{ "cells": [ { "cell_type": "code", "execution_count": 5, "id": "8ce6b023", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import yfinance as yf\n", "# extra dependencies et-xmlfile-1.1.0 openpyxl-3.1.1" ] }, { "cell_type": "code", "execution_count": 6, "id": "8304939a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sheet1\n" ] } ], "source": [ "file_path_23 = \"./data/23-138.Records.xlsx\"\n", " # skip header rows so column names align, drop all NaN rows\n", "df = pd.read_excel(file_path_23, parse_dates=True, skiprows=6).dropna(how='all')" ] }, { "cell_type": "markdown", "id": "538233a8", "metadata": {}, "source": [ "#### Setting up the Operating Pool DataFrame " ] }, { "cell_type": "code", "execution_count": 7, "id": "96dee5bc", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Account or SecurityCouponDateQuantityCost ValueMarket ValueBankAsset TypeCompanyIndustryPrivate Placement
369-200100-Neuberger IntermediateNaNNaNNaNNaNNaN<NA><NA><NA><NA>False
37Asset-Backed SecuritiesNaNNaNNaNNaNNaN<NA><NA><NA><NA>False
38CHASE FDG MTG LN 2004-1 MTG LN2.081933-12-25 00:00:006462.536462.536068.88<NA><NA><NA><NA>False
39MVW 2021-2 LLC TIMESHARE LN BK1.431939-05-20 00:00:00737880.25737679.54672033.22<NA><NA><NA><NA>False
40PFS FING CORP .77% 08-15-20260.772026-08-15 00:00:001090000.001089872.251010524.50<NA><NA><NA><NA>False
\n", "
" ], "text/plain": [ " Account or Security Coupon Date Quantity \\\n", "36 9-200100-Neuberger Intermediate NaN NaN NaN \n", "37 Asset-Backed Securities NaN NaN NaN \n", "38 CHASE FDG MTG LN 2004-1 MTG LN 2.08 1933-12-25 00:00:00 6462.53 \n", "39 MVW 2021-2 LLC TIMESHARE LN BK 1.43 1939-05-20 00:00:00 737880.25 \n", "40 PFS FING CORP .77% 08-15-2026  0.77 2026-08-15 00:00:00 1090000.00 \n", "\n", " Cost Value Market Value Bank Asset Type Company Industry \\\n", "36 NaN NaN \n", "37 NaN NaN \n", "38 6462.53 6068.88 \n", "39 737679.54 672033.22 \n", "40 1089872.25 1010524.50 \n", "\n", " Private Placement \n", "36 False \n", "37 False \n", "38 False \n", "39 False \n", "40 False " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bank_i = df[df['Account or Security'].str.contains(\"9-200100\", na=False)].index\n", "op_i = df[df['Account or Security'].str.contains(\"Operating Funds Pool\", na=False)].index\n", "op_df = df.loc[bank_i[0]:op_i[1]-1]\n", "op_df.insert(6, 'Bank', pd.NA)\n", "op_df.insert(7, 'Asset Type', pd.NA)\n", "op_df.insert(8, 'Company', pd.NA)\n", "op_df.insert(9, 'Industry', pd.NA)\n", "op_df.insert(10, 'Private Placement', False)\n", "# op_df = op_df.insert(7, 'Bank', pd.NA)\n", "op_df.head()" ] }, { "cell_type": "markdown", "id": "cc1f037f", "metadata": {}, "source": [ "#### Add the Bank and Asset Type " ] }, { "cell_type": "code", "execution_count": 8, "id": "29c95d09", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Account or SecurityCouponDateQuantityCost ValueMarket ValueBankAsset TypeCompanyIndustryPrivate Placement
369-200100-Neuberger IntermediateNaNNaNNaNNaNNaN9-200100-Neuberger Intermediate<NA><NA><NA>False
37Asset-Backed SecuritiesNaNNaNNaNNaNNaN9-200100-Neuberger IntermediateAsset-Backed Securities<NA><NA>False
38CHASE FDG MTG LN 2004-1 MTG LN2.081933-12-25 00:00:006462.536462.536068.889-200100-Neuberger IntermediateAsset-Backed Securities<NA><NA>False
39MVW 2021-2 LLC TIMESHARE LN BK1.431939-05-20 00:00:00737880.25737679.54672033.229-200100-Neuberger IntermediateAsset-Backed Securities<NA><NA>False
