BDS extraction

BDS.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from xbbg import blp\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BDS values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "           ticker\n",
      "0  MSFT US Equity\n",
      "1  TSLA US Equity\n"
     ]
    }
   ],
   "source": [
    "tickers  = pd.read_csv ('Tiker_list_file_name.csv') #list of indexes with first row 'ticker'\n",
    "print (tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          field\n",
      "0  CIE_DES_BULK\n"
     ]
    }
   ],
   "source": [
    "bds_fields= pd.read_csv ('BDS_fields_file_name.csv')  #list of fields from FLDS with first row 'field'\n",
    "print (bds_fields)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for field in bds_fields.field:\n",
    "    temp_data = blp.bds(tickers.ticker,field)\n",
    "    temp_data.to_csv('./folder_name/' + field +'_.csv')\n",
    "    time.sleep(10) #delay for better API connection"
   ]
  }
 ],
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