Bloomberg Python Interop.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><a name=\"basic\"></a></p>\n",
    "## What Packages do I have Installed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alabaster==0.7.10\n",
      "anaconda-client==1.6.9\n",
      "anaconda-navigator==1.7.0\n",
      "anaconda-project==0.8.2\n",
      "asn1crypto==0.24.0\n",
      "astroid==1.6.1\n",
      "astropy==2.0.3\n",
      "attrs==17.4.0\n",
      "Babel==2.5.3\n",
      "backports.shutil-get-terminal-size==1.0.0\n",
      "beautifulsoup4==4.6.0\n",
      "bitarray==0.8.1\n",
      "bkcharts==0.2\n",
      "blaze==0.11.3\n",
      "bleach==2.1.2\n",
      "blpapi==3.9.1\n",
      "bokeh==0.12.13\n",
      "boto==2.48.0\n",
      "Bottleneck==1.2.1\n",
      "bqplot==0.11.6\n",
      "certifi==2018.1.18\n",
      "cffi==1.11.4\n",
      "chardet==3.0.4\n",
      "click==6.7\n",
      "cloudpickle==0.5.2\n",
      "clyent==1.2.2\n",
      "colorama==0.3.9\n",
      "comtypes==1.1.4\n",
      "conda==4.4.10\n",
      "conda-build==3.4.1\n",
      "conda-verify==2.0.0\n",
      "contextlib2==0.5.5\n",
      "cryptography==2.1.4\n",
      "cycler==0.10.0\n",
      "Cython==0.27.3\n",
      "cytoolz==0.9.0\n",
      "dask==0.16.1\n",
      "datashape==0.5.4\n",
      "decorator==4.2.1\n",
      "distributed==1.20.2\n",
      "docutils==0.14\n",
      "entrypoints==0.2.3\n",
      "et-xmlfile==1.0.1\n",
      "fastcache==1.0.2\n",
      "filelock==2.0.13\n",
      "Flask==0.12.2\n",
      "Flask-Cors==3.0.3\n",
      "gevent==1.2.2\n",
      "glob2==0.6\n",
      "greenlet==0.4.12\n",
      "h5py==2.7.1\n",
      "heapdict==1.0.0\n",
      "html5lib==1.0.1\n",
      "idna==2.6\n",
      "imageio==2.2.0\n",
      "imagesize==0.7.1\n",
      "ipython==6.2.1\n",
      "ipython-genutils==0.2.0\n",
      "ipywidgets==7.1.1\n",
      "isort==4.2.15\n",
      "itsdangerous==0.24\n",
      "jdcal==1.3\n",
      "jedi==0.11.1\n",
      "Jinja2==2.10\n",
      "jsonschema==2.6.0\n",
      "jupyter==1.0.0\n",
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      "jupyter-highlight-selected-word==0.2.0\n",
      "jupyter-latex-envs==1.4.6\n",
      "jupyter-nbextensions-configurator==0.4.1\n",
      "jupyterlab==0.31.4\n",
      "jupyterlab-launcher==0.10.2\n",
      "lazy-object-proxy==1.3.1\n",
      "llvmlite==0.21.0\n",
      "locket==0.2.0\n",
      "lxml==4.1.1\n",
      "MarkupSafe==1.0\n",
      "matplotlib==2.1.2\n",
      "mccabe==0.6.1\n",
      "menuinst==1.4.11\n",
      "mistune==0.8.3\n",
      "mpmath==1.0.0\n",
      "msgpack-python==0.5.1\n",
      "multipledispatch==0.4.9\n",
      "navigator-updater==0.1.0\n",
      "nbconvert==5.3.1\n",
      "nbformat==4.4.0\n",
      "networkx==2.1\n",
      "nltk==3.2.5\n",
      "nose==1.3.7\n",
      "notebook==5.4.0\n",
      "numba==0.36.2\n",
      "numexpr==2.6.4\n",
      "numpy==1.14.0\n",
      "numpydoc==0.7.0\n",
      "odo==0.5.1\n",
      "olefile==0.45.1\n",
      "openpyxl==2.4.10\n",
      "packaging==16.8\n",
      "pandas==0.22.0\n",
      "pandocfilters==1.4.2\n",
      "parso==0.1.1\n",
      "partd==0.3.8\n",
      "path.py==10.5\n",
      "pathlib2==2.3.0\n",
      "patsy==0.5.0\n",
      "pdblp==0.1.8\n",
      "pep8==1.7.1\n",
      "pickleshare==0.7.4\n",
      "Pillow==5.0.0\n",
      "pkginfo==1.4.1\n",
      "pluggy==0.6.0\n",
      "ply==3.10\n",
      "prompt-toolkit==1.0.15\n",
      "psutil==5.4.3\n",
      "py==1.5.2\n",
      "pycodestyle==2.3.1\n",
      "pycosat==0.6.3\n",
      "pycparser==2.18\n",
      "pycrypto==2.6.1\n",
      "pycurl==7.43.0.1\n",
      "pyflakes==1.6.0\n",
      "Pygments==2.2.0\n",
      "pylint==1.8.2\n",
      "pyodbc==4.0.22\n",
      "pyOpenSSL==17.5.0\n",
      "pyparsing==2.2.0\n",
      "PySocks==1.6.7\n",
      "pytest==3.3.2\n",
      "python-dateutil==2.6.1\n",
      "pytz==2017.3\n",
      "PyWavelets==0.5.2\n",
      "pywin32==222\n",
      "pywinpty==0.5\n",
      "PyYAML==3.12\n",
      "pyzmq==16.0.3\n",
      "QtAwesome==0.4.4\n",
      "qtconsole==4.3.1\n",
      "QtPy==1.3.1\n",
      "requests==2.18.4\n",
      "rope==0.10.7\n",
