V1/product/abor/Generate P&L with different accounting methods (FIFO and LIFO).ipynb

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   "cell_type": "code",
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     "data": {
      "text/plain": [
       "'Accounting methods\\n\\nGenerating P&L with different accounting methods (FIFO and LIFO)\\n\\nAttributes\\n----------\\ncocoon\\ntransaction configuration\\nderived portfolios\\naccounting methods\\n'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"Accounting methods\n",
    "\n",
    "Generating P&L with different accounting methods (FIFO and LIFO)\n",
    "\n",
    "Attributes\n",
    "----------\n",
    "cocoon\n",
    "transaction configuration\n",
    "derived portfolios\n",
    "accounting methods\n",
    "\"\"\"\n",
    "## Import Libraries & Connect to LUSID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import LUSID\n",
    "import lusid\n",
    "import lusidtools.cocoon.cocoon as cocoon_tools\n",
    "import lusid_sample_data as sd\n",
    "from lusidjam import RefreshingToken\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import pytz\n",
    "import printer as prettyprint\n",
    "from datetime import datetime\n",
    "import pylab\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Authenticate our user and create our API client\n",
    "secrets_path = os.getenv(\"FBN_SECRETS_PATH\")\n",
    "\n",
    "api_factory = lusid.utilities.ApiClientFactory(\n",
    "    token=RefreshingToken(),\n",
    "    api_secrets_filename = secrets_path,\n",
    "    app_name=\"LusidJupyterNotebook\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%pylab inline\n",
    "\n",
    "# Set style to fivethirtyeight to create clean and clear looking graphs\n",
    "plt.style.use('fivethirtyeight')\n",
    "\n",
    "# Define a dictionary containing default plotting configurations\n",
    "params = {\n",
    "    'legend.fontsize': 'small',\n",
    "    'figure.figsize': (15, 10),\n",
    "    'axes.labelsize': 'small',\n",
    "    'axes.titlesize':'medium',\n",
    "    'xtick.labelsize':'small',\n",
    "    'ytick.labelsize':'small'\n",
    "}\n",
    "\n",
    "pylab.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import and Create Instruments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>instrument_name</th>\n",
       "      <th>client_internal</th>\n",
       "      <th>currency</th>\n",
       "      <th>isin</th>\n",
       "      <th>figi</th>\n",
       "      <th>exchange_code</th>\n",
       "      <th>country_issue</th>\n",
       "      <th>ticker</th>\n",
       "      <th>market_sector</th>\n",
       "      <th>security_type</th>\n",
       "      <th>coupon</th>\n",
       "      <th>s&amp;p rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>imd_43535553</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB0007980591</td>\n",
       "      <td>BBG000C05BD1</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>BP/</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>imd_43534356</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GG00B4L84979</td>\n",
       "      <td>BBG000PN88Q7</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>BUR</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EKFDiagnostics_LondonStockEx_EKF</td>\n",
       "      <td>imd_34535355</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB0031509804</td>\n",
       "      <td>BBG000BVNBN3</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>EKF</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>imd_34534555</td>\n",
       "      <td>GBP</td>\n",
       "      <td>JE00B4T3BW64</td>\n",
       "      <td>BBG001MM1KV4</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>GLEN</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>JustEat_LondonStockEx_JE</td>\n",
       "      <td>imd_35436366</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00BKX5CN86</td>\n",
       "      <td>BBG0065YWM39</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>JE/</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Kingfisher_LondonStockEx_KGF</td>\n",
       "      <td>imd_34535552</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB0033195214</td>\n",
       "      <td>BBG000BKH1W6</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>KGF</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MicroFocus_LondonStockEx_MCRO</td>\n",
       "      <td>imd_34567338</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00BD8YWM01</td>\n",
       "      <td>BBG000G4KKD2</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>MCRO</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>RELXGroup_LondonStockEx_REL</td>\n",
       "      <td>imd_43532542</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00B2B0DG97</td>\n",
       "      <td>BBG000D03XD4</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>REL</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sage_LondonStockEx_SGE</td>\n",
       "      <td>imd_23536673</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00B8C3BL03</td>\n",
       "      <td>BBG000BN0PP3</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>SGE</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>TESCO_LondonStockEx_TSCO</td>\n",
       "      <td>imd_34634673</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB0008847096</td>\n",
       "      <td>BBG000BF46Y8</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>TSCO</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>UKGiltTreasury_2.0_2025</td>\n",
       "      <td>imd_34534536</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00BTHH2R79</td>\n",
       "      <td>BBG0088JSC32</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>UKT 2 09/07/25</td>\n",
       "      <td>govt</td>\n",
       "      <td>uk_gilt_stock</td>\n",
       "      <td>2.00</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>UKGiltTreasury_3.5_2045</td>\n",
       "      <td>imd_54234532</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00BN65R313</td>\n",
       "      <td>BBG006N6HZM7</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>UKT 3.5 01/22/45</td>\n",
       "      <td>govt</td>\n",
       "      <td>uk_gilt_stock</td>\n",
       "      <td>3.50</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>UKGiltTreasury_3.75_2021</td>\n",
       "      <td>imd_34643653</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00B4RMG977</td>\n",
       "      <td>BBG001KKJLR4</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>UKT 3.75 09/07/21</td>\n",
       "      <td>govt</td>\n",
       "      <td>uk_gilt_stock</td>\n",
       "      <td>3.75</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>UKGiltTreasury_4.5_2034</td>\n",
       "      <td>imd_34534534</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00B52WS153</td>\n",
       "      <td>BBG0000D14P3</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>UKT 4.5 09/07/34</td>\n",
       "      <td>govt</td>\n",
       "      <td>uk_gilt_stock</td>\n",
       "      <td>4.50</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>WPP_LondonStockEx_WPP</td>\n",
       "      <td>imd_34536734</td>\n",
       "      <td>GBP</td>\n",
       "      <td>JE00B8KF9B49</td>\n",
       "      <td>BBG000BF6B57</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>WPP</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Whitebread_LondonStockEx_WTB</td>\n",
       "      <td>imd_35349900</td>\n",
       "      <td>GBP</td>\n",
       "      <td>GB00B1KJJ408</td>\n",
       "      <td>BBG000BRVH05</td>\n",
       "      <td>LN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>WTB</td>\n",
       "      <td>equity</td>\n",
       "      <td>common_stock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>TESCO_6.13_2022</td>\n",
       "      <td>imd_34001121</td>\n",
       "      <td>GBP</td>\n",
       "      <td>XS0414345974</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>united_kingdom</td>\n",
       "      <td>NaN</td>\n",
       "      <td>corporate</td>\n",
       "      <td>corporate_bond</td>\n",
       "      <td>6.13</td>\n",
       "      <td>A-</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     instrument_name client_internal currency          isin  \\\n",
       "0                BP_LondonStockEx_BP    imd_43535553      GBP  GB0007980591   \n",
       "1   BurfordCapital_LondonStockEx_BUR    imd_43534356      GBP  GG00B4L84979   \n",
       "2   EKFDiagnostics_LondonStockEx_EKF    imd_34535355      GBP  GB0031509804   \n",
       "3        Glencore_LondonStockEx_GLEN    imd_34534555      GBP  JE00B4T3BW64   \n",
       "4           JustEat_LondonStockEx_JE    imd_35436366      GBP  GB00BKX5CN86   \n",
       "5       Kingfisher_LondonStockEx_KGF    imd_34535552      GBP  GB0033195214   \n",
       "6      MicroFocus_LondonStockEx_MCRO    imd_34567338      GBP  GB00BD8YWM01   \n",
       "7        RELXGroup_LondonStockEx_REL    imd_43532542      GBP  GB00B2B0DG97   \n",
       "8             Sage_LondonStockEx_SGE    imd_23536673      GBP  GB00B8C3BL03   \n",
       "9           TESCO_LondonStockEx_TSCO    imd_34634673      GBP  GB0008847096   \n",
       "10           UKGiltTreasury_2.0_2025    imd_34534536      GBP  GB00BTHH2R79   \n",
       "11           UKGiltTreasury_3.5_2045    imd_54234532      GBP  GB00BN65R313   \n",
       "12          UKGiltTreasury_3.75_2021    imd_34643653      GBP  GB00B4RMG977   \n",
       "13           UKGiltTreasury_4.5_2034    imd_34534534      GBP  GB00B52WS153   \n",
       "14             WPP_LondonStockEx_WPP    imd_34536734      GBP  JE00B8KF9B49   \n",
       "15      Whitebread_LondonStockEx_WTB    imd_35349900      GBP  GB00B1KJJ408   \n",
       "16                   TESCO_6.13_2022    imd_34001121      GBP  XS0414345974   \n",
       "\n",
       "            figi exchange_code   country_issue             ticker  \\\n",
       "0   BBG000C05BD1            LN  united_kingdom                BP/   \n",
       "1   BBG000PN88Q7            LN  united_kingdom                BUR   \n",
       "2   BBG000BVNBN3            LN  united_kingdom                EKF   \n",
       "3   BBG001MM1KV4            LN  united_kingdom               GLEN   \n",
       "4   BBG0065YWM39            LN  united_kingdom                JE/   \n",
       "5   BBG000BKH1W6            LN  united_kingdom                KGF   \n",
       "6   BBG000G4KKD2            LN  united_kingdom               MCRO   \n",
       "7   BBG000D03XD4            LN  united_kingdom                REL   \n",
       "8   BBG000BN0PP3            LN  united_kingdom                SGE   \n",
       "9   BBG000BF46Y8            LN  united_kingdom               TSCO   \n",
       "10  BBG0088JSC32            LN  united_kingdom     UKT 2 09/07/25   \n",
       "11  BBG006N6HZM7            LN  united_kingdom   UKT 3.5 01/22/45   \n",
       "12  BBG001KKJLR4            LN  united_kingdom  UKT 3.75 09/07/21   \n",
       "13  BBG0000D14P3            LN  united_kingdom   UKT 4.5 09/07/34   \n",
       "14  BBG000BF6B57            LN  united_kingdom                WPP   \n",
       "15  BBG000BRVH05            LN  united_kingdom                WTB   \n",
       "16           NaN           NaN  united_kingdom                NaN   \n",
       "\n",
       "   market_sector   security_type  coupon s&p rating  \n",
       "0         equity    common_stock     NaN        NaN  \n",
       "1         equity    common_stock     NaN        NaN  \n",
       "2         equity    common_stock     NaN        NaN  \n",
       "3         equity    common_stock     NaN        NaN  \n",
       "4         equity    common_stock     NaN        NaN  \n",
       "5         equity    common_stock     NaN        NaN  \n",
       "6         equity    common_stock     NaN        NaN  \n",
       "7         equity    common_stock     NaN        NaN  \n",
       "8         equity    common_stock     NaN        NaN  \n",
       "9         equity    common_stock     NaN        NaN  \n",
       "10          govt   uk_gilt_stock    2.00         AA  \n",
       "11          govt   uk_gilt_stock    3.50         AA  \n",
       "12          govt   uk_gilt_stock    3.75         AA  \n",
       "13          govt   uk_gilt_stock    4.50         AA  \n",
       "14        equity    common_stock     NaN        NaN  \n",
       "15        equity    common_stock     NaN        NaN  \n",
       "16     corporate  corporate_bond    6.13         A-  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_instrument_master = pd.read_csv(\"data/global-fund-UK-instrument-master.csv\")\n",
    "uk_instrument_master.head(n=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[91m\u001b[1mInstruments Successfully Upserted: \u001b[0m\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Instrument</th>\n",
       "      <th>ClientInternal ID</th>\n",
