td>EUR/PLN</td>\n",
       "      <td>EUR/RON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>EUR/RUB</td>\n",
       "      <td>EUR/SEK</td>\n",
       "      <td>EUR/SGD</td>\n",
       "      <td>EUR/THB</td>\n",
       "      <td>EUR/TRY</td>\n",
       "      <td>EUR/TWD</td>\n",
       "      <td>EUR/USD</td>\n",
       "      <td>EUR/ZAR</td>\n",
       "      <td>GBP/AED</td>\n",
       "      <td>GBP/AUD</td>\n",
       "      <td>GBP/BRL</td>\n",
       "      <td>GBP/CAD</td>\n",
       "      <td>GBP/CHF</td>\n",
       "      <td>GBP/CZK</td>\n",
       "      <td>GBP/DKK</td>\n",
       "      <td>GBP/EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>GBP/HKD</td>\n",
       "      <td>GBP/HUF</td>\n",
       "      <td>GBP/INR</td>\n",
       "      <td>GBP/JPY</td>\n",
       "      <td>GBP/KRW</td>\n",
       "      <td>GBP/MXN</td>\n",
       "      <td>GBP/MYR</td>\n",
       "      <td>GBP/NOK</td>\n",
       "      <td>GBP/NZD</td>\n",
       "      <td>GBP/PLN</td>\n",
       "      <td>GBP/SEK</td>\n",
       "      <td>GBP/SGD</td>\n",
       "      <td>GBP/THB</td>\n",
       "      <td>GBP/TRY</td>\n",
       "      <td>GBP/USD</td>\n",
       "      <td>GBP/ZAR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>HKD/EUR</td>\n",
       "      <td>HKD/GBP</td>\n",
       "      <td>HKD/JPY</td>\n",
       "      <td>HKD/USD</td>\n",
       "      <td>HRK/EUR</td>\n",
       "      <td>HRK/USD</td>\n",
       "      <td>HUF/EUR</td>\n",
       "      <td>HUF/GBP</td>\n",
       "      <td>HUF/USD</td>\n",
       "      <td>ILS/EUR</td>\n",
       "      <td>ILS/USD</td>\n",
       "      <td>INR/EUR</td>\n",
       "      <td>INR/GBP</td>\n",
       "      <td>INR/USD</td>\n",
       "      <td>ISK/CHF</td>\n",
       "      <td>ISK/EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ISK/USD</td>\n",
       "      <td>JPY/AUD</td>\n",
       "      <td>JPY/BRL</td>\n",
       "      <td>JPY/CAD</td>\n",
       "      <td>JPY/CHF</td>\n",
       "      <td>JPY/DKK</td>\n",
       "      <td>JPY/EUR</td>\n",
       "      <td>JPY/GBP</td>\n",
       "      <td>JPY/HKD</td>\n",
       "      <td>JPY/MXN</td>\n",
       "      <td>JPY/NOK</td>\n",
       "      <td>JPY/NZD</td>\n",
       "      <td>JPY/SEK</td>\n",
       "      <td>JPY/SGD</td>\n",
       "      <td>JPY/TRY</td>\n",
       "      <td>JPY/USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>JPY/ZAR</td>\n",
       "      <td>KRW/EUR</td>\n",
       "      <td>KRW/GBP</td>\n",
       "      <td>KRW/USD</td>\n",
       "      <td>KWD/USD</td>\n",
       "      <td>MAD/EUR</td>\n",
       "      <td>MAD/USD</td>\n",
       "      <td>MXN/AUD</td>\n",
       "      <td>MXN/BRL</td>\n",
       "      <td>MXN/CAD</td>\n",
       "      <td>MXN/EUR</td>\n",
       "      <td>MXN/GBP</td>\n",
       "      <td>MXN/JPY</td>\n",
       "      <td>MXN/USD</td>\n",
       "      <td>MXN/ZAR</td>\n",
       "      <td>MYR/EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>MYR/GBP</td>\n",
       "      <td>MYR/USD</td>\n",
       "      <td>NOK/AUD</td>\n",
       "      <td>NOK/CAD</td>\n",
       "      <td>NOK/CHF</td>\n",
       "      <td>NOK/DKK</td>\n",
       "      <td>NOK/EUR</td>\n",
       "      <td>NOK/GBP</td>\n",
       "      <td>NOK/JPY</td>\n",
       "      <td>NOK/NZD</td>\n",
       "      <td>NOK/SEK</td>\n",
       "      <td>NOK/USD</td>\n",
       "      <td>NZD/AUD</td>\n",
       "      <td>NZD/CAD</td>\n",