      "ruamel-yaml==0.15.35\n",
      "scikit-image==0.13.1\n",
      "scikit-learn==0.19.1\n",
      "scipy==1.0.0\n",
      "seaborn==0.8.1\n",
      "Send2Trash==1.4.2\n",
      "simplegeneric==0.8.1\n",
      "singledispatch==3.4.0.3\n",
      "six==1.11.0\n",
      "snowballstemmer==1.2.1\n",
      "sortedcollections==0.5.3\n",
      "sortedcontainers==1.5.9\n",
      "Sphinx==1.6.6\n",
      "sphinxcontrib-websupport==1.0.1\n",
      "spyder==3.2.6\n",
      "SQLAlchemy==1.2.1\n",
      "statsmodels==0.8.0\n",
      "sympy==1.1.1\n",
      "tables==3.4.2\n",
      "tblib==1.3.2\n",
      "terminado==0.8.1\n",
      "testpath==0.3.1\n",
      "toolz==0.9.0\n",
      "tornado==4.5.3\n",
      "traitlets==4.3.2\n",
      "traittypes==0.2.1\n",
      "typing==3.6.2\n",
      "unicodecsv==0.14.1\n",
      "urllib3==1.22\n",
      "wcwidth==0.1.7\n",
      "webencodings==0.5.1\n",
      "Werkzeug==0.14.1\n",
      "widgetsnbextension==3.1.0\n",
      "win-inet-pton==1.0.1\n",
      "win-unicode-console==0.5\n",
      "wincertstore==0.2\n",
      "wrapt==1.10.11\n",
      "xlrd==1.1.0\n",
      "XlsxWriter==1.0.2\n",
      "xlwings==0.11.5\n",
      "xlwt==1.3.0\n",
      "zict==0.1.3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are using pip version 9.0.1, however version 20.3.3 is available.\n",
      "You should consider upgrading via the 'python -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip freeze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><a name=\"explore\"></a></p>\n",
    "## Bloomberg Interop via python wrapper\n",
    "#### Accessing Bloomberg Desktop API directly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "INSTRUCTIONS FOR INSTALLING THE LIBRARY\n",
    "1. https://www.bloomberg.com/professional/support/api-library/\n",
    "- download the Python Supported Release\n",
    "\n",
    "2. go to command line and run: pip install pdblp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pdblp #pandas wrapper to Bloomberg API. also xbbg & pybbg are popular"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "pdblp.pdblp:INFO:Event Type: 'SESSION_STATUS'\n",
      "pdblp.pdblp:INFO:Message Received:\n",
      "SessionConnectionUp = {\n",
      "    server = \"localhost:8194\"\n",
      "    encryptionStatus = \"Clear\"\n",
      "    compressionStatus = \"Uncompressed\"\n",
      "}\n",
      "\n",
      "pdblp.pdblp:INFO:Event Type: 'SESSION_STATUS'\n",
      "pdblp.pdblp:INFO:Message Received:\n",
      "SessionStarted = {\n",
      "    initialEndpoints[] = {\n",
      "        initialEndpoints = {\n",
      "            address = \"localhost:8194\"\n",
      "        }\n",
      "    }\n",
      "}\n",
      "\n",
      "pdblp.pdblp:INFO:Event Type: 'SERVICE_STATUS'\n",
      "pdblp.pdblp:INFO:Message Received:\n",
      "ServiceOpened = {\n",
      "    serviceName = \"//blp/refdata\"\n",
      "}\n",
      "\n",
      "pdblp.pdblp:INFO:Event Type: 'SERVICE_STATUS'\n",
      "pdblp.pdblp:INFO:Message Received:\n",
      "ServiceOpened = {\n",
      "    serviceName = \"//blp/exrsvc\"\n",
      "}\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<pdblp.pdblp.BCon at 0x18168585a20>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "con = pdblp.BCon(debug=True, port=8194)\n",
    "con.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "con.debug = False  #turn off 'verbose' mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#historical data via 'bdh'\n",
    "tickers = ['QCOM US Equity', 'AAPL US Equity', 'XIU CN Equity']\n",
    "fields = ['PX_LAST', 'DX_SAF', 'VL158']  #borrow cost p/a and 3mo IVOL\n",
    "start = '20200105'\n",
    "end = '20200805'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = con.bdh(tickers, fields, start, end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>ticker</th>\n",
       "      <th colspan=\"3\" halign=\"left\">QCOM US Equity</th>\n",
       "      <th colspan=\"3\" halign=\"left\">AAPL US Equity</th>\n",
       "      <th colspan=\"3\" halign=\"left\">XIU CN Equity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>field</th>\n",