       "      <th>LUSID Instrument ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ClientInternal: imd_54234532</td>\n",
       "      <td>imd_54234532</td>\n",
       "      <td>LUID_0000MIPC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ClientInternal: imd_34634673</td>\n",
       "      <td>imd_34634673</td>\n",
       "      <td>LUID_0000NA4Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ClientInternal: imd_43532542</td>\n",
       "      <td>imd_43532542</td>\n",
       "      <td>LUID_0000MIOW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ClientInternal: imd_23536673</td>\n",
       "      <td>imd_23536673</td>\n",
       "      <td>LUID_0000MIP5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ClientInternal: imd_34535355</td>\n",
       "      <td>imd_34535355</td>\n",
       "      <td>LUID_0000MIPB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ClientInternal: imd_34535552</td>\n",
       "      <td>imd_34535552</td>\n",
       "      <td>LUID_0000MIOZ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ClientInternal: imd_35349900</td>\n",
       "      <td>imd_35349900</td>\n",
       "      <td>LUID_0000MIP2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ClientInternal: imd_34643653</td>\n",
       "      <td>imd_34643653</td>\n",
       "      <td>LUID_0000MIP6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ClientInternal: imd_43535553</td>\n",
       "      <td>imd_43535553</td>\n",
       "      <td>LUID_00044OXX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ClientInternal: imd_34534536</td>\n",
       "      <td>imd_34534536</td>\n",
       "      <td>LUID_0000MIP3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ClientInternal: imd_34536734</td>\n",
       "      <td>imd_34536734</td>\n",
       "      <td>LUID_0000MIPF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ClientInternal: imd_34534534</td>\n",
       "      <td>imd_34534534</td>\n",
       "      <td>LUID_0000MIPA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ClientInternal: imd_34534555</td>\n",
       "      <td>imd_34534555</td>\n",
       "      <td>LUID_0000MIPD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ClientInternal: imd_35436366</td>\n",
       "      <td>imd_35436366</td>\n",
       "      <td>LUID_0000MIP4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ClientInternal: imd_34567338</td>\n",
       "      <td>imd_34567338</td>\n",
       "      <td>LUID_0000MIP9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>ClientInternal: imd_43534356</td>\n",
       "      <td>imd_43534356</td>\n",
       "      <td>LUID_0000MIOY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ClientInternal: imd_34001121</td>\n",
       "      <td>imd_34001121</td>\n",
       "      <td>LUID_WNY0FCEW</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Instrument ClientInternal ID LUSID Instrument ID\n",
       "0   ClientInternal: imd_54234532      imd_54234532       LUID_0000MIPC\n",
       "1   ClientInternal: imd_34634673      imd_34634673       LUID_0000NA4Q\n",
       "2   ClientInternal: imd_43532542      imd_43532542       LUID_0000MIOW\n",
       "3   ClientInternal: imd_23536673      imd_23536673       LUID_0000MIP5\n",
       "4   ClientInternal: imd_34535355      imd_34535355       LUID_0000MIPB\n",
       "5   ClientInternal: imd_34535552      imd_34535552       LUID_0000MIOZ\n",
       "6   ClientInternal: imd_35349900      imd_35349900       LUID_0000MIP2\n",
       "7   ClientInternal: imd_34643653      imd_34643653       LUID_0000MIP6\n",
       "8   ClientInternal: imd_43535553      imd_43535553       LUID_00044OXX\n",
       "9   ClientInternal: imd_34534536      imd_34534536       LUID_0000MIP3\n",
       "10  ClientInternal: imd_34536734      imd_34536734       LUID_0000MIPF\n",
       "11  ClientInternal: imd_34534534      imd_34534534       LUID_0000MIPA\n",
       "12  ClientInternal: imd_34534555      imd_34534555       LUID_0000MIPD\n",
       "13  ClientInternal: imd_35436366      imd_35436366       LUID_0000MIP4\n",
       "14  ClientInternal: imd_34567338      imd_34567338       LUID_0000MIP9\n",
       "15  ClientInternal: imd_43534356      imd_43534356       LUID_0000MIOY\n",
       "16  ClientInternal: imd_34001121      imd_34001121       LUID_WNY0FCEW"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "instrument_properties_scope = 'InstrumentProperties005'\n",
    "\n",
    "instrument_identifier_mapping = {\n",
    "    \"Figi\": \"figi\",\n",
    "    \"Isin\": \"isin\",\n",
    "    \"ClientInternal\": \"client_internal\",\n",
    "    \"Ticker\": \"ticker\"\n",
    "}\n",
    "\n",
    "instrument_mapping_required = {\n",
    "    \"name\": \"instrument_name\"\n",
    "}\n",
    "\n",
    "instrument_mapping_optional = {}\n",
    "\n",
    "responses = cocoon_tools.load_from_data_frame(\n",
    "    api_factory=api_factory, \n",
    "    scope=instrument_properties_scope, \n",
    "    data_frame=uk_instrument_master, \n",
    "    mapping_required=instrument_mapping_required, \n",
    "    mapping_optional=instrument_mapping_optional, \n",
    "    file_type=\"instrument\", \n",
    "    identifier_mapping=instrument_identifier_mapping, \n",
    "    property_columns=[\n",
    "        \"exchange_code\", \n",
    "        \"country_issue\", \n",
    "        \"market_sector\",\n",
    "        \"security_type\",\n",
    "        \"coupon\",\n",
    "        \"s&p rating\",\n",
    "        \"currency\"])\n",
    "\n",
    "prettyprint.instrument_response(responses[\"instruments\"][\"success\"][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a Portfolio with \"FirstInFirstOut\" (FIFO) Accounting Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>code</th>\n",
       "      <th>display_name</th>\n",
       "      <th>description</th>\n",
       "      <th>base_currency</th>\n",
       "      <th>accounting_method</th>\n",
       "      <th>created</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>UK Equity Fund</td>\n",
       "      <td>UK Growth Fund Trading in UK Tradeable Equities</td>\n",
       "      <td>GBP</td>\n",
       "      <td>FirstInFirstOut</td>\n",
       "      <td>2010-01-01 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      code    display_name                                      description  \\\n",
       "0  UK12XC2  UK Equity Fund  UK Growth Fund Trading in UK Tradeable Equities   \n",
       "\n",
       "  base_currency accounting_method                   created  \n",
       "0           GBP   FirstInFirstOut 2010-01-01 00:00:00+00:00  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_code = \"UK12XC2\"\n",
    "\n",
    "portfolio = pd.DataFrame([\n",
    "    {\n",
    "        \"code\": portfolio_code,\n",
    "        \"display_name\": \"UK Equity Fund\",\n",
    "        \"description\": \"UK Growth Fund Trading in UK Tradeable Equities\",\n",
    "        \"base_currency\": \"GBP\",\n",
    "        \"accounting_method\": \"FirstInFirstOut\",\n",
    "        \"created\": datetime.datetime(year=2010, day=1, month=1, tzinfo=pytz.UTC)\n",
    "    }\n",
    "])\n",
    "\n",
    "portfolio.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mPortfolio Created\u001b[0m\n",
      "\u001b[1mScope: \u001b[0mAccountingDemoScope\n",
      "\u001b[1mCode: \u001b[0mUK12XC2\n",
      "\u001b[1mPortfolio Effective From: \u001b[0m2010-01-01 00:00:00+00:00\n",
      "\u001b[1mPortfolio Created On: \u001b[0m2023-10-02 15:43:37.355909+00:00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "trading_scope = \"AccountingDemoScope\"\n",
    "\n",
    "portfolio_mapping_required = {\n",
    "    \"code\": \"code\",\n",
    "    \"display_name\": \"display_name\",\n",
    "    \"base_currency\": \"base_currency\",\n",
    "    \"accounting_method\": \"accounting_method\"\n",
    "}\n",
    "\n",
    "portfolio_mapping_optional = {\n",
    "    \"description\": \"description\",\n",
    "    \"created\": \"created\"\n",
    "}\n",
    "\n",
    "responses = cocoon_tools.load_from_data_frame(\n",
    "    api_factory=api_factory, \n",
    "    scope=trading_scope, \n",
    "    data_frame=portfolio, \n",
    "    mapping_required=portfolio_mapping_required, \n",
    "    mapping_optional=portfolio_mapping_optional, \n",
    "    file_type=\"portfolio\")\n",
    "\n",
    "prettyprint.portfolio_response(responses[\"portfolios\"][\"success\"][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import and Create Transactions for September 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>desc</th>\n",
       "      <th>qty</th>\n",
       "      <th>unit_price</th>\n",
       "      <th>trade_currency</th>\n",
       "      <th>exposure</th>\n",
       "      <th>total_trade_amount</th>\n",
       "      <th>figi_identifier</th>\n",
       "      <th>trade_datetime</th>\n",
       "      <th>settlement_datetime</th>\n",
       "      <th>isin_identifier</th>\n",
       "      <th>executor</th>\n",
       "      <th>asset_name</th>\n",
       "      <th>fund_code</th>\n",
       "      <th>t_id</th>\n",
       "      <th>internal_identifier</th>\n",
       "      <th>cash_transactions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FundsIn</td>\n",
       "      <td>900000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>GBP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95000000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-09-01T09:31:22.664000+00:00</td>\n",
       "      <td>2019-09-01T09:31:22.664000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>GBP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>kjk99898990z88908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Buy</td>\n",
       "      <td>729176</td>\n",
       "      <td>5.92</td>\n",
       "      <td>GBP</td>\n",
       "      <td>BP</td>\n",
       "      <td>3996759.49</td>\n",
       "      <td>BBG000C05BD1</td>\n",
       "      <td>2019-09-03T14:42:12.435000+00:00</td>\n",
       "      <td>2019-09-05T14:42:12.435000+00:00</td>\n",
       "      <td>GB0007980591</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>435opkplk03sfsf33</td>\n",
       "      <td>imd_43535553</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Buy</td>\n",
       "      <td>1762711</td>\n",
       "      <td>8.85</td>\n",
       "      <td>GBP</td>\n",
       "      <td>BurfordCapital</td>\n",
       "      <td>15599992.35</td>\n",
       "      <td>BBG000PN88Q7</td>\n",
       "      <td>2019-09-05T15:12:44.090000+00:00</td>\n",
       "      <td>2019-09-07T15:12:44.090000+00:00</td>\n",
       "      <td>GG00B4L84979</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>dsfsdlkjs933234211</td>\n",
       "      <td>imd_43534356</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Buy</td>\n",
       "      <td>14087318</td>\n",
       "      <td>2.40</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Glencore</td>\n",
       "      <td>33879999.79</td>\n",
       "      <td>BBG001MM1KV4</td>\n",
       "      <td>2019-09-10T09:58:43.112000+00:00</td>\n",
       "      <td>2019-09-11T09:58:43.112000+00:00</td>\n",
       "      <td>JE00B4T3BW64</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>dfklsjd90232350239</td>\n",
       "      <td>imd_34534555</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Buy</td>\n",
       "      <td>276624</td>\n",
       "      <td>7.42</td>\n",
       "      <td>GBP</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>2051996.83</td>\n",
       "      <td>BBG0065YWM39</td>\n",
       "      <td>2019-09-10T13:58:57.113000+00:00</td>\n",
       "      <td>2019-09-11T13:58:57.113000+00:00</td>\n",
       "      <td>GB00BKX5CN86</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>kj0llk90f0909201141</td>\n",
       "      <td>imd_35436366</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Buy</td>\n",
       "      <td>500000</td>\n",
       "      <td>10.50</td>\n",
       "      <td>GBP</td>\n",
       "      <td>MicroFocus</td>\n",
       "      <td>5249000.00</td>\n",
       "      <td>BBG000G4KKD2</td>\n",
       "      <td>2019-09-12T15:32:57.113000+00:00</td>\n",
       "      <td>2019-09-14T15:32:57.113000+00:00</td>\n",
       "      <td>GB00BD8YWM01</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>MicroFocus_LondonStockEx_MCRO</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>sadjkas934234sadfs</td>\n",
       "      <td>imd_34567338</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Buy</td>\n",
       "      <td>543176</td>\n",
       "      <td>5.10</td>\n",
       "      <td>GBP</td>\n",
       "      <td>BP</td>\n",
       "      <td>2829240.83</td>\n",
       "      <td>BBG000C05BD1</td>\n",
       "      <td>2019-09-13T16:29:18.123000+00:00</td>\n",
       "      <td>2019-09-15T16:29:18.123000+00:00</td>\n",
       "      <td>GB0007980591</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>fas2340090sd9f0s23</td>\n",