       "      <td>NZD/CHF</td>\n",
       "      <td>NZD/DKK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NZD/EUR</td>\n",
       "      <td>NZD/GBP</td>\n",
       "      <td>NZD/JPY</td>\n",
       "      <td>NZD/NOK</td>\n",
       "      <td>NZD/SEK</td>\n",
       "      <td>NZD/TRY</td>\n",
       "      <td>NZD/USD</td>\n",
       "      <td>PEN/EUR</td>\n",
       "      <td>PEN/USD</td>\n",
       "      <td>PHP/EUR</td>\n",
       "      <td>PHP/USD</td>\n",
       "      <td>PLN/CHF</td>\n",
       "      <td>PLN/EUR</td>\n",
       "      <td>PLN/GBP</td>\n",
       "      <td>PLN/USD</td>\n",
       "      <td>RON/EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>RON/USD</td>\n",
       "      <td>RUB/AUD</td>\n",
       "      <td>RUB/EUR</td>\n",
       "      <td>RUB/USD</td>\n",
       "      <td>SEK/AUD</td>\n",
       "      <td>SEK/CAD</td>\n",
       "      <td>SEK/CHF</td>\n",
       "      <td>SEK/CZK</td>\n",
       "      <td>SEK/DKK</td>\n",
       "      <td>SEK/EUR</td>\n",
       "      <td>SEK/GBP</td>\n",
       "      <td>SEK/JPY</td>\n",
       "      <td>SEK/NOK</td>\n",
       "      <td>SEK/NZD</td>\n",
       "      <td>SEK/USD</td>\n",
       "      <td>SGD/AUD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>SGD/EUR</td>\n",
       "      <td>SGD/GBP</td>\n",
       "      <td>SGD/JPY</td>\n",
       "      <td>SGD/USD</td>\n",
       "      <td>THB/EUR</td>\n",
       "      <td>THB/GBP</td>\n",
       "      <td>THB/USD</td>\n",
       "      <td>TRY/CHF</td>\n",
       "      <td>TRY/EUR</td>\n",
       "      <td>TRY/GBP</td>\n",
       "      <td>TRY/JPY</td>\n",
       "      <td>TRY/NZD</td>\n",
       "      <td>TRY/USD</td>\n",
       "      <td>TRY/ZAR</td>\n",
       "      <td>TWD/EUR</td>\n",
       "      <td>TWD/USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>USD/AED</td>\n",
       "      <td>USD/ARS</td>\n",
       "      <td>USD/AUD</td>\n",
       "      <td>USD/BRL</td>\n",
       "      <td>USD/CAD</td>\n",
       "      <td>USD/CHF</td>\n",
       "      <td>USD/CLP</td>\n",
       "      <td>USD/CNY</td>\n",
       "      <td>USD/COP</td>\n",
       "      <td>USD/CZK</td>\n",
       "      <td>USD/DKK</td>\n",
       "      <td>USD/EUR</td>\n",
       "      <td>USD/GBP</td>\n",
       "      <td>USD/HKD</td>\n",
       "      <td>USD/HRK</td>\n",
       "      <td>USD/HUF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>USD/IDR</td>\n",
       "      <td>USD/ILS</td>\n",
       "      <td>USD/INR</td>\n",
       "      <td>USD/ISK</td>\n",
       "      <td>USD/JPY</td>\n",
       "      <td>USD/KRW</td>\n",
       "      <td>USD/KWD</td>\n",
       "      <td>USD/MAD</td>\n",
       "      <td>USD/MXN</td>\n",
       "      <td>USD/MYR</td>\n",
       "      <td>USD/NOK</td>\n",
       "      <td>USD/NZD</td>\n",
       "      <td>USD/PEN</td>\n",
       "      <td>USD/PHP</td>\n",
       "      <td>USD/PLN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>USD/RON</td>\n",
       "      <td>USD/RUB</td>\n",
       "      <td>USD/SEK</td>\n",
       "      <td>USD/SGD</td>\n",
       "      <td>USD/THB</td>\n",
       "      <td>USD/TRY</td>\n",
       "      <td>USD/TWD</td>\n",
       "      <td>USD/ZAR</td>\n",
       "      <td>ZAR/CHF</td>\n",
       "      <td>ZAR/EUR</td>\n",
       "      <td>ZAR/GBP</td>\n",
       "      <td>ZAR/JPY</td>\n",
       "      <td>ZAR/MXN</td>\n",
       "      <td>ZAR/TRY</td>\n",