       "      <th>PX_LAST</th>\n",
       "      <th>DX_SAF</th>\n",
       "      <th>VL158</th>\n",
       "      <th>PX_LAST</th>\n",
       "      <th>DX_SAF</th>\n",
       "      <th>VL158</th>\n",
       "      <th>PX_LAST</th>\n",
       "      <th>DX_SAF</th>\n",
       "      <th>VL158</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>107.19</td>\n",
       "      <td>24.974</td>\n",
       "      <td>37.0650</td>\n",
       "      <td>96.190</td>\n",
       "      <td>112.592</td>\n",
       "      <td>31.4088</td>\n",
       "      <td>24.7280</td>\n",
       "      <td>75.0</td>\n",
       "      <td>29.6814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>105.61</td>\n",
       "      <td>25.143</td>\n",
       "      <td>36.6846</td>\n",
       "      <td>106.260</td>\n",
       "      <td>110.736</td>\n",
       "      <td>30.8887</td>\n",
       "      <td>24.5200</td>\n",
       "      <td>75.0</td>\n",
       "      <td>21.3565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>109.59</td>\n",
       "      <td>23.884</td>\n",
       "      <td>38.1381</td>\n",
       "      <td>108.938</td>\n",
       "      <td>114.368</td>\n",
       "      <td>34.3100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-04</th>\n",
       "      <td>110.95</td>\n",
       "      <td>23.205</td>\n",
       "      <td>37.6730</td>\n",
       "      <td>109.665</td>\n",
       "      <td>104.396</td>\n",
       "      <td>33.8754</td>\n",
       "      <td>24.7900</td>\n",
       "      <td>75.0</td>\n",
       "      <td>20.8693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-05</th>\n",
       "      <td>111.39</td>\n",
       "      <td>24.396</td>\n",
       "      <td>37.2934</td>\n",
       "      <td>110.063</td>\n",
       "      <td>108.932</td>\n",
       "      <td>32.9420</td>\n",
       "      <td>24.9977</td>\n",
       "      <td>75.0</td>\n",
       "      <td>19.4612</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ticker     QCOM US Equity                  AAPL US Equity                    \\\n",
       "field             PX_LAST  DX_SAF    VL158        PX_LAST   DX_SAF    VL158   \n",
       "date                                                                          \n",
       "2020-07-30         107.19  24.974  37.0650         96.190  112.592  31.4088   \n",
       "2020-07-31         105.61  25.143  36.6846        106.260  110.736  30.8887   \n",
       "2020-08-03         109.59  23.884  38.1381        108.938  114.368  34.3100   \n",
       "2020-08-04         110.95  23.205  37.6730        109.665  104.396  33.8754   \n",
       "2020-08-05         111.39  24.396  37.2934        110.063  108.932  32.9420   \n",
       "\n",
       "ticker     XIU CN Equity                  \n",
       "field            PX_LAST DX_SAF    VL158  \n",
       "date                                      \n",
       "2020-07-30       24.7280   75.0  29.6814  \n",
       "2020-07-31       24.5200   75.0  21.3565  \n",
       "2020-08-03           NaN   75.0      NaN  \n",
       "2020-08-04       24.7900   75.0  20.8693  \n",
       "2020-08-05       24.9977   75.0  19.4612  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Chart Prices (same axis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1816a17d710>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1816a17dfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "response.filter(like=\"PX_LAST\").plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('QCOM US Equity', 'PX_LAST'),\n",
       " ('QCOM US Equity', 'DX_SAF'),\n",
       " ('QCOM US Equity', 'VL158'),\n",
       " ('AAPL US Equity', 'PX_LAST'),\n",
       " ('AAPL US Equity', 'DX_SAF'),\n",
       " ('AAPL US Equity', 'VL158'),\n",
       " ('XIU CN Equity', 'PX_LAST'),\n",
       " ('XIU CN Equity', 'DX_SAF'),\n",
       " ('XIU CN Equity', 'VL158')]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(response.columns) #format for columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### extract one Series (column) from DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2020-07-30    24.7280\n",