       "      <td>imd_43535553</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Buy</td>\n",
       "      <td>853000</td>\n",
       "      <td>8.83</td>\n",
       "      <td>GBP</td>\n",
       "      <td>BurfordCapital</td>\n",
       "      <td>7531990.00</td>\n",
       "      <td>BBG000PN88Q7</td>\n",
       "      <td>2019-09-15T10:58:57.113000+00:00</td>\n",
       "      <td>2019-09-17T10:58:57.113000+00:00</td>\n",
       "      <td>GG00B4L84979</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>dflkjsdflk932432rsd</td>\n",
       "      <td>imd_43534356</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Buy</td>\n",
       "      <td>9349219</td>\n",
       "      <td>2.41</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Glencore</td>\n",
       "      <td>22503570.13</td>\n",
       "      <td>BBG001MM1KV4</td>\n",
       "      <td>2019-09-16T09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-18T09:32:38.113000+00:00</td>\n",
       "      <td>JE00B4T3BW64</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>sdfdslkf234092304s</td>\n",
       "      <td>imd_34534555</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sell</td>\n",
       "      <td>854176</td>\n",
       "      <td>5.32</td>\n",
       "      <td>GBP</td>\n",
       "      <td>BP</td>\n",
       "      <td>4548060.11</td>\n",
       "      <td>BBG000C05BD1</td>\n",
       "      <td>2019-09-19T09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21T09:32:38.113000+00:00</td>\n",
       "      <td>GB0007980591</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>2354lafjaso3432502</td>\n",
       "      <td>imd_43535553</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sell</td>\n",
       "      <td>153000</td>\n",
       "      <td>7.33</td>\n",
       "      <td>GBP</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>1121459.40</td>\n",
       "      <td>BBG0065YWM39</td>\n",
       "      <td>2019-09-19T09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21T09:32:38.113000+00:00</td>\n",
       "      <td>GB00BKX5CN86</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>sdlfksdlfk23409235</td>\n",
       "      <td>imd_35436366</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       desc        qty  unit_price trade_currency        exposure  \\\n",
       "0   FundsIn  900000000        1.00            GBP             NaN   \n",
       "1       Buy     729176        5.92            GBP              BP   \n",
       "2       Buy    1762711        8.85            GBP  BurfordCapital   \n",
       "3       Buy   14087318        2.40            GBP        Glencore   \n",
       "4       Buy     276624        7.42            GBP         JustEat   \n",
       "5       Buy     500000       10.50            GBP      MicroFocus   \n",
       "6       Buy     543176        5.10            GBP              BP   \n",
       "7       Buy     853000        8.83            GBP  BurfordCapital   \n",
       "8       Buy    9349219        2.41            GBP        Glencore   \n",
       "9      Sell     854176        5.32            GBP              BP   \n",
       "10     Sell     153000        7.33            GBP         JustEat   \n",
       "\n",
       "    total_trade_amount figi_identifier                    trade_datetime  \\\n",
       "0          95000000.00             NaN  2019-09-01T09:31:22.664000+00:00   \n",
       "1           3996759.49    BBG000C05BD1  2019-09-03T14:42:12.435000+00:00   \n",
       "2          15599992.35    BBG000PN88Q7  2019-09-05T15:12:44.090000+00:00   \n",
       "3          33879999.79    BBG001MM1KV4  2019-09-10T09:58:43.112000+00:00   \n",
       "4           2051996.83    BBG0065YWM39  2019-09-10T13:58:57.113000+00:00   \n",
       "5           5249000.00    BBG000G4KKD2  2019-09-12T15:32:57.113000+00:00   \n",
       "6           2829240.83    BBG000C05BD1  2019-09-13T16:29:18.123000+00:00   \n",
       "7           7531990.00    BBG000PN88Q7  2019-09-15T10:58:57.113000+00:00   \n",
       "8          22503570.13    BBG001MM1KV4  2019-09-16T09:32:38.113000+00:00   \n",
       "9           4548060.11    BBG000C05BD1  2019-09-19T09:32:38.113000+00:00   \n",
       "10          1121459.40    BBG0065YWM39  2019-09-19T09:32:38.113000+00:00   \n",
       "\n",
       "                 settlement_datetime isin_identifier  executor  \\\n",
       "0   2019-09-01T09:31:22.664000+00:00             NaN  jx112421   \n",
       "1   2019-09-05T14:42:12.435000+00:00    GB0007980591  jx112421   \n",
       "2   2019-09-07T15:12:44.090000+00:00    GG00B4L84979  jx112421   \n",
       "3   2019-09-11T09:58:43.112000+00:00    JE00B4T3BW64  jx112421   \n",
       "4   2019-09-11T13:58:57.113000+00:00    GB00BKX5CN86  jp392431   \n",
       "5   2019-09-14T15:32:57.113000+00:00    GB00BD8YWM01  jx112421   \n",
       "6   2019-09-15T16:29:18.123000+00:00    GB0007980591  jp392431   \n",
       "7   2019-09-17T10:58:57.113000+00:00    GG00B4L84979  jx112421   \n",
       "8   2019-09-18T09:32:38.113000+00:00    JE00B4T3BW64  jp392431   \n",
       "9   2019-09-21T09:32:38.113000+00:00    GB0007980591  jp392431   \n",
       "10  2019-09-21T09:32:38.113000+00:00    GB00BKX5CN86  jp392431   \n",
       "\n",
       "                          asset_name fund_code                 t_id  \\\n",
       "0                                GBP   UK12XC2    kjk99898990z88908   \n",
       "1                BP_LondonStockEx_BP   UK12XC2    435opkplk03sfsf33   \n",
       "2   BurfordCapital_LondonStockEx_BUR   UK12XC2   dsfsdlkjs933234211   \n",
       "3        Glencore_LondonStockEx_GLEN   UK12XC2   dfklsjd90232350239   \n",
       "4            JustEat_LondonStockEx_J   UK12XC2  kj0llk90f0909201141   \n",
       "5      MicroFocus_LondonStockEx_MCRO   UK12XC2   sadjkas934234sadfs   \n",
       "6                BP_LondonStockEx_BP   UK12XC2   fas2340090sd9f0s23   \n",
       "7   BurfordCapital_LondonStockEx_BUR   UK12XC2  dflkjsdflk932432rsd   \n",
       "8        Glencore_LondonStockEx_GLEN   UK12XC2   sdfdslkf234092304s   \n",
       "9                BP_LondonStockEx_BP   UK12XC2   2354lafjaso3432502   \n",
       "10           JustEat_LondonStockEx_J   UK12XC2   sdlfksdlfk23409235   \n",
       "\n",
       "   internal_identifier cash_transactions  \n",
       "0                  NaN               GBP  \n",
       "1         imd_43535553               NaN  \n",
       "2         imd_43534356               NaN  \n",
       "3         imd_34534555               NaN  \n",
       "4         imd_35436366               NaN  \n",
       "5         imd_34567338               NaN  \n",
       "6         imd_43535553               NaN  \n",
       "7         imd_43534356               NaN  \n",
       "8         imd_34534555               NaN  \n",
       "9         imd_43535553               NaN  \n",
       "10        imd_35436366               NaN  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions = pd.read_csv(\"data/accounting-demo-sample-transactions.csv\")\n",
    "transactions[\"cash_transactions\"] = np.where(transactions[\"desc\"] == \"FundsIn\", transactions[\"trade_currency\"], np.NaN) \n",
    "transactions.head(n=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HD9WpU0dhYWFq1qyZRowYoT179lzoLSi35s2ba+nSpTKZTMrMzDSeyCksJSVF77zzjoYPH66OHTuqTp06Cg8PV/PmzTVq1Ch99913Rfb5888/FRwcbBxvx44dxs/F8bVixYpi93vyySd13XXXqUaNGoqIiFC7du30xBNPFFlDBQAAAACudBRHAAAAUOH++OMPderUSQsWLNCpU6fk4eE8m+uHH36oUaNG6f3339evv/6q/Px8eXh4KC4uTp988okGDhyoadOmlXj8zZs3q3Pnzlq9erXOnDkjT09PxcfHa/HixerSpYv+/PPPUtu3f/9+XXfddXr22Wf13XffKT09Xd7e3jp16pTWrl2rXr16ac6cORVyL0rTpk0b9ezZU5K0fv16ZWdnO73/v//9T+PHj9e6det08OBB4/WTJ09qzZo16tmzpxYuXOi0j7u7u8LCwuTv7y9J8vT0VFhYmNPXuevCrFq1Su3bt9fChQv1+++/y2KxSJIOHz6sRYsWqWPHjvryyy8r/PoBAAAA4HKhOAIAAIAK99RTTykoKEjr169XbGysYmJitHfvXuP94OBgjRs3Tp999plOnTqlEydOKDY2Vr///rumTJkiT09Pvfbaa/rkk0+KHPvUqVMaMWKEcnNz1axZM23ZskUnT55UbGys1qxZI3d3d02dOrXEtsXFxemuu+7SqVOndPvtt2vr1q2Ki4tTTEyMDh8+rEmTJsnd3V3PPfecPv7440tyfwpzFEdyc3OLPAkSERGhJ554Qlu3btXp06d1/PhxxcXFad++fXrooYckSVOnTtVPP/1k7FOzZk0dOnRIDz/8sCSpffv2OnTokNPXnXfeaWz/1Vdf6aGHHpLVatWECRP0008/KS4uTrGxsfruu+/Uv39/paena/jw4TxBAgAAAOCqQXEEAAAAFc7NzU3r1q1T165d5eZW0OWsX7++8X6fPn00Y8YMXXfddfLz8zNer169up544glNnz5dkrRo0aIix54zZ47S0tJUpUoVrVu3Tm3atDHO2b17d61evVpZWVkltu35559XQkKCBg4cqGXLlqlly5by9PSUJFWrVk1Tp07Vs88+K0maNWvWRd6JsjVv3tz49/Hjx53eGz58uKZMmaKWLVvKy8tLkmQymVSnTh3NmjVLo0aNktVq1ZIlSy7o3DabTY8//rhsNpv+85//6Nlnn1VUVJRMJpNMJpMaNGigt99+W7feeqvS0tI0f/78C75OAAAAAKhMKI4AAACgwg0aNEg1atS44P0dT1N89913slqtxut2u11r166VJI0YMULVqlUrsm/Tpk3Vr1+/Yo+bk5OjNWvWSJImTJhQ4vnvueceSdIvv/xS7jVMLlRISIjx7+Tk5PPa13Gfdu/efUHn3rFjh44eParQ0FANHTq0xO3+8Y9/SBJTawEAAAC4aniUvQkAAABwfjp06FDmNmfOnNGSJUv01Vdf6ciRI0pLS3MqhEgFC7enpKQoNDRUUsGi4Y4CQufOnUs8dpcuXYwiSGH79u1TTk6OJDlNLVWamJgYhYWFlWvbS+H48eNasmSJtm/frj/++EMZGRmy2WxO28TGxl7Qsb/99ltJUlpamho3blzidnl5eZLEtFoAAAAArhoURwAAAFDhinuio7A9e/Zo4MCBSk1NNV4LCAiQr6+vTCaTrFarzp49K0nKzMw0iiMJCQnG9pGRkSUev6T34uLijH+X94mQ0qboqgiFnxYp/BSJJH300UcaNWqUcnNzjdfMZrO8vb1lMpmUl5enlJQUZWZmXtC5HfcjPz+/XPfj3AXjAQAAAOBKRXEEAAAAFc6xzkhxLBaLRo4cqdTUVEVHR2v69Om67rrrFBgYaGzzxx9/qFWrVpIKptKqKIWfTImLi5OPj0+FHftC/fLLL8a/69ata/w7KSlJY8eOVW5urrp06aLJkyerTZs28vX1NbbZtm1biVOIlYfjfrRt21abN2++4OMAAAAAwJWG4ggAAAD+Vnv27FFMTIzc3d31/vvvF/uUR3x8fLH7Fn4iJTY2Vg0aNCh2u5KmmSo8PVZMTEyJ+/+dPv/8c0mSt7e32rVr5/R6WlqagoOD9d577zktXO9Q0n0qL8f9YLosAAAAAK6GBdkBAADwtzp16pQkqWrVqiVOf7V169ZiX4+KijKmntq+fXuJ5yjpvdatW8vLy0uS9Nlnn5W3yZfM999/bxRH7rzzTqcnWRz3qUGDBsUWRqSS75P019M7pT15c91110kqKLL8+OOP59V2AAAAALiSURwBAADA38psNksqWPOjuHUuTp06pUWLFhW7r8lk0h133CFJeuutt4x1SQr7/ffftX79+mL39/f314ABAyRJ8+bNK/OJicLrgVS0X3/9VcOGDZPdbpe/v78mT57s9L7jPh05csRYRL6w/fv3F7vovINjmrLC67qcq3PnzqpXr54k6amnnjIWXi/JpbwfAAAAAPB3ojgCAACAv9V1110nf39/2e12DR8+XEeOHJFUsP7Fli1bdNttt8lkMpW4/8SJExUYGKizZ8+qf//+xhMPdrtdX375pQYMGOC0Lse5pk+froiICJ09e1Y9e/bUe++9p/T0dOP9xMRErV+/XoMHD9bIkSMr6KoLpKena/v27XrkkUd088036+TJk/Ly8tLbb7/ttN6IJN10001yc3NTcnKyHnjgAWOqsLy8PH344Ye68847FRAQUOK5mjZtKqmgWPTtt98Wu42Hh4fmzp0rDw8P7dq1S71799a2bduUn59vbHP8+HG9+eabuvHGG7VkyZKLvQUAAAAAUCmYUlJSKm6FSwAAAFzVZs6cqdmzZ0uSUlJSirwfHBwsSfroo4/UuXPnEo/z5ptv6tFHHzW+DwgIkMViUU5OjkJDQ/Xaa6/pnnvukST99NNPioqKctp/06ZNGjp0qHJzcyUVPCVhsViUnZ2t6tWra9q0aXr44YdLbOfBgwc1ePBgozDj5uamoKAg5eXlKTMz09iuW7duWrduXek35RzR0dGKiYmRj4+P8fSH3W5XZmamsrKynLbt0KGD5s6daxQyzvXMM89o3rx5xvdms1nZ2dnKz89XVFSUpk2bpgceeKDY67RYLLr++ut1+PBhSQU/G8fTJM8//7zTQu4ff/yxRo8ebRSJPD09FRgYqMzMTOMeS9K0adP0+OOPn9f9AAAAAIDKiAXZAQAA8LcbMWKEatasqVdeeUX79u2TxWJRRESEevTooYkTJ5Y5vVOvXr20bds2vfTSS/r666+Vlpam8PBw9erVS5MmTdLBgwdL3b9Ro0basWOHVq5cqQ0bNujnn39WcnKyvLy8VK9ePbVo0UI33nijUwHhfOXk5BjTYXl4eCggIEBhYWFq1KiRWrRoob59+yo6OrrUYzzzzDNq3LixFi9erN9++00Wi0X16tXTbbfdpvHjx2v//v0l7uvh4aH169dr1qxZ2rZtm06fPm0UUDIyMpy2ve2229ShQwctWbJEmzdv1tGjR5Wamip/f381aNBArVu3Vs+ePdWzZ88Lvh8AAAAAUJnw5AgAAAAAAAAAAHAprDkCAAAAAAAAAABcCsURAAAAAAAAAADgUiiOAAAAAAAAAAAAl0JxBAAAAAAAAAAAuBSKIwAAAAAAAAAAwKVQHAEAAAAAAAAAAC6F4ggAAAAAAAAAAHApFEcAAAAAAAAAAIBLoTgCAAAAAAAAAABcCsURAAAAAAAAAADgUiiOAAAAAAAAAAAAl0JxBAAAAAAAAAAAuBSKIwAAAAAAAAAAwKVQHAEAAAAAAAAAAC7l/wCcrfwGGqWPIgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [datetime.date.fromisoformat(date.split(\"T\")[0]) for date in transactions[\"trade_datetime\"].values[1:]]\n",
    "y = transactions[\"unit_price\"].values[1:]\n",
    "labels = [\n",
    "    \"-\".join([\n",
    "        transactions[\"desc\"].values[i], \n",
    "        transactions[\"asset_name\"].values[i]\n",
    "    ]) for i in range(1, len(transactions[\"desc\"].values))]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "for x, y, label in zip(x,y,labels):\n",
    "    if \"Buy\" in label:\n",
    "        colour = \"blue\"\n",
    "    else:\n",
    "        colour = \"red\"\n",
    "\n",
    "    ax.plot_date(x=x, y=y, c=colour)\n",
    "    ax.annotate(label, (x, y), rotation=-5)\n",
    "\n",
    "plt.xlabel('Trade Date', fontsize=18)\n",
    "plt.ylabel('Unit Price (£)', fontsize=18)\n",
    "fig.suptitle('Transactions for September', fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mTransactions Successfully Upserted into Portfolio\u001b[0m\n",
      "\u001b[1mScope: \u001b[0mAccountingDemoScope\n",
      "\u001b[1mCode: \u001b[0mUK12XC2\n",
      "\u001b[1mTransactions Effective From: \u001b[0m2010-01-01 00:00:00+00:00\n",
      "\u001b[1mTransactions Created On: \u001b[0m2019-11-18 11:46:36.561221+00:00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "transaction_identifier_mapping = {\n",
    "    \"Figi\": \"figi_identifier\",\n",
    "    \"Isin\": \"isin_identifier\",\n",
    "    \"ClientInternal\": \"internal_identifier\",\n",
    "    \"Currency\": \"cash_transactions\"\n",
    "}\n",
    "\n",
    "transaction_mapping_required = {\n",
    "    \"code\": \"fund_code\",\n",
    "    \"transaction_id\": \"t_id\",\n",
    "    \"type\": \"desc\",\n",
    "    \"transaction_date\": \"trade_datetime\",\n",