40PFS FING CORP .77% 08-15-20260.772026-08-15 00:00:001090000.001089872.251010524.509-200100-Neuberger IntermediateAsset-Backed Securities<NA><NA>False
\n", "
" ], "text/plain": [ " Account or Security Coupon Date Quantity \\\n", "36 9-200100-Neuberger Intermediate NaN NaN NaN \n", "37 Asset-Backed Securities NaN NaN NaN \n", "38 CHASE FDG MTG LN 2004-1 MTG LN 2.08 1933-12-25 00:00:00 6462.53 \n", "39 MVW 2021-2 LLC TIMESHARE LN BK 1.43 1939-05-20 00:00:00 737880.25 \n", "40 PFS FING CORP .77% 08-15-2026  0.77 2026-08-15 00:00:00 1090000.00 \n", "\n", " Cost Value Market Value Bank \\\n", "36 NaN NaN 9-200100-Neuberger Intermediate \n", "37 NaN NaN 9-200100-Neuberger Intermediate \n", "38 6462.53 6068.88 9-200100-Neuberger Intermediate \n", "39 737679.54 672033.22 9-200100-Neuberger Intermediate \n", "40 1089872.25 1010524.50 9-200100-Neuberger Intermediate \n", "\n", " Asset Type Company Industry Private Placement \n", "36 False \n", "37 Asset-Backed Securities False \n", "38 Asset-Backed Securities False \n", "39 Asset-Backed Securities False \n", "40 Asset-Backed Securities False " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bank_name = pd.NA\n", "asset_type = pd.NA\n", "for i in op_df.index:\n", " if np.isnan(op_df.loc[i][\"Quantity\"]):\n", " if \"9-200100\" in df.loc[i][\"Account or Security\"]:\n", " bank_name = df.loc[i][\"Account or Security\"]\n", " else:\n", " asset_type = df.loc[i][\"Account or Security\"]\n", " op_df.at[i,'Bank'] = bank_name\n", " op_df.at[i,'Asset Type'] = asset_type\n", "op_df.head()" ] }, { "cell_type": "code", "execution_count": 9, "id": "3ea40a3e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{,\n", " 'Account Totals',\n", " 'Account Totals - Allspring Conservative Income Fund',\n", " 'Account Totals - Allspring Short Duration',\n", " 'Account Totals - Galliard Capital',\n", " 'Account Totals - Income Research Intermediate',\n", " 'Account Totals - Income Research Short Duration',\n", " 'Account Totals - JP Morgan Managed Reserves ',\n", " 'Account Totals - Neuberger Berman Enhanced Cash',\n", " 'Account Totals - Neuberger Intermediate',\n", " 'Account Totals - Northern Trust UI Short Duration',\n", " 'Asset Backed Securities',\n", " 'Asset-Backed Securities',\n", " 'Cash & Cash Equivalents',\n", " 'Commercial Mortgage Backed Securities',\n", " 'Commercial Paper',\n", " 'Corporate Bonds',\n", " 'International Government Bonds',\n", " 'Municipal Bonds',\n", " 'U.S. Agency Bonds',\n", " 'U.S. Treasury Securities'}" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_asset_types = set([op_df.loc[i]['Asset Type'] for i in op_df.index]);all_asset_types" ] }, { "cell_type": "markdown", "id": "274d0b39", "metadata": {}, "source": [ "#### First, we just check the corperate bonds " ] }, { "cell_type": "code", "execution_count": 10, "id": "fe124c92", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Corperate Bond Totals\n", "Cost Value\t $1,020,500,769.44\n", "Market Value\t $985,000,673.71\n" ] } ], "source": [ "cb_df = op_df[op_df['Asset Type'].str.contains(\"Corporate Bonds\", na=False)]\n", "print(\"Corperate Bond Totals\")\n", "print(\"Cost Value\\t\",'${:,.2f}'.format(cb_df.sum(numeric_only=True)[\"Cost Value\"]))\n", "print(\"Market Value\\t\",'${:,.2f}'.format(cb_df.sum(numeric_only=True)[\"Market