       "2020-07-31    24.5200\n",
       "2020-08-03        NaN\n",
       "2020-08-04    24.7900\n",
       "2020-08-05    24.9977\n",
       "Name: (XIU CN Equity, PX_LAST), dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spycloses = response[('XIU CN Equity', 'PX_LAST')]  \n",
    "spycloses.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1816a3925f8>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1816a3ad7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "spycloses.plot()   #chart it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(spycloses)  #confirm dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "spx_df = pd.DataFrame(spycloses) #confirm to dataframe with dates as index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>XIU CN Equity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>PX_LAST</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>24.7280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>24.5200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-04</th>\n",
       "      <td>24.7900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-05</th>\n",
       "      <td>24.9977</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           XIU CN Equity\n",
       "                 PX_LAST\n",
       "date                    \n",
       "2020-07-30       24.7280\n",
       "2020-07-31       24.5200\n",
       "2020-08-03           NaN\n",
       "2020-08-04       24.7900\n",
       "2020-08-05       24.9977"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spx_df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Non-Equity Examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          ticker      field       value\n",
      "0  AUDUSD Curncy  SETTLE_DT  2021-01-27\n"
     ]
    }
   ],
   "source": [
    "# individual datapoint using 'ref' (similar to 'bdp')\n",
    "response2 = con.ref(['AUDUSD Curncy'], 'SETTLE_DT')\n",
    "print(response2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      ticker  field    value\n",
      "0  NDX Index  VL137  22.7313\n"
     ]
    }
   ],
   "source": [
    "response3 = con.ref(['NDX Index'], 'VL137')\n",
    "print(response3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22.7313"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response3.value[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = con.bsrch(\"FI:ytd_green\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BK814876 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BM910716 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ZO309983 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BK398989 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BK883764 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BM404455 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BK499158 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>BM664134 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BG345649 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BM722615 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ZO514532 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ZO813518 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>BJ482331 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>BK312429 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>BN015528 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BM627998 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ZO473417 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ZP605250 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>BG680220 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>ZO703743 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ZO425474 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ZO037312 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>BG011532 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>BK877754 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>BM341884 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>BK892754 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>ZO621438 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>BM664110 