    "    \"settlement_date\": \"settlement_datetime\",\n",
    "    \"units\": \"qty\",\n",
    "    \"transaction_price.price\": \"unit_price\",\n",
    "    \"transaction_price.type\": \"$Price\",\n",
    "    \"total_consideration.amount\": \"total_trade_amount\",\n",
    "    \"total_consideration.currency\": \"trade_currency\"\n",
    "}\n",
    "\n",
    "transaction_mapping_optional = {\n",
    "    \"exchange_rate\": \"$1\",\n",
    "    \"transaction_currency\": \"trade_currency\"\n",
    "}\n",
    "\n",
    "responses = cocoon_tools.load_from_data_frame(\n",
    "    api_factory=api_factory, \n",
    "    scope=trading_scope, \n",
    "    data_frame=transactions, \n",
    "    mapping_required=transaction_mapping_required, \n",
    "    mapping_optional=transaction_mapping_optional, \n",
    "    file_type=\"transactions\", \n",
    "    identifier_mapping=transaction_identifier_mapping, \n",
    "    property_columns=[\n",
    "        \"exposure\",\n",
    "        \"executor\",\n",
    "        \"asset_name\"\n",
    "    ])\n",
    "\n",
    "prettyprint.transactions_response(\n",
    "    responses[\"transactions\"][\"success\"][0], \n",
    "    trading_scope, \n",
    "    responses[\"transactions\"][\"success\"][0].href.split(\"/\")[7])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## List Transaction Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[4mTransaction Configuration source: default\u001b[0m\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Type Aliases\u001b[0m\n",
      "\u001b[1mTransaction Type: \u001b[0m\u001b[91mBuy\u001b[0m\n",
      "\u001b[1mAlias Description: \u001b[0mPurchase\n",
      "\u001b[1mTransaction Class: \u001b[0mBasic\n",
      "\u001b[1mTransaction Roles: \u001b[0mLongLonger\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Movements\u001b[0m\n",
      "\u001b[1mMovement Types: \u001b[0mStockMovement\n",
      "\u001b[1mSide: \u001b[0mSide1\n",
      "\u001b[1mDirection: \u001b[0m1\n",
      "\u001b[1mMovement Types: \u001b[0mCashCommitment\n",
      "\u001b[1mSide: \u001b[0mSide2\n",
      "\u001b[1mDirection: \u001b[0m-1\n",
      "\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Type Aliases\u001b[0m\n",
      "\u001b[1mTransaction Type: \u001b[0m\u001b[91mSell\u001b[0m\n",
      "\u001b[1mAlias Description: \u001b[0mSale\n",
      "\u001b[1mTransaction Class: \u001b[0mBasic\n",
      "\u001b[1mTransaction Roles: \u001b[0mLongShorter\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Movements\u001b[0m\n",
      "\u001b[1mMovement Types: \u001b[0mStockMovement\n",
      "\u001b[1mSide: \u001b[0mSide1\n",
      "\u001b[1mDirection: \u001b[0m-1\n",
      "\u001b[1mMovement Types: \u001b[0mCashCommitment\n",
      "\u001b[1mSide: \u001b[0mSide2\n",
      "\u001b[1mDirection: \u001b[0m1\n",
      "\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Type Aliases\u001b[0m\n",
      "\u001b[1mTransaction Type: \u001b[0m\u001b[91mFundsIn\u001b[0m\n",
      "\u001b[1mAlias Description: \u001b[0mDeposit New Funds\n",
      "\u001b[1mTransaction Class: \u001b[0mCashTransfers\n",
      "\u001b[1mTransaction Roles: \u001b[0mLonger\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Movements\u001b[0m\n",
      "\u001b[1mMovement Types: \u001b[0mCashReceivable\n",
      "\u001b[1mSide: \u001b[0mSide1\n",
      "\u001b[1mDirection: \u001b[0m1\n",
      "\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[4mTransaction Configuration source: US_SimcorpDimension\u001b[0m\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Type Aliases\u001b[0m\n",
      "\u001b[1mTransaction Type: \u001b[0m\u001b[91mFundsIn\u001b[0m\n",
      "\u001b[1mAlias Description: \u001b[0mFundsIn\n",
      "\u001b[1mTransaction Class: \u001b[0mFundsIn\n",
      "\u001b[1mTransaction Roles: \u001b[0mNone\n",
      "\n",
      "\n",
      "\u001b[1m\u001b[91mTransaction Movements\u001b[0m\n",
      "\u001b[1mMovement Types: \u001b[0mCashCommitment\n",
      "\u001b[1mSide: \u001b[0mSide2\n",
      "\u001b[1mDirection: \u001b[0m1\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Call LUSID to get your transaction type configuration\n",
    "response = api_factory.build(lusid.api.TransactionConfigurationApi).list_transaction_types()\n",
    "# Pretty print the configuration\n",
    "prettyprint.transaction_type_response(response, filters=[\"Buy\", \"Sell\", \"FundsIn\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate Holdings by Tax Lot At 30th September 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>local_vars_configuration</th>\n",
       "      <th>_instrument_scope</th>\n",
       "      <th>_instrument_uid</th>\n",
       "      <th>_holding_type</th>\n",
       "      <th>_units</th>\n",
       "      <th>_settled_units</th>\n",
       "      <th>_transaction</th>\n",
       "      <th>_currency</th>\n",
       "      <th>_holding_type_name</th>\n",
       "      <th>discriminator</th>\n",
       "      <th>...</th>\n",
       "      <th>cost.currency</th>\n",
       "      <th>cost_portfolio_ccy.amount</th>\n",
       "      <th>Instrument/default/Name</th>\n",
       "      <th>Instrument/default/Figi</th>\n",
       "      <th>Holding/default/SourcePortfolioId</th>\n",
       "      <th>Holding/default/SourcePortfolioScope</th>\n",
       "      <th>Holding/default/TaxlotPurchaseDate</th>\n",
       "      <th>Holding/default/TaxlotPurchasePrice</th>\n",
       "      <th>Holding/default/TaxlotId</th>\n",
       "      <th>Instrument/InstrumentProperties005/security_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>CCY_GBP</td>\n",
       "      <td>B</td>\n",
       "      <td>812026970.09</td>\n",
       "      <td>812026970.09</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Balance</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>812026970.09</td>\n",
       "      <td>GBP</td>\n",
       "      <td>some-figi-code12312</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</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>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_00044OXX</td>\n",
       "      <td>P</td>\n",
       "      <td>418176.00</td>\n",
       "      <td>418176.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2178153.33</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>BBG000C05BD1</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-13T16:29:18.1230000+00:00</td>\n",
       "      <td>5.10</td>\n",
       "      <td>fas2340090sd9f0s23</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_0000MIOY</td>\n",
       "      <td>P</td>\n",
       "      <td>1762711.00</td>\n",
       "      <td>1762711.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>15599992.35</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>BBG000PN88Q7</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-05T15:12:44.0900000+00:00</td>\n",
       "      <td>8.85</td>\n",
       "      <td>dsfsdlkjs933234211</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_0000MIOY</td>\n",
       "      <td>P</td>\n",
       "      <td>853000.00</td>\n",
       "      <td>853000.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>7531990.00</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>BBG000PN88Q7</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-15T10:58:57.1130000+00:00</td>\n",
       "      <td>8.83</td>\n",
       "      <td>dflkjsdflk932432rsd</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_0000MIPD</td>\n",
       "      <td>P</td>\n",
       "      <td>14087318.00</td>\n",
       "      <td>14087318.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>33879999.79</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>BBG001MM1KV4</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-10T09:58:43.1120000+00:00</td>\n",
       "      <td>2.40</td>\n",
       "      <td>dfklsjd90232350239</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_0000MIPD</td>\n",
       "      <td>P</td>\n",
       "      <td>9349219.00</td>\n",
       "      <td>9349219.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>22503570.13</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>BBG001MM1KV4</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-16T09:32:38.1130000+00:00</td>\n",
       "      <td>2.41</td>\n",
       "      <td>sdfdslkf234092304s</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_0000MIP4</td>\n",
       "      <td>P</td>\n",
       "      <td>123624.00</td>\n",
       "      <td>123624.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>917042.83</td>\n",
       "      <td>JustEat_LondonStockEx_JE</td>\n",
       "      <td>BBG0065YWM39</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-10T13:58:57.1130000+00:00</td>\n",
       "      <td>7.42</td>\n",
       "      <td>kj0llk90f0909201141</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td>default</td>\n",
       "      <td>LUID_0000MIP9</td>\n",
       "      <td>P</td>\n",
       "      <td>500000.00</td>\n",
       "      <td>500000.00</td>\n",
       "      <td>None</td>\n",
       "      <td>GBP</td>\n",
       "      <td>Position</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>GBP</td>\n",
       "      <td>5249000.00</td>\n",
       "      <td>MicroFocus_LondonStockEx_MCRO</td>\n",
       "      <td>BBG000G4KKD2</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>2019-09-12T15:32:57.1130000+00:00</td>\n",
       "      <td>10.50</td>\n",
       "      <td>sadjkas934234sadfs</td>\n",
       "      <td>common_stock</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            local_vars_configuration _instrument_scope  \\\n",
       "0  <lusid.configuration.Configuration object at 0...           default   \n",
       "1  <lusid.configuration.Configuration object at 0...           default   \n",
       "2  <lusid.configuration.Configuration object at 0...           default   \n",
       "3  <lusid.configuration.Configuration object at 0...           default   \n",
       "4  <lusid.configuration.Configuration object at 0...           default   \n",
       "5  <lusid.configuration.Configuration object at 0...           default   \n",
       "6  <lusid.configuration.Configuration object at 0...           default   \n",
       "7  <lusid.configuration.Configuration object at 0...           default   \n",
       "\n",
       "  _instrument_uid _holding_type       _units  _settled_units _transaction  \\\n",
       "0         CCY_GBP             B 812026970.09    812026970.09         None   \n",
       "1   LUID_00044OXX             P    418176.00       418176.00         None   \n",
       "2   LUID_0000MIOY             P   1762711.00      1762711.00         None   \n",
       "3   LUID_0000MIOY             P    853000.00       853000.00         None   \n",
       "4   LUID_0000MIPD             P  14087318.00     14087318.00         None   \n",
       "5   LUID_0000MIPD             P   9349219.00      9349219.00         None   \n",
       "6   LUID_0000MIP4             P    123624.00       123624.00         None   \n",
       "7   LUID_0000MIP9             P    500000.00       500000.00         None   \n",
       "\n",
       "  _currency _holding_type_name discriminator  ...  cost.currency  \\\n",
       "0       GBP            Balance          None  ...            GBP   \n",
       "1       GBP           Position          None  ...            GBP   \n",
       "2       GBP           Position          None  ...            GBP   \n",
       "3       GBP           Position          None  ...            GBP   \n",
       "4       GBP           Position          None  ...            GBP   \n",
       "5       GBP           Position          None  ...            GBP   \n",
       "6       GBP           Position          None  ...            GBP   \n",
       "7       GBP           Position          None  ...            GBP   \n",
       "\n",
       "  cost_portfolio_ccy.amount           Instrument/default/Name  \\\n",
       "0              812026970.09                               GBP   \n",
       "1                2178153.33               BP_LondonStockEx_BP   \n",
       "2               15599992.35  BurfordCapital_LondonStockEx_BUR   \n",
       "3                7531990.00  BurfordCapital_LondonStockEx_BUR   \n",
       "4               33879999.79       Glencore_LondonStockEx_GLEN   \n",
       "5               22503570.13       Glencore_LondonStockEx_GLEN   \n",
       "6                 917042.83          JustEat_LondonStockEx_JE   \n",
       "7                5249000.00     MicroFocus_LondonStockEx_MCRO   \n",
       "\n",
       "  Instrument/default/Figi Holding/default/SourcePortfolioId  \\\n",
       "0     some-figi-code12312                           UK12XC2   \n",
       "1            BBG000C05BD1                           UK12XC2   \n",
       "2            BBG000PN88Q7                           UK12XC2   \n",