       "      <td>ZAR/USD</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CurrencyPair CurrencyPair CurrencyPair CurrencyPair CurrencyPair  \\\n",
       "0       AED/EUR      AED/GBP      AED/USD      ARS/USD      AUD/BRL   \n",
       "1       AUD/SGD      AUD/USD      BRL/AUD      BRL/COP      BRL/EUR   \n",
       "2       CAD/NZD      CAD/SEK      CAD/USD      CHF/AUD      CHF/CAD   \n",
       "3       CHF/ZAR      CLP/EUR      CLP/USD      CNY/USD      COP/BRL   \n",
       "4       DKK/NOK      DKK/NZD      DKK/SEK      DKK/USD      EUR/AED   \n",
       "5       EUR/HUF      EUR/IDR      EUR/ILS      EUR/INR      EUR/ISK   \n",
       "6       EUR/RUB      EUR/SEK      EUR/SGD      EUR/THB      EUR/TRY   \n",
       "7       GBP/HKD      GBP/HUF      GBP/INR      GBP/JPY      GBP/KRW   \n",
       "8       HKD/EUR      HKD/GBP      HKD/JPY      HKD/USD      HRK/EUR   \n",
       "9       ISK/USD      JPY/AUD      JPY/BRL      JPY/CAD      JPY/CHF   \n",
       "10      JPY/ZAR      KRW/EUR      KRW/GBP      KRW/USD      KWD/USD   \n",
       "11      MYR/GBP      MYR/USD      NOK/AUD      NOK/CAD      NOK/CHF   \n",
       "12      NZD/EUR      NZD/GBP      NZD/JPY      NZD/NOK      NZD/SEK   \n",
       "13      RON/USD      RUB/AUD      RUB/EUR      RUB/USD      SEK/AUD   \n",
       "14      SGD/EUR      SGD/GBP      SGD/JPY      SGD/USD      THB/EUR   \n",
       "15      USD/AED      USD/ARS      USD/AUD      USD/BRL      USD/CAD   \n",
       "16      USD/IDR      USD/ILS      USD/INR      USD/ISK      USD/JPY   \n",
       "17      USD/RON      USD/RUB      USD/SEK      USD/SGD      USD/THB   \n",
       "\n",
       "   CurrencyPair CurrencyPair CurrencyPair CurrencyPair CurrencyPair  \\\n",
       "0       AUD/CAD      AUD/CHF      AUD/DKK      AUD/EUR      AUD/GBP   \n",
       "1       BRL/GBP      BRL/JPY      BRL/MXN      BRL/USD      CAD/AUD   \n",
       "2       CHF/DKK      CHF/EUR      CHF/GBP      CHF/ISK      CHF/JPY   \n",
       "3       COP/EUR      COP/USD      CZK/EUR      CZK/GBP      CZK/SEK   \n",
       "4       EUR/AUD      EUR/BRL      EUR/CAD      EUR/CHF      EUR/CLP   \n",
       "5       EUR/JPY      EUR/KRW      EUR/MAD      EUR/MXN      EUR/MYR   \n",
       "6       EUR/TWD      EUR/USD      EUR/ZAR      GBP/AED      GBP/AUD   \n",
       "7       GBP/MXN      GBP/MYR      GBP/NOK      GBP/NZD      GBP/PLN   \n",
       "8       HRK/USD      HUF/EUR      HUF/GBP      HUF/USD      ILS/EUR   \n",
       "9       JPY/DKK      JPY/EUR      JPY/GBP      JPY/HKD      JPY/MXN   \n",
       "10      MAD/EUR      MAD/USD      MXN/AUD      MXN/BRL      MXN/CAD   \n",
       "11      NOK/DKK      NOK/EUR      NOK/GBP      NOK/JPY      NOK/NZD   \n",
       "12      NZD/TRY      NZD/USD      PEN/EUR      PEN/USD      PHP/EUR   \n",
       "13      SEK/CAD      SEK/CHF      SEK/CZK      SEK/DKK      SEK/EUR   \n",
       "14      THB/GBP      THB/USD      TRY/CHF      TRY/EUR      TRY/GBP   \n",
       "15      USD/CHF      USD/CLP      USD/CNY      USD/COP      USD/CZK   \n",
       "16      USD/KRW      USD/KWD      USD/MAD      USD/MXN      USD/MYR   \n",
       "17      USD/TRY      USD/TWD      USD/ZAR      ZAR/CHF      ZAR/EUR   \n",
       "\n",
       "   CurrencyPair CurrencyPair CurrencyPair CurrencyPair CurrencyPair  \\\n",
       "0       AUD/JPY      AUD/MXN      AUD/NOK      AUD/NZD      AUD/RUB   \n",
       "1       CAD/CHF      CAD/EUR      CAD/GBP      CAD/JPY      CAD/MXN   \n",