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>ZO531975 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>ZO479457 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>BJ920124 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>BK290940 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>BM235753 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>BK508613 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>BJ263136 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>BJ820609 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>BK678579 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>BJ374602 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>BJ604202 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>BH844759 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>ZO515061 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>ZP761067 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>BM607027 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>BK409403 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>BK880743 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>ZP479931 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>ZP480146 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>ZO064972 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>ZO957837 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>ZO404037 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>BM422439 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>BH811629 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>BM027057 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>ZO858908 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>BH810514 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>BK318383 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>BG070047 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>BJ676884 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>BJ691049 Corp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>ZP631688 Corp</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 0\n",
       "0    BK814876 Corp\n",
       "1    BM910716 Corp\n",
       "2    ZO309983 Corp\n",
       "3    BK398989 Corp\n",
       "4    BK883764 Corp\n",
       "5    BM404455 Corp\n",
       "6    BK499158 Corp\n",
       "7    BM664134 Corp\n",
       "8    BG345649 Corp\n",
       "9    BM722615 Corp\n",
       "10   ZO514532 Corp\n",
       "11   ZO813518 Corp\n",
       "12   BJ482331 Corp\n",
       "13   BK312429 Corp\n",
       "14   BN015528 Corp\n",
       "15   BM627998 Corp\n",
       "16   ZO473417 Corp\n",
       "17   ZP605250 Corp\n",
       "18   BG680220 Corp\n",
       "19   ZO703743 Corp\n",
       "20   ZO425474 Corp\n",
       "21   ZO037312 Corp\n",
       "22   BG011532 Corp\n",
       "23   BK877754 Corp\n",
       "24   BM341884 Corp\n",
       "25   BK892754 Corp\n",
       "26   ZO621438 Corp\n",
       "27   BM664110 Corp\n",
       "28   ZO531975 Corp\n",
       "29   ZO479457 Corp\n",
       "..             ...\n",
       "128  BJ920124 Corp\n",
       "129  BK290940 Corp\n",
       "130  BM235753 Corp\n",
       "131  BK508613 Corp\n",
       "132  BJ263136 Corp\n",
       "133  BJ820609 Corp\n",
       "134  BK678579 Corp\n",
       "135  BJ374602 Corp\n",
       "136  BJ604202 Corp\n",
       "137  BH844759 Corp\n",
       "138  ZO515061 Corp\n",
       "139  ZP761067 Corp\n",
       "140  BM607027 Corp\n",
       "141  BK409403 Corp\n",
       "142  BK880743 Corp\n",
       "143  ZP479931 Corp\n",
       "144  ZP480146 Corp\n",
       "145  ZO064972 Corp\n",
       "146  ZO957837 Corp\n",
       "147  ZO404037 Corp\n",
       "148  BM422439 Corp\n",
       "149  BH811629 Corp\n",
       "150  BM027057 Corp\n",
       "151  ZO858908 Corp\n",
       "152  BH810514 Corp\n",
       "153  BK318383 Corp\n",
       "154  BG070047 Corp\n",
       "155  BJ676884 Corp\n",
       "156  BJ691049 Corp\n",
       "157  ZP631688 Corp\n",
       "\n",
       "[158 rows x 1 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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