       "3            BBG000PN88Q7                           UK12XC2   \n",
       "4            BBG001MM1KV4                           UK12XC2   \n",
       "5            BBG001MM1KV4                           UK12XC2   \n",
       "6            BBG0065YWM39                           UK12XC2   \n",
       "7            BBG000G4KKD2                           UK12XC2   \n",
       "\n",
       "  Holding/default/SourcePortfolioScope Holding/default/TaxlotPurchaseDate  \\\n",
       "0                  AccountingDemoScope                                NaN   \n",
       "1                  AccountingDemoScope  2019-09-13T16:29:18.1230000+00:00   \n",
       "2                  AccountingDemoScope  2019-09-05T15:12:44.0900000+00:00   \n",
       "3                  AccountingDemoScope  2019-09-15T10:58:57.1130000+00:00   \n",
       "4                  AccountingDemoScope  2019-09-10T09:58:43.1120000+00:00   \n",
       "5                  AccountingDemoScope  2019-09-16T09:32:38.1130000+00:00   \n",
       "6                  AccountingDemoScope  2019-09-10T13:58:57.1130000+00:00   \n",
       "7                  AccountingDemoScope  2019-09-12T15:32:57.1130000+00:00   \n",
       "\n",
       "  Holding/default/TaxlotPurchasePrice  Holding/default/TaxlotId  \\\n",
       "0                                 NaN                       NaN   \n",
       "1                                5.10        fas2340090sd9f0s23   \n",
       "2                                8.85        dsfsdlkjs933234211   \n",
       "3                                8.83       dflkjsdflk932432rsd   \n",
       "4                                2.40        dfklsjd90232350239   \n",
       "5                                2.41        sdfdslkf234092304s   \n",
       "6                                7.42       kj0llk90f0909201141   \n",
       "7                               10.50        sadjkas934234sadfs   \n",
       "\n",
       "  Instrument/InstrumentProperties005/security_type  \n",
       "0                                              NaN  \n",
       "1                                     common_stock  \n",
       "2                                     common_stock  \n",
       "3                                     common_stock  \n",
       "4                                     common_stock  \n",
       "5                                     common_stock  \n",
       "6                                     common_stock  \n",
       "7                                     common_stock  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response = api_factory.build(lusid.api.TransactionPortfoliosApi).get_holdings(\n",
    "    scope=trading_scope,\n",
    "    code=portfolio_code,\n",
    "    property_keys=[\n",
    "        \"Instrument/default/Name\",\n",
    "        \"Instrument/default/Figi\",\n",
    "        f\"Instrument/{instrument_properties_scope}/security_type\"\n",
    "    ],\n",
    "    by_taxlots=True,\n",
    "    effective_at=datetime.datetime(year=2019, month=9, day=30, hour=12, tzinfo=pytz.UTC))\n",
    "\n",
    "prettyprint.get_holdings_df(response)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate P/L for September 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[91m\u001b[1mOutput Transactions for Portfolio\u001b[0m\n",
      "\u001b[1mScope: \u001b[0mAccountingDemoScope\n",
      "\u001b[1mCode: \u001b[0mUK12XC2\n",
      "\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>Transaction ID</th>\n",
       "      <th>Transaction Type</th>\n",
       "      <th>Transaction/AccountingDemoScope/executor</th>\n",
       "      <th>Transaction/AccountingDemoScope/asset_name</th>\n",
       "      <th>Transaction/default/SourcePortfolioId</th>\n",
       "      <th>Transaction/default/SourcePortfolioScope</th>\n",
       "      <th>Transaction/AccountingDemoScope/exposure</th>\n",
       "      <th>Transaction/default/ResultantHolding</th>\n",
       "      <th>Units</th>\n",
       "      <th>Price</th>\n",
       "      <th>Currency</th>\n",
       "      <th>Transaction Date</th>\n",
       "      <th>Settlement Date</th>\n",
       "      <th>Realised Gain Loss</th>\n",
       "      <th>0</th>\n",
       "      <th>accounting_method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2354lafjaso3432502</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>854176.00</td>\n",
       "      <td>5.32</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>-99786.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sdlfksdlfk23409235</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>153000.00</td>\n",
       "      <td>7.33</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>-13494.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>kjk99898990z88908</td>\n",
       "      <td>FundsIn</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>GBP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>900000000.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-01 09:31:22.664000+00:00</td>\n",
       "      <td>2019-09-01 09:31:22.664000+00:00</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>435opkplk03sfsf33</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>729176.00</td>\n",
       "      <td>5.92</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-03 14:42:12.435000+00:00</td>\n",
       "      <td>2019-09-05 14:42:12.435000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dsfsdlkjs933234211</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BurfordCapital</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1762711.00</td>\n",
       "      <td>8.85</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-05 15:12:44.090000+00:00</td>\n",
       "      <td>2019-09-07 15:12:44.090000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dfklsjd90232350239</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>Glencore</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14087318.00</td>\n",
       "      <td>2.40</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-10 09:58:43.112000+00:00</td>\n",
       "      <td>2019-09-11 09:58:43.112000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>kj0llk90f0909201141</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>276624.00</td>\n",
       "      <td>7.42</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-10 13:58:57.113000+00:00</td>\n",
       "      <td>2019-09-11 13:58:57.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sadjkas934234sadfs</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>MicroFocus_LondonStockEx_MCRO</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>MicroFocus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500000.00</td>\n",
       "      <td>10.50</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-12 15:32:57.113000+00:00</td>\n",
       "      <td>2019-09-14 15:32:57.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>fas2340090sd9f0s23</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>543176.00</td>\n",
       "      <td>5.10</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-13 16:29:18.123000+00:00</td>\n",
       "      <td>2019-09-15 16:29:18.123000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>dflkjsdflk932432rsd</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BurfordCapital</td>\n",
       "      <td>NaN</td>\n",
       "      <td>853000.00</td>\n",
       "      <td>8.83</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-15 10:58:57.113000+00:00</td>\n",
       "      <td>2019-09-17 10:58:57.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sdfdslkf234092304s</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>Glencore</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9349219.00</td>\n",
       "      <td>2.41</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-16 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-18 09:32:38.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.00</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-113281.48</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Transaction ID Transaction Type  \\\n",
       "0    2354lafjaso3432502             Sell   \n",
       "1    sdlfksdlfk23409235             Sell   \n",
       "2     kjk99898990z88908          FundsIn   \n",
       "3     435opkplk03sfsf33              Buy   \n",
       "4    dsfsdlkjs933234211              Buy   \n",
       "5    dfklsjd90232350239              Buy   \n",
       "6   kj0llk90f0909201141              Buy   \n",
       "7    sadjkas934234sadfs              Buy   \n",
       "8    fas2340090sd9f0s23              Buy   \n",
       "9   dflkjsdflk932432rsd              Buy   \n",
       "10   sdfdslkf234092304s              Buy   \n",
       "11                  NaN              NaN   \n",
       "12                  NaN              NaN   \n",
       "\n",
       "   Transaction/AccountingDemoScope/executor  \\\n",
       "0                                  jp392431   \n",
       "1                                  jp392431   \n",
       "2                                  jx112421   \n",
       "3                                  jx112421   \n",
       "4                                  jx112421   \n",
       "5                                  jx112421   \n",
       "6                                  jp392431   \n",
       "7                                  jx112421   \n",
       "8                                  jp392431   \n",
       "9                                  jx112421   \n",
       "10                                 jp392431   \n",
       "11                                      NaN   \n",
       "12                                      NaN   \n",
       "\n",
       "   Transaction/AccountingDemoScope/asset_name  \\\n",
       "0                         BP_LondonStockEx_BP   \n",
       "1                     JustEat_LondonStockEx_J   \n",
       "2                                         GBP   \n",
       "3                         BP_LondonStockEx_BP   \n",
       "4            BurfordCapital_LondonStockEx_BUR   \n",
       "5                 Glencore_LondonStockEx_GLEN   \n",
       "6                     JustEat_LondonStockEx_J   \n",
       "7               MicroFocus_LondonStockEx_MCRO   \n",
       "8                         BP_LondonStockEx_BP   \n",
       "9            BurfordCapital_LondonStockEx_BUR   \n",
       "10                Glencore_LondonStockEx_GLEN   \n",
       "11                                        NaN   \n",
       "12                                        NaN   \n",
       "\n",
       "   Transaction/default/SourcePortfolioId  \\\n",
       "0                                UK12XC2   \n",
       "1                                UK12XC2   \n",
       "2                                UK12XC2   \n",
       "3                                UK12XC2   \n",
       "4                                UK12XC2   \n",
       "5                                UK12XC2   \n",
       "6                                UK12XC2   \n",
       "7                                UK12XC2   \n",
       "8                                UK12XC2   \n",
       "9                                UK12XC2   \n",
       "10                               UK12XC2   \n",
       "11                                   NaN   \n",
       "12                                   NaN   \n",
       "\n",
       "   Transaction/default/SourcePortfolioScope  \\\n",
       "0                       AccountingDemoScope   \n",
       "1                       AccountingDemoScope   \n",
       "2                       AccountingDemoScope   \n",
       "3                       AccountingDemoScope   \n",
       "4                       AccountingDemoScope   \n",
       "5                       AccountingDemoScope   \n",
       "6                       AccountingDemoScope   \n",
       "7                       AccountingDemoScope   \n",
       "8                       AccountingDemoScope   \n",
       "9                       AccountingDemoScope   \n",
       "10                      AccountingDemoScope   \n",
       "11                                      NaN   \n",
       "12                                      NaN   \n",
       "\n",
       "   Transaction/AccountingDemoScope/exposure  \\\n",
       "0                                        BP   \n",
       "1                                   JustEat   \n",
       "2                              900000000.00   \n",
       "3                                        BP   \n",
       "4                            BurfordCapital   \n",
       "5                                  Glencore   \n",
       "6                                   JustEat   \n",
       "7                                MicroFocus   \n",
       "8                                        BP   \n",
       "9                            BurfordCapital   \n",
       "10                                 Glencore   \n",