       "2       CHF/NOK      CHF/NZD      CHF/PLN      CHF/SEK      CHF/TRY   \n",
       "3       CZK/USD      DKK/AUD      DKK/CHF      DKK/EUR      DKK/GBP   \n",
       "4       EUR/COP      EUR/CZK      EUR/DKK      EUR/GBP      EUR/HKD   \n",
       "5       EUR/NOK      EUR/NZD      EUR/PEN      EUR/PHP      EUR/PLN   \n",
       "6       GBP/BRL      GBP/CAD      GBP/CHF      GBP/CZK      GBP/DKK   \n",
       "7       GBP/SEK      GBP/SGD      GBP/THB      GBP/TRY      GBP/USD   \n",
       "8       ILS/USD      INR/EUR      INR/GBP      INR/USD      ISK/CHF   \n",
       "9       JPY/NOK      JPY/NZD      JPY/SEK      JPY/SGD      JPY/TRY   \n",
       "10      MXN/EUR      MXN/GBP      MXN/JPY      MXN/USD      MXN/ZAR   \n",
       "11      NOK/SEK      NOK/USD      NZD/AUD      NZD/CAD      NZD/CHF   \n",
       "12      PHP/USD      PLN/CHF      PLN/EUR      PLN/GBP      PLN/USD   \n",
       "13      SEK/GBP      SEK/JPY      SEK/NOK      SEK/NZD      SEK/USD   \n",
       "14      TRY/JPY      TRY/NZD      TRY/USD      TRY/ZAR      TWD/EUR   \n",
       "15      USD/DKK      USD/EUR      USD/GBP      USD/HKD      USD/HRK   \n",
       "16      USD/NOK      USD/NZD      USD/PEN      USD/PHP      USD/PLN   \n",
       "17      ZAR/GBP      ZAR/JPY      ZAR/MXN      ZAR/TRY      ZAR/USD   \n",
       "\n",
       "   CurrencyPair  \n",
       "0       AUD/SEK  \n",
       "1       CAD/NOK  \n",
       "2       CHF/USD  \n",
       "3       DKK/JPY  \n",
       "4       EUR/HRK  \n",
       "5       EUR/RON  \n",
       "6       GBP/EUR  \n",
       "7       GBP/ZAR  \n",
       "8       ISK/EUR  \n",
       "9       JPY/USD  \n",
       "10      MYR/EUR  \n",
       "11      NZD/DKK  \n",
       "12      RON/EUR  \n",
       "13      SGD/AUD  \n",
       "14      TWD/USD  \n",
       "15      USD/HUF  \n",
       "16         None  \n",
       "17         None  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_ccy_pairs = sorted(quotes_df[\"InstrumentID\"].unique())\n",
    "pd.DataFrame(np.array_split(unique_ccy_pairs, 18), columns = ([\"CurrencyPair\"] * 16))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get a time series of GBP/EUR for past 3 months\n",
    "\n",
    "You can use Python's plotting packages to plot a time series of quotes for a given currency pair between dates 27 December 2019 and 27 March 2020."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "currency_pair = \"GBP/EUR\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "quotes_df = get_quotes(**{\n",
    "    \"filter\": f\"QuoteId.EffectiveAt gte {start_date} and QuoteId.EffectiveAt lte {end_date} and QuoteId.QuoteSeriesId.InstrumentId eq '{currency_pair}'\", \n",
    "    \"fallback_csv\": \"data/fx_rates_3m.txt\"\n",
    "})        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "quotes_df[\"EffectiveAt\"] = pd.to_datetime(quotes_df[\"EffectiveAt\"].str[:10], format='%Y-%m-%d')\n",
    "quotes_df.set_index(\"EffectiveAt\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x14116d6d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "timeseries = quotes_df.plot(y=[\"Value\"], figsize=(12,9))\n",
    "timeseries.set_title(f\"Time series of {currency_pair} FX Spot rate\", fontsize=\"large\")\n",
    "timeseries.set_ylabel(f'{currency_pair} price', fontsize=\"large\")\n",
    "timeseries.set_xlabel('Date', fontsize=\"large\")\n",
    "timeseries.legend(prop={'size': 12})"
   ]
  }
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