       "11                                      NaN   \n",
       "12                                      NaN   \n",
       "\n",
       "    Transaction/default/ResultantHolding       Units  \\\n",
       "0                                    NaN   854176.00   \n",
       "1                                    NaN   153000.00   \n",
       "2                                   1.00         GBP   \n",
       "3                                    NaN   729176.00   \n",
       "4                                    NaN  1762711.00   \n",
       "5                                    NaN 14087318.00   \n",
       "6                                    NaN   276624.00   \n",
       "7                                    NaN   500000.00   \n",
       "8                                    NaN   543176.00   \n",
       "9                                    NaN   853000.00   \n",
       "10                                   NaN  9349219.00   \n",
       "11                                   NaN         NaN   \n",
       "12                                   NaN         NaN   \n",
       "\n",
       "                               Price                          Currency  \\\n",
       "0                               5.32                               GBP   \n",
       "1                               7.33                               GBP   \n",
       "2   2019-09-01 09:31:22.664000+00:00  2019-09-01 09:31:22.664000+00:00   \n",
       "3                               5.92                               GBP   \n",
       "4                               8.85                               GBP   \n",
       "5                               2.40                               GBP   \n",
       "6                               7.42                               GBP   \n",
       "7                              10.50                               GBP   \n",
       "8                               5.10                               GBP   \n",
       "9                               8.83                               GBP   \n",
       "10                              2.41                               GBP   \n",
       "11                               NaN                               NaN   \n",
       "12                               NaN                               NaN   \n",
       "\n",
       "                   Transaction Date                  Settlement Date  \\\n",
       "0  2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "1  2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "2                               NaT                              NaT   \n",
       "3  2019-09-03 14:42:12.435000+00:00 2019-09-05 14:42:12.435000+00:00   \n",
       "4  2019-09-05 15:12:44.090000+00:00 2019-09-07 15:12:44.090000+00:00   \n",
       "5  2019-09-10 09:58:43.112000+00:00 2019-09-11 09:58:43.112000+00:00   \n",
       "6  2019-09-10 13:58:57.113000+00:00 2019-09-11 13:58:57.113000+00:00   \n",
       "7  2019-09-12 15:32:57.113000+00:00 2019-09-14 15:32:57.113000+00:00   \n",
       "8  2019-09-13 16:29:18.123000+00:00 2019-09-15 16:29:18.123000+00:00   \n",
       "9  2019-09-15 10:58:57.113000+00:00 2019-09-17 10:58:57.113000+00:00   \n",
       "10 2019-09-16 09:32:38.113000+00:00 2019-09-18 09:32:38.113000+00:00   \n",
       "11                              NaT                              NaT   \n",
       "12                              NaT                              NaT   \n",
       "\n",
       "    Realised Gain Loss          0 accounting_method  \n",
       "0            -99786.88        NaN              FIFO  \n",
       "1            -13494.60        NaN              FIFO  \n",
       "2                  NaN        NaN              FIFO  \n",
       "3                  NaN        NaN              FIFO  \n",
       "4                  NaN        NaN              FIFO  \n",
       "5                  NaN        NaN              FIFO  \n",
       "6                  NaN        NaN              FIFO  \n",
       "7                  NaN        NaN              FIFO  \n",
       "8                  NaN        NaN              FIFO  \n",
       "9                  NaN        NaN              FIFO  \n",
       "10                 NaN        NaN              FIFO  \n",
       "11                 NaN       1.00              FIFO  \n",
       "12                 NaN -113281.48              FIFO  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response = api_factory.build(lusid.api.TransactionPortfoliosApi).build_transactions(\n",
    "    scope=trading_scope,\n",
    "    code=portfolio_code,\n",
    "    transaction_query_parameters=lusid.models.TransactionQueryParameters(\n",
    "        start_date=datetime.datetime(year=2019, month=9, day=1, hour=0, tzinfo=pytz.UTC).isoformat(),\n",
    "        end_date=datetime.datetime(year=2019, month=9, day=30, hour=0, tzinfo=pytz.UTC).isoformat(),\n",
    "        query_mode=\"TradeDate\"\n",
    "        )\n",
    "    )\n",
    "\n",
    "profit_loss_fifo = prettyprint.output_transactions(response, trading_scope, portfolio_code)\n",
    "profit_loss_fifo[\"accounting_method\"] = \"FIFO\"\n",
    "profit_loss_fifo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Derived Portfolio with \"LastInFirstOut\" accounting method and Generate P/L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mDerived Portfolio Created\u001b[0m\n",
      "\u001b[1mScope: \u001b[0mAccountingDemoScope\n",
      "\u001b[1mCode: \u001b[0mUK12XC2LIFO\n",
      "\u001b[1mPortfolio Effective From: \u001b[0m2010-01-01 00:00:00+00:00\n",
      "\u001b[1mPortfolio Created On: \u001b[0m2023-10-02 15:43:53.779637+00:00\n",
      "\n",
      "\u001b[1m   Parent Portfolio Details\u001b[0m\n",
      "\u001b[1m   Scope: \u001b[0mAccountingDemoScope\n",
      "\u001b[1m   Code: \u001b[0mUK12XC2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    response = api_factory.build(lusid.api.PortfoliosApi).get_portfolio(\n",
    "        scope=trading_scope,\n",
    "        code=portfolio_code+\"LIFO\")\n",
    "    \n",
    "except lusid.exceptions.ApiException as e:\n",
    "    if e.status == 404:\n",
    "        response = api_factory.build(lusid.api.DerivedTransactionPortfoliosApi).create_derived_portfolio(\n",
    "            scope=trading_scope,\n",
    "            create_derived_transaction_portfolio_request=lusid.models.CreateDerivedTransactionPortfolioRequest(\n",
    "                code=portfolio_code+\"LIFO\",\n",
    "                display_name=\"LIFO Accounting treatment for the fund\",\n",
    "                parent_portfolio_id=lusid.models.ResourceId(\n",
    "                    scope=trading_scope,\n",
    "                    code=portfolio_code),\n",
    "                accounting_method=\"LastInFirstOut\",\n",
    "                created=datetime.datetime(year=2010, month=1, day=1, tzinfo=pytz.UTC).isoformat()\n",
    "            )\n",
    "        )\n",
    "\n",
    "prettyprint.portfolio_response(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[91m\u001b[1mOutput Transactions for Portfolio\u001b[0m\n",
      "\u001b[1mScope: \u001b[0mAccountingDemoScope\n",
      "\u001b[1mCode: \u001b[0mUK12XC2LIFO\n",
      "\n"
     ]
    },
    {
     "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>Transaction ID</th>\n",
       "      <th>Transaction Type</th>\n",
       "      <th>Transaction/AccountingDemoScope/executor</th>\n",
       "      <th>Transaction/AccountingDemoScope/asset_name</th>\n",
       "      <th>Transaction/default/SourcePortfolioId</th>\n",
       "      <th>Transaction/default/SourcePortfolioScope</th>\n",
       "      <th>Transaction/AccountingDemoScope/exposure</th>\n",
       "      <th>Transaction/default/ResultantHolding</th>\n",
       "      <th>Units</th>\n",
       "      <th>Price</th>\n",
       "      <th>Currency</th>\n",
       "      <th>Transaction Date</th>\n",
       "      <th>Settlement Date</th>\n",
       "      <th>Realised Gain Loss</th>\n",
       "      <th>0</th>\n",
       "      <th>accounting_method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sdlfksdlfk23409235</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>153000.00</td>\n",
       "      <td>7.33</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>-13494.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2354lafjaso3432502</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>854176.00</td>\n",
       "      <td>5.32</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>14166.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>kjk99898990z88908</td>\n",
       "      <td>FundsIn</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>GBP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>900000000.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-01 09:31:22.664000+00:00</td>\n",
       "      <td>2019-09-01 09:31:22.664000+00:00</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>435opkplk03sfsf33</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>729176.00</td>\n",
       "      <td>5.92</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-03 14:42:12.435000+00:00</td>\n",
       "      <td>2019-09-05 14:42:12.435000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dsfsdlkjs933234211</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BurfordCapital</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1762711.00</td>\n",
       "      <td>8.85</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-05 15:12:44.090000+00:00</td>\n",
       "      <td>2019-09-07 15:12:44.090000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dfklsjd90232350239</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>Glencore</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14087318.00</td>\n",
       "      <td>2.40</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-10 09:58:43.112000+00:00</td>\n",
       "      <td>2019-09-11 09:58:43.112000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>kj0llk90f0909201141</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>276624.00</td>\n",
       "      <td>7.42</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-10 13:58:57.113000+00:00</td>\n",
       "      <td>2019-09-11 13:58:57.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sadjkas934234sadfs</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>MicroFocus_LondonStockEx_MCRO</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>MicroFocus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500000.00</td>\n",
       "      <td>10.50</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-12 15:32:57.113000+00:00</td>\n",
       "      <td>2019-09-14 15:32:57.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>fas2340090sd9f0s23</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>543176.00</td>\n",
       "      <td>5.10</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-13 16:29:18.123000+00:00</td>\n",
       "      <td>2019-09-15 16:29:18.123000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>dflkjsdflk932432rsd</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jx112421</td>\n",
       "      <td>BurfordCapital_LondonStockEx_BUR</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BurfordCapital</td>\n",
       "      <td>NaN</td>\n",
       "      <td>853000.00</td>\n",
       "      <td>8.83</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-15 10:58:57.113000+00:00</td>\n",
       "      <td>2019-09-17 10:58:57.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sdfdslkf234092304s</td>\n",
       "      <td>Buy</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>Glencore_LondonStockEx_GLEN</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>Glencore</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9349219.00</td>\n",
       "      <td>2.41</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-16 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-18 09:32:38.113000+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.00</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>671.48</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Transaction ID Transaction Type  \\\n",
       "0    sdlfksdlfk23409235             Sell   \n",
       "1    2354lafjaso3432502             Sell   \n",
       "2     kjk99898990z88908          FundsIn   \n",
       "3     435opkplk03sfsf33              Buy   \n",
       "4    dsfsdlkjs933234211              Buy   \n",
       "5    dfklsjd90232350239              Buy   \n",
       "6   kj0llk90f0909201141              Buy   \n",
       "7    sadjkas934234sadfs              Buy   \n",
       "8    fas2340090sd9f0s23              Buy   \n",
       "9   dflkjsdflk932432rsd              Buy   \n",
       "10   sdfdslkf234092304s              Buy   \n",
       "11                  NaN              NaN   \n",
       "12                  NaN              NaN   \n",
       "\n",
       "   Transaction/AccountingDemoScope/executor  \\\n",
       "0                                  jp392431   \n",
       "1                                  jp392431   \n",
       "2                                  jx112421   \n",
       "3                                  jx112421   \n",
       "4                                  jx112421   \n",
       "5                                  jx112421   \n",
       "6                                  jp392431   \n",
       "7                                  jx112421   \n",
       "8                                  jp392431   \n",
       "9                                  jx112421   \n",
       "10                                 jp392431   \n",
       "11                                      NaN   \n",
       "12                                      NaN   \n",
       "\n",
       "   Transaction/AccountingDemoScope/asset_name  \\\n",
       "0                     JustEat_LondonStockEx_J   \n",
       "1                         BP_LondonStockEx_BP   \n",
       "2                                         GBP   \n",
       "3                         BP_LondonStockEx_BP   \n",
       "4            BurfordCapital_LondonStockEx_BUR   \n",
       "5                 Glencore_LondonStockEx_GLEN   \n",
       "6                     JustEat_LondonStockEx_J   \n",
       "7               MicroFocus_LondonStockEx_MCRO   \n",
       "8                         BP_LondonStockEx_BP   \n",
       "9            BurfordCapital_LondonStockEx_BUR   \n",
       "10                Glencore_LondonStockEx_GLEN   \n",
       "11                                        NaN   \n",
       "12                                        NaN   \n",
       "\n",
       "   Transaction/default/SourcePortfolioId  \\\n",
       "0                                UK12XC2   \n",
       "1                                UK12XC2   \n",
       "2                                UK12XC2   \n",
       "3                                UK12XC2   \n",
       "4                                UK12XC2   \n",
       "5                                UK12XC2   \n",
       "6                                UK12XC2   \n",
       "7                                UK12XC2   \n",
       "8                                UK12XC2   \n",
       "9                                UK12XC2   \n",
       "10                               UK12XC2   \n",
       "11                                   NaN   \n",
       "12                                   NaN   \n",
       "\n",
       "   Transaction/default/SourcePortfolioScope  \\\n",
       "0                       AccountingDemoScope   \n",
       "1                       AccountingDemoScope   \n",
       "2                       AccountingDemoScope   \n",
       "3                       AccountingDemoScope   \n",
       "4                       AccountingDemoScope   \n",
       "5                       AccountingDemoScope   \n",
       "6                       AccountingDemoScope   \n",
       "7                       AccountingDemoScope   \n",
       "8                       AccountingDemoScope   \n",
       "9                       AccountingDemoScope   \n",
       "10                      AccountingDemoScope   \n",
       "11                                      NaN   \n",
       "12                                      NaN   \n",
       "\n",
       "   Transaction/AccountingDemoScope/exposure  \\\n",
       "0                                   JustEat   \n",
       "1                                        BP   \n",
       "2                              900000000.00   \n",
       "3                                        BP   \n",
       "4                            BurfordCapital   \n",
       "5                                  Glencore   \n",
       "6                                   JustEat   \n",
       "7                                MicroFocus   \n",
       "8                                        BP   \n",
       "9                            BurfordCapital   \n",
       "10                                 Glencore   \n",
       "11                                      NaN   \n",
       "12                                      NaN   \n",
       "\n",
       "    Transaction/default/ResultantHolding       Units  \\\n",
       "0                                    NaN   153000.00   \n",
       "1                                    NaN   854176.00   \n",
       "2                                   1.00         GBP   \n",
       "3                                    NaN   729176.00   \n",
       "4                                    NaN  1762711.00   \n",
       "5                                    NaN 14087318.00   \n",
       "6                                    NaN   276624.00   \n",
       "7                                    NaN   500000.00   \n",
       "8                                    NaN   543176.00   \n",
       "9                                    NaN   853000.00   \n",
       "10                                   NaN  9349219.00   \n",
       "11                                   NaN         NaN   \n",
       "12                                   NaN         NaN   \n",
       "\n",
       "                               Price                          Currency  \\\n",
       "0                               7.33                               GBP   \n",
       "1                               5.32                               GBP   \n",
       "2   2019-09-01 09:31:22.664000+00:00  2019-09-01 09:31:22.664000+00:00   \n",
       "3                               5.92                               GBP   \n",
       "4                               8.85                               GBP   \n",
       "5                               2.40                               GBP   \n",
       "6                               7.42                               GBP   \n",
       "7                              10.50                               GBP   \n",
       "8                               5.10                               GBP   \n",
       "9                               8.83                               GBP   \n",
       "10                              2.41                               GBP   \n",
       "11                               NaN                               NaN   \n",
       "12                               NaN                               NaN   \n",
       "\n",
       "                   Transaction Date                  Settlement Date  \\\n",
       "0  2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "1  2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "2                               NaT                              NaT   \n",
       "3  2019-09-03 14:42:12.435000+00:00 2019-09-05 14:42:12.435000+00:00   \n",
       "4  2019-09-05 15:12:44.090000+00:00 2019-09-07 15:12:44.090000+00:00   \n",
       "5  2019-09-10 09:58:43.112000+00:00 2019-09-11 09:58:43.112000+00:00   \n",
       "6  2019-09-10 13:58:57.113000+00:00 2019-09-11 13:58:57.113000+00:00   \n",
       "7  2019-09-12 15:32:57.113000+00:00 2019-09-14 15:32:57.113000+00:00   \n",
       "8  2019-09-13 16:29:18.123000+00:00 2019-09-15 16:29:18.123000+00:00   \n",
       "9  2019-09-15 10:58:57.113000+00:00 2019-09-17 10:58:57.113000+00:00   \n",
       "10 2019-09-16 09:32:38.113000+00:00 2019-09-18 09:32:38.113000+00:00   \n",
       "11                              NaT                              NaT   \n",
       "12                              NaT                              NaT   \n",
       "\n",
       "    Realised Gain Loss      0 accounting_method  \n",
       "0            -13494.60    NaN              LIFO  \n",
       "1             14166.08    NaN              LIFO  \n",
       "2                  NaN    NaN              LIFO  \n",
       "3                  NaN    NaN              LIFO  \n",
       "4                  NaN    NaN              LIFO  \n",
       "5                  NaN    NaN              LIFO  \n",
       "6                  NaN    NaN              LIFO  \n",
       "7                  NaN    NaN              LIFO  \n",
       "8                  NaN    NaN              LIFO  \n",
       "9                  NaN    NaN              LIFO  \n",
       "10                 NaN    NaN              LIFO  \n",
       "11                 NaN   1.00              LIFO  \n",
       "12                 NaN 671.48              LIFO  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response = api_factory.build(lusid.api.TransactionPortfoliosApi).build_transactions(\n",
    "    scope=trading_scope,\n",
    "    code=portfolio_code+\"LIFO\",\n",
    "    transaction_query_parameters=lusid.models.TransactionQueryParameters(\n",
    "        start_date=datetime.datetime(year=2019, month=9, day=1, hour=0, tzinfo=pytz.UTC).isoformat(),\n",
    "        end_date=datetime.datetime(year=2019, month=9, day=30, hour=0, tzinfo=pytz.UTC).isoformat(),\n",
    "        query_mode=\"TradeDate\"\n",
    "        )\n",
    "    )\n",
    "\n",
    "profit_loss_lifo = prettyprint.output_transactions(response, trading_scope, portfolio_code+\"LIFO\")\n",
    "profit_loss_lifo[\"accounting_method\"] = \"LIFO\"\n",
    "profit_loss_lifo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4lmuuuSaNGzfOhRdeONdrXmKJJdKqVaskyYcffpj77rsv3bp1ywknnDDX87Zr1660233o0KH55JNPss8++5RK5CRp1KhRTjvttDRp0mSen5v6OOWUU2rdILNHjx7p3bt3Xn/99Xz66acN8hy77bZbqUROUmucxL///e/S8TvvvDOzZs3KYYcdViqRk9l/BszPTvavat++fbbaaqvSTvNk9g9G2rRpk2233Xaej5k4cWLuvvvubLrpprVK5CRp27ZtjjjiiHz88cfz/WfjiiuumF/96le1js0ZUfTl9+Lpp5/OW2+9la222mqucTvHHXdcWrVqlTvvvDPTp09PMnv38rhx47L11lvX+sFiRUVFTj755Ln+1QoAUMyOZABgkfbWW2+V5pTO0b59+wwbNiwrr7xy6djrr7+eysrKdOzYMWefffZc15k4cWJp3RxzZrzecsstGTt2bD755JNUV1eXzn/wwQf1yrzxxhunQ4cOueiii/Liiy9m6623Tt++fbPaaqvVKovnN/Prr7+eqqqqbLrppnP98/5GjRqld+/e+b//+796Zf6yd955Z673vG/fvtl7771LH3/66ae57LLL8o9//CPjxo3L559/Xmv9/Lx3c3ZLftmcIvWrBeYDDzyQWbNm1btI/s9//pNk3juxN9xww7Ro0aLW3NZdd9019913X/r375/dd989m266aTbeeONa/7Q+SQYOHJg//elP2WeffTJw4MBsscUW2XjjjdOpU6f5zvjVnfZzsjVp0qRWtjZt2mSHHXbIXXfdlddee61008c5O/a/WgQWmVNGz9mJncwu437yk5/kggsuyJ133pkDDzwwyexd9a+++mpWXnnlb/zhxXPPPZeampr069fvG0vtos9Nly5dstJKK+WNN97Ip59+mmWWWabOr21evulrbkGvX5fnmOPFF19MMu/Pe+/evRcowz777JNhw4bl/vvvz8Ybb5yHH344hxxyyNd+Lv79739n1qxZmT59+lz/miKZ/YO9ZPafRdtss02dc6y11lpp1Kj2Hqd5vRdFXwNLL7101l133Tz88MN5/fXXs+aaa5beu4033niu9V27dk3nzp3zzjvv1DknAHzfKZIBgEXalltumbvuuitJ8vHHH+fWW2/N4MGDs9dee2XkyJGlfxY/efLkJMnYsWMzduzYr73elwvP4447LldddVXp5nYdOnQo7VA+55xzMm3atHplXm655TJixIiceeaZGT58eB588MEkyQorrJCjjjoqBx10UL0yf/LJJ0lmF4jz8uU5o99kzs7H999/f65z/fr1S2VlZZLZO0pXW221WuenT5+e7bffPi+88EJ69eqVn/zkJ2ndunUaN26cd955J7feeut8vXfzKu3m7CScNWtWreP/+Mc/0qpVq3kWR3UxZ7fpl3d+zlFRUZG2bdvWek923nnn3Hzzzbniiity7bXX5qqrrkpFRUXpRnG9evVKkvzwhz/M/fffnwsvvDB33nlnaQf3euutl1NPPTWbbrppnTPO6/PYuHHjtG7duvQ1MMdPf/rT3HXXXbnhhhtyxhln5P33389DDz2Uvn37ZpVVVqnT81VVVeWOO+7I0ksvnR122KHWuT333DMXXHBBbrrpplKRPCfD183Y/bL5WVv0uUlm/wCpoYrkL+9GnuPrvubqq65f13Ne97x+X8/P7+l52XrrrdOuXbvcdNNNGTduXKqrqwvHWsz5M+npp5/O008//bXrvvqDo28yr/dizk70eb0XRV8DX15Xlz8TFckAUHeKZABgsdGmTZscccQRmTJlSs4///ycccYZpZ28c4qKHXfcsbQjs8hHH32Uq6++OmuuuWZGjBhR62ZlH3744Vw7cudXly5d8qc//SnV1dV58cUX88gjj+Qvf/lLfvOb36Rly5alm5PNT+Y55dfHH388z/NzxlXUxZydjk888USdHzPH0KFD88ILL2TffffNZZddVuvcXXfdlVtvvXW+r1kXVVVVeeSRR7L99tvPdfO/uprznn/00Uelm6fNUVNTk48++miu0mu77bbLdtttl08//TTPPPNM6SaNu+22W8aMGVO6UdzGG2+cjTfeOFOnTs0///nPDB8+PNdcc01+8pOf5KmnnprnOJB5+d///ldr1Ecyu2ybNGnSXMViv379suqqq+a2227LKaeckptvvjmzZs2ar5vsfXl0xdftoH7uuefy4osv5gc/+EHp63BeP4T4qjk3O6vL2i9/buZlztf3nHVzdrjOq/j96k72hdmc1/Pxxx/P9TU5P7+n56VJkybZc889c/nll+eVV17J+uuvnzXWWOMbsxx++OE544wzFui562N+vwYa8s9EAMCMZABgMXTMMcekY8eOueaaa/L2228nSVZbbbUsu+yyee655zJjxoxvvMa4ceNSU1OTzTffvFaJnMyeu9lQGjVqlF69euXII4/M1VdfnSQZNmxYvTKvssoqadGiRZ577rlaNzNLZs9bnnMDvbro169fVlxxxTz11FMZPXr0fLyi2eNGksxzvERDvndfNWrUqHz++ef1HmuRpLSDeF4F+j//+c9UVVV97U38lllmmfTv3z+XXHJJBg0alP/973/517/+Nde6JZZYIv369csf/vCH/PrXv87UqVPzyCOP1DnjvN7DMWPGZObMmfPMtv/+++fjjz/OP/7xj9x0001p2bJldtxxxzo/35yxFjvvvHP23Xffuf6bM6t2zrqll146PXv2zNtvv/2No1TWXXfdNGrUKI8//vg3fo0XfW4mTJiQt956KyuttFKpRJxTUr/33ntzrZ8zImFBzdlB/OWRNw1tzjzoee0Anp/f019nn332SXV1dT744IPC3cjJ7B30FRUVefbZZ+t8/YbcyV30NfD555/nueeeyxJLLFH6Qcuc9+7JJ5+ca/0777yTd999d4EzAcD3iSIZAFjsLLHEEjnyyCMzY8aMnHfeeUlm77z72c9+lvHjx+ekk06aZ2n18ssvl3a6denSJcnsoubLJdG7776b0047bYHyjR07dp474eY895yb7c1v5ubNm2fnnXfORx99lMsvv7zWuhtuuCFvvPFGnTM2adIk5513Xho1apT999//a4vOee3snPPefbX4euKJJ3L99dfXOcP8Gjp0aJo3bz7XTbjmx+67754mTZrkiiuuqLVLdvr06Rk8eHCSZNCgQaXjo0ePnmdB9tXP5ZgxY+Yq9+e1ri7+/Oc/1yrApk+fntNPP32ubHMMGjQoLVq0yG9/+9uMGzcuP/nJT+aaof11xo0bl8cffzxdu3bNX//611x22WVz/XfttddmiSWWyB133FEaWXLQQQdl1qxZOeaYYzJ16tRa16yqqiqNSGjXrl123HHHec46T2a/PzNnzkwy+wcTyy67bG6++eZao15qampy6qmnZubMmbVe/7LLLpsePXrk6aefLs3uTWaPPfjyjTgXxJybBk6YMKFBrjcvu+66axo1apQrrriiNBc9mV2cXnDBBQt8/VVXXTV33nlnbrrppuy+++6Fa9u3b5+BAwfmmWeeyaWXXpqampq51vzzn//MF198Ufq4Id+jjTbaKN26dcuIESPmuqHf+eefn0mTJmXXXXctjSDq06dPVlxxxTzwwAO1fgBTU1OT008/vcHGlADA94XRFgDAYumnP/1pLrnkktx222055phj0q1bt5x44ol54YUX8pe//CUPPvhgNt5447Rt2zbvvfdeXn755bz44osZMWJE2rZtmw4dOmTHHXfM3//+92y++ebZbLPN8r///S8PPPBANttss9Ku2/p45JFHcsopp6R3795ZZZVV0rp164wbNy7Dhg1LixYtcvDBB5fWzk/mJDn11FPz2GOP5YwzzsjTTz+dXr165dVXX82IESPyox/9KA8//HCdc/74xz/OlVdemV/96lcZOHBgfvCDH2TDDTdMq1atMmXKlIwbNy6PPvpoKioqstFGG5Uet80226Rr16655JJLMnbs2Ky++up5/fXX88ADD2T77bfPvffeW+/37utUV1dn+PDh2WyzzUpzseflmmuuyUMPPTTPc/vtt1/69OmTU089NSeddFL69u2bgQMHZskll8zw4cPz+uuvZ8CAAfnJT35Seszxxx+fDz74IBtttFG6du2aioqKPP300/nXv/6VDTbYoHSDtIsvvjhPPPFEqdhq0aJFXnjhhTz66KNZaaWVsv3229f5tf7whz/MJptskl122aVWth122CE77bTTXOtbtWqVnXbaKbfffnuSzNdYi5tuuik1NTXZa6+9at0I8suWW265bL/99hkyZEj+8Y9/ZJdddsmBBx6Y0aNH55577sn666+fbbfdNssss0wmTJiQkSNH5rLLLiu95gsuuCBjx47N+eefnwcffDCbbrppampq8sYbb+SRRx7Ja6+9lpYtW2bZZZfNpZdemgMPPDD9+/fPwIED06ZNm4waNSrPP/981l9//fzqV7+qle3www/PkUcema222io777xzqqurM2LEiKy33np1fg+K9OvXLxUVFTn99NPzyiuvZNlll81yyy2Xn//85w1y/STp0aNHjj766FxwwQXZeOONs/POO6dJkya57777ssYaa+Tll1+e60Z186t///51XnvBBRfk9ddfzymnnJLbbrstG264YZZbbrm8++67ee655/J///d/efXVV0v/kmPTTTfNvffem/322y9bbbVVmjdvnh/84AfZdttt5ztno0aN8sc//jG77rprdt999+y8887p0qVLxowZkyeeeCLdunXLqaeeWmv9JZdcUlo7cODAdOzYMY899lg+/PDDrLnmmnnppZfmOwcAfF8pkgGAxVKLFi1y9NFH57jjjsvZZ5+dv/zlL2nevHnuvPPO3Hjjjbntttty3333Zdq0aWnbtm169uyZn/3sZ7Xmg/7xj39M165d8/e//z1XXnllVlhhhRx22GE56qijFqgM3XLLLfPOO+/kySefzH333ZfPP/88HTt2zMCBA3PkkUemZ8+epbXzm7lDhw554IEHMnjw4IwcOTJPPvlk1l577dxzzz157LHH5qtITpLddtstm2yySa6++uo8/PDDueuuu/LZZ59l6aWXTvfu3XPooYdm0KBBtTIvvfTS+fvf/55TTjklTz75ZJ544on07NkzV111Vdq2bfutFMnPPvts/ve//2W77bYrXPfkk0/O85+5J8kmm2ySPn365PDDD8/KK6+cK664InfccUemT5+e7t2754wzzsghhxxSq1D99a9/nfvuuy/PP/98Hn744TRp0iRdu3bNaaedlgMPPLD0z/oPPPDALLvssvnXv/6VJ598MjU1NVlhhRVyzDHH5Je//OU8b+72dc4+++z87W9/yw033JAJEyakffv2OeGEE/LrX//6ax8zaNCg3H777dlggw0KZ+B+WXV1dW699dZUVFRkr732Kly79957Z8iQIbnxxhuzyy67pKKiItdee2222GKL0tduTU1N6et8nXXWKT12+eWXz4gRI3LZZZfl3nvvzVVXXZXmzZtnxRVXzFFHHZWlllqqtHbnnXdOu3btctFFF+W+++7L1KlT07Vr1xx77LE56qij5tppvf/++2fGjBn505/+lBtuuCHt27fPoEGDcuyxx37tDdvmR8+ePXPFFVfk8ssvz5VXXplp06alS5cuDVokJ8nJJ5+cTp065corr8xf//rXtG3bNrvssksOOeSQDB8+fIFvLjg/WrVqlQcffDBXXXVV7r777gwZMiTV1dVp165dfvCDH+TYY4/N8ssvX1q///7755133sldd92Viy++ODNnzsxee+1VryI5mb3LeMSIETn33HPz8MMP55NPPkmHDh1yyCGHzPXcSbL55pvn3nvvzRlnnJF77703LVq0yGabbZbrrrsuhxxyyAK9FwDwfVNRWVk5979HAgCARcjgwYNz6aWX5pVXXkn79u3LHWehc9lll+Xkk0/OZZddln333bfccWggo0aNys4775wjjzxygUfuAAB8E0UyAACLvA022CAtW7bMiBEjyh1loVNVVZUNNtggn376aV5++eW5bh7Jwu/jjz9Oq1atSjvck6SysjIDBw7Mc889lwcffDAbbrhhGRMCAN8HRlsAALDIe/bZZ8sdYaHz1FNPZfTo0Rk5cmTGjx+fwYMHK5EXUXfccUcuv/zy9OvXLx07dswHH3yQkSNH5qOPPsqgQYOUyADAd0KRDAAAi6FRo0blnHPOyfLLL59f/vKXOeKII8odiXrq3bt3Hn/88Tz66KOZPHlyGjdunFVXXTXHHntsDjrooHLHAwC+J4y2AAAAAACgUKNyBwAAAAAAYOGmSAYAAAAAoJAiGQAAAACAQopkAAAAAAAKKZIBAAAAACikSAbgO1VVVZU333wzVVVV5Y4CAAANxve5wOJOkQzAd27WrFnljgAAAA3O97nA4kyRDAAAAABAIUUyAAAAAACFFMkAAAAAABRSJAMAAAAAUKhJuQPw7aqurs4nn3ySGTNmlDsK9VBRUZFll102zZo1K3cUAAAAAL7HFMmLsenTp6eysjLLLbdclltuuVRUVJQ7EvOpuro6EydOzHLLLadMBgAAAKBsjLZYjH366adZfvnl07x5cyXyIqpRo0ZZfvnl88knn5Q7CgAAAADfY4rkxVh1dXUaN25c7hgsoEaNGqWmpqbcMQAAAAD4HlMkAwAAAABQSJEMAAAAAEAhRTIAAAAAAIWalDsA5dHyr++W9fkrD+hcr8fdfPPNOeyww/Lkk09mjTXWaLA8M2fOzHnnnZdNNtkk/fr1q3XurLPOyjnnnDPPx7Vu3TpvvvnmfD3XqFGj8tRTT+XEE0+sd14AAAAA+C4pkiGzi+Q5ZfFXi+Q5/v73v2eJJZaodaxp06bz/VyjRo3KxRdfrEgGAAAAYJGhSIY6Wm+99bL00kuXOwYAAAAAfOfMSGaRttZaa+XQQw/9xuOff/55TjjhhPzgBz9Iu3bt0r1792y77bZ55plnkiQdOnRIkpxzzjlp2bJlWrZsmbPOOmu+snz88cc5+uij88Mf/jCdOnXK6quvnkGDBuWNN94orTnrrLNy8cUXJ0npeVq2bDmfrxoAAAAAvlt2JPO98Lvf/S73339/Tj755KyyyiqprKzMv//970yePDlJ8o9//CPbbbdd9t133+y3335Jkk6dOtW6xqxZszJz5sxaxxo1apRGjWb/PGby5Mlp2rRpTj755LRp0yYff/xxrrnmmvTv3z/PPvts2rZtm/322y/jxo3L7bffnhEjRnwHrxwAAAAAFpwime+FZ555Jrvvvnv233//0rHtttuu9Ov1118/yezyeIMNNpjnNVZcccW5jg0YMCC33HJLkqRHjx4599xzS+dmzZqVrbbaKj169MiQIUPyy1/+Mp07d07Hjh2T5GufBwAAAAAWNopkvhfWXXfd3HLLLVl++eWz+eabZ5111kmTJvP35T906NC5brb31bEUN9xwQ66++uq89dZb+fTTT0vHvzzeAgAAAAAWNYpkvhfOPffcdOzYMbfddlvOOOOMLLvsshk4cGBOO+20Os8o7tWrV+HN9q6++ur85je/yS9+8YuccsopadWqVRo1apTdd989U6dObaBXAgAAAADfPUUyi7QWLVpk+vTpcx2vrKys9fHSSy+dk08+OSeffHLefffdDBs2LKecckqmTp2aK6+8skGy3Hnnndl0001zzjnnlI5Nnz69NIcZAAAAABZVjcodABZEly5dMnbs2FrHHn/88VpjJb6qc+fOOeigg9K3b9+89NJLSZJmzZqloqIiVVVV9c7yxRdfpGnTprWO3XrrrZk1a1atY82aNUsSu5QBAAAAWGTYkcwiqaKiIkmy++6759BDD82xxx6b7bffPm+88Ub+/Oc/Z9lll621vn///tlmm22y5pprZplllsm///3vPPbYYznkkEOSJI0aNUqPHj0yfPjwbLHFFlluueXSoUOH0o3xkuTf//73XDOSk9nzl5s0aZKtttoqF154Yc4999z07t07zz77bK655post9xytdb37NkzSXLZZZflRz/6URo3bpx11123Qd8fAAAAAGhIimQWKXN28TZv3jxJ8pOf/CTvv/9+rrvuutx4441Zd911c9VVV2Xfffet9bhNNtkkf//733PppZdmxowZ6dKlS4499tgcddRRpTUXXHBBfvvb32aPPfbI9OnTc/zxx+fEE08snd9xxx3nmen//u//svzyy+fYY4/NJ598kquvvjoXX3xx1ltvvdxxxx0ZNGhQrfU77rhj9t9///zlL3/JWWedlZqamrlGcQAAAADAwqSisrKyptwh+HZ89NFHadu2bbljNKgTTjghV199dSZMmJAWLVqUO853ZnH8XPL9VVVVlfHjx6dLly7fq9/HAAAs3nyfCyzu7EhmkfDf//43//rXv3LLLbdk++2395cyAAAAAHyHFMksEn75y19m0qRJGThwYE4//fRyxwEAAACA7xVFMouExx9/vNwRAAAAAOB7q1G5AwAAAAAAsHBTJAMAAAAAUEiRDAAAAABAIUUyAAAAAACFFMkAAAAAABRSJAMAAAAAUKhJuQMAAAAALA7WPePgckcAGshn148qd4SFjiL5e2rp/Tcv6/MvyG/Gm2++OYcddljp44qKirRr1y7rrLNOTjjhhKy77rpJkscffzw77LBDaV3z5s3TpUuXbLPNNvnNb36Tli1b1jsDAAAAAHyfKJJZZF111VVZaaWVUl1dnQkTJuSiiy7KTjvtlMcffzwrrrhiad3pp5+ejTbaKF988UUeeeSRXHrppRk9enRGjhyZRo1MdwEAAACAb6JIZpG15pprZo011kiS9O7dOz/4wQ/Su3fvPPTQQznwwANL63r06JENNtggSbLZZpvlf//7X2655ZaMGTMmG220UVmyAwAAAMCixHZMFhvLLLNMkmTGjBmF69Zbb70kyfjx47/1TAAAAACwOLAjmUXWrFmzMnPmzNJoi1NPPTVLLbVUBgwYUPi4t99+O0my/PLLfxcxAQAAAGCRp0hmkdWvX79aH7ds2TI33nhjunbtWut4dXV1Zs6cmalTp+bhhx/Otddem44dO6ZPnz7fZVwAAAAAWGQpkllkXXvttenWrVtqamrywQcf5Kqrrsq+++6bO+64I3379i2tGzRoUK3H9e3bN+edd16WWGKJ7zoyAAAAACySFMkssnr27Fm62V6SbLHFFllzzTVzyimnZOTIkaXjZ555Zvr06ZPmzZunS5cupVnKAAAAAEDdKJJZbCyxxBJZaaWV8tJLL9U6vvLKK2fdddctUyoAAAAAWPQ1KncAaChffPFF3nrrrbRp06bcUQAAAABgsWJHMousl156KZ9//nlpRvLVV1+dyZMn55hjjil3NAAAAABYrCiSWWQdfPDBpV+3bt06q666av76179m4MCBZUwFAAAAAIufisrKyppyh+Db8dFHH6Vt27bljkED8LlkcVJVVZXx48enS5cuadGiRbnjAABAg6iqqkqbX2xT7hhAA/ns+lHljrDQMSMZAAAAAIBCimQAAAAAAAopkgEAAAAAKKRIBgAAAACgkCIZAAAAAIBCimQAAAAAAAopkhdjjRo1yqxZs8odgwVUXV2dioqKcscAAAAA4HtMkbwYW2aZZTJx4sRUVVWlpqam3HGoh+rq6kycODHLLrtsuaMAAAAA8D3WpNwB+PY0a9Ysbdq0ySeffJJPP/203HGoh4qKiiy33HJp1qxZuaMAAAAA8D2mSF7MNWrUKC1btix3DAAAAABgEWa0BQAAAAAAhRTJAAAAAAAUUiQDAAAAAFBIkQwAAAAAQCFFMgAAAAAAhRTJAAAAAAAUUiQDAAAAAFBIkQwAAAAAQCFFMgAAAAAAhRTJAAAAAAAUUiQDAAAAAFBIkQwAAAAAQCFFMgAAAAAAhRTJAAAAAAAUUiQDAAAAAFBIkQwAAAAAQCFFMgAAAAAAhRTJAAAAAAAUUiQDAAAAAFBIkQwAAAAAQCFFMgAAAAA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",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Transaction ID</th>\n",
       "      <th>Transaction Type</th>\n",
       "      <th>Transaction/AccountingDemoScope/executor</th>\n",
       "      <th>Transaction/AccountingDemoScope/asset_name</th>\n",
       "      <th>Transaction/default/SourcePortfolioId</th>\n",
       "      <th>Transaction/default/SourcePortfolioScope</th>\n",
       "      <th>Transaction/AccountingDemoScope/exposure</th>\n",
       "      <th>Transaction/default/ResultantHolding</th>\n",
       "      <th>Units</th>\n",
       "      <th>Price</th>\n",
       "      <th>Currency</th>\n",
       "      <th>Transaction Date</th>\n",
       "      <th>Settlement Date</th>\n",
       "      <th>Realised Gain Loss</th>\n",
       "      <th>0</th>\n",
       "      <th>accounting_method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2354lafjaso3432502</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>854176.00</td>\n",
       "      <td>5.32</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>-99786.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sdlfksdlfk23409235</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>153000.00</td>\n",
       "      <td>7.33</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>-13494.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sdlfksdlfk23409235</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>JustEat_LondonStockEx_J</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>JustEat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>153000.00</td>\n",
       "      <td>7.33</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>-13494.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2354lafjaso3432502</td>\n",
       "      <td>Sell</td>\n",
       "      <td>jp392431</td>\n",
       "      <td>BP_LondonStockEx_BP</td>\n",
       "      <td>UK12XC2</td>\n",
       "      <td>AccountingDemoScope</td>\n",
       "      <td>BP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>854176.00</td>\n",
       "      <td>5.32</td>\n",
       "      <td>GBP</td>\n",
       "      <td>2019-09-19 09:32:38.113000+00:00</td>\n",
       "      <td>2019-09-21 09:32:38.113000+00:00</td>\n",
       "      <td>14166.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LIFO</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Transaction ID Transaction Type  \\\n",
       "0  2354lafjaso3432502             Sell   \n",
       "1  sdlfksdlfk23409235             Sell   \n",
       "0  sdlfksdlfk23409235             Sell   \n",
       "1  2354lafjaso3432502             Sell   \n",
       "\n",
       "  Transaction/AccountingDemoScope/executor  \\\n",
       "0                                 jp392431   \n",
       "1                                 jp392431   \n",
       "0                                 jp392431   \n",
       "1                                 jp392431   \n",
       "\n",
       "  Transaction/AccountingDemoScope/asset_name  \\\n",
       "0                        BP_LondonStockEx_BP   \n",
       "1                    JustEat_LondonStockEx_J   \n",
       "0                    JustEat_LondonStockEx_J   \n",
       "1                        BP_LondonStockEx_BP   \n",
       "\n",
       "  Transaction/default/SourcePortfolioId  \\\n",
       "0                               UK12XC2   \n",
       "1                               UK12XC2   \n",
       "0                               UK12XC2   \n",
       "1                               UK12XC2   \n",
       "\n",
       "  Transaction/default/SourcePortfolioScope  \\\n",
       "0                      AccountingDemoScope   \n",
       "1                      AccountingDemoScope   \n",
       "0                      AccountingDemoScope   \n",
       "1                      AccountingDemoScope   \n",
       "\n",
       "  Transaction/AccountingDemoScope/exposure  \\\n",
       "0                                       BP   \n",
       "1                                  JustEat   \n",
       "0                                  JustEat   \n",
       "1                                       BP   \n",
       "\n",
       "   Transaction/default/ResultantHolding     Units Price Currency  \\\n",
       "0                                   NaN 854176.00  5.32      GBP   \n",
       "1                                   NaN 153000.00  7.33      GBP   \n",
       "0                                   NaN 153000.00  7.33      GBP   \n",
       "1                                   NaN 854176.00  5.32      GBP   \n",
       "\n",
       "                  Transaction Date                  Settlement Date  \\\n",
       "0 2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "1 2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "0 2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "1 2019-09-19 09:32:38.113000+00:00 2019-09-21 09:32:38.113000+00:00   \n",
       "\n",
       "   Realised Gain Loss   0 accounting_method  \n",
       "0           -99786.88 NaN              FIFO  \n",
       "1           -13494.60 NaN              FIFO  \n",
       "0           -13494.60 NaN              LIFO  \n",
       "1            14166.08 NaN              LIFO  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profit_loss_both = pd.concat([profit_loss_lifo, profit_loss_fifo]) \\\n",
    "                   .dropna(subset=[\"Realised Gain Loss\", \"Transaction ID\"], axis=0) \\\n",
    "                   .sort_values(\"accounting_method\")\n",
    "\n",
    "x = np.arange(len(profit_loss_both[\"accounting_method\"].unique()))\n",
    "gain_loss_just_eat = profit_loss_both.loc[\n",
    "    profit_loss_both[\"Transaction/AccountingDemoScope/exposure\"] == \"JustEat\", \"Realised Gain Loss\"].unique()\n",
    "gain_loss_bp = profit_loss_both.loc[\n",
    "    profit_loss_both[\"Transaction/AccountingDemoScope/exposure\"] == \"BP\", \"Realised Gain Loss\"].unique()\n",
    "width = 0.35\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "rects1 = ax.bar(x - width/2, gain_loss_just_eat, width, label='JustEat')\n",
    "rects2 = ax.bar(x + width/2, gain_loss_bp, width, label='BP')\n",
    "\n",
    "# Add some text for labels, title and custom x-axis tick labels, etc.\n",
    "ax.set_ylabel('Realised Gain/Loss (£)')\n",
    "ax.set_title('Realised Gain/Loss by Accounting Method')\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels([\"FirstInFirstOut\", \"LastInFirstOut\"])\n",
    "ax.legend()\n",
    "plt.show()\n",
    "profit_loss_both"
   ]
  }
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