Value\"]))" ] }, { "cell_type": "markdown", "id": "d4aba4d7", "metadata": {}, "source": [ "Yup, you read that right" ] }, { "cell_type": "markdown", "id": "9879b032", "metadata": {}, "source": [ "##### get company name\n", "+ Parse our 'PVTPL', which is an abreviation for privatly placed https://www.investopedia.com/terms/p/privateplacement.asp\n", "+ Remove everything after and including the tokens ```['%']```\n", "+ Remove everything after `[\" CAP\", \" INC\", \" FDG\", \" CORP\", \" CO\", \" LLC\", \" CR\"]`\n", "+ Add the company names to a set\n", "+ Map different semantic names to the same syntax for the same company" ] }, { "cell_type": "code", "execution_count": 11, "id": "d78a9733", "metadata": {}, "outputs": [], "source": [ "company_name_dict = {\n", " \"AMERICAN EXPRESS\" : \"AMERICAN EXPRESS CO\",\n", " 'AIG GLOBAL' : \"AMERICAN INTL GROUP INC\",\n", " \"ANHEUSER-BUSCH\" : \"ANHEUSER-BUSCH CO\",\n", " \"APTIV\" : \"APTIV CO\",\n", " \"ASTRAZENECA\" : \"ASTRAZENECA PLC\",\n", " \"AUSTRALIA & NEW\" : \"AUSTRALIA & NEW ZEALAND BKG GR\",\n", " \"BAE SYS\" : \"BAE SYS PLC\",\n", " \"BANCO SANTANDER\" : \"BANCO SANTANDER SA\",\n", " \"BANK MONTREAL\" : \"BANK OF MONTREAL\",\n", " \"BANK OF MONTREAL\" : \"BANK OF MONTREAL\",\n", " \"BK MONTREAL\" : \"BANK OF MONTREAL\",\n", " \"BANK NOVA SCOTIA\" : \"BANK OF NOVA SCOTIA\",\n", " \"BANK OF NOVA SCOTIA\" : \"BANK OF NOVA SCOTIA\",\n", " \"BANK AMER\" : \"BANK OF AMERICA CO\",\n", " \"BAXTER INT\" : \"BAXTER INTERNATIONAL INC\",\n", " \"BAYER US FIN\" : \"BAYER US FINANCE LLC\",\n", " \"BB&T\" : \"BB&T CO\",\n", " \"BLACKSTONE\" : \"BLACKSTONE\",\n", " \"BMW\" : \"BMW\",\n", " \"BNP PARIBAS\" : \"BNP PARIBAS\",\n", " \"BRIGHTHOUSE\" : \"BRIGHTHOUSE\",\n", " \"BRISTOL MYERS SQUIBB\" : \"BRISTOL MYERS SQUIBB CO\",\n", " \"BRISTOL-MYERS SQUIBB\" : \"BRISTOL MYERS SQUIBB CO\",\n", " \"CANADIAN IMPERIAL BK\" : \"CANADIAN IMPERIAL BK CO\",\n", " \"CAPITAL ONE\" : \"CAPITAL ONE FINL CO\",\n", " \"CATERPILLAR FINL\" : \"CATERPILLAR FINL\",\n", " \"CENTERPOINT ENERGY\" : \"CENTERPOINT ENERGY INC\",\n", " \"CHEVRON U S A\" : \"CHEVRON CO\",\n", " \"CREDIT AGRICOLE\" : \"CREDIT AGRICOLE\",\n", " \"CREDIT SUISSE\" : \"CREDIT SUISSE GROUP AG\",\n", " \"CROWN CASTLE INTL\" : \"CROWN CASTLE INTL\",\n", " \"DAIMLER\" : \"DAIMLER\",\n", " \"DELTA AIR LINES\" : \"DELTA AIR LINES\",\n", " \"DTE E\" : \"DTE ELEC\",\n", " \"DUKE ENERGY\" : \"DUKE ENERGY CO\",\n", " \"DOWDUPONT INC\" : \"DUPONT DE NEMOURS INC\",\n", " \"ENTERGY\" : \"ENTERGY CO\",\n", " \"EQUITABLE FINL LIFE\" : \"EQUITABLE FINL LIFE GLOBAL FDG\",\n", " \"ESC CB LEHMAN BROS\" : \"ESC LEHMAN BROTH HLD INC\",\n", " \"FIFTH THIRD BANCORP\" : \"FIFTH THIRD BANCORP\",\n", " \"FLORIDA P\" : \"FLORIDA POWER & LIGHT CO\",\n", " \"GENERAL MTRS\" : \"GENERAL MOTORS\",\n", " \"GENERAL MOTORS\" : \"GENERAL MOTORS\",\n", " \"HEWLETT PACKARD\" : \"HEWLETT PACKARD ENTERPRISE CO\",\n", " \"HP INC\" : \"HEWLETT PACKARD ENTERPRISE CO\",\n", " \"HUNTINGTON\" : \"HUNTINGTON NATL BK MD\",\n", " \"JACKSON FINANCIAL INC\" : \"JACKSON NATIONAL LIFE GL\",\n", " \"JPM CHASE\" : \"JPMORGAN CHASE & CO\",\n", " \"KINDER MORGAN\" : \"KINDER MORGAN INC\",\n", " \"LLOYDS BKG\" : \"LLOYDS BANKING GROUP PLC FORME\",\n", " \"MACQUARIE\" : \"MACQUARIE BK LTD\",\n", " \"MIZUHO\" : \"MIZUHO CO\",\n", " \"MONDELEZ INT\" : \"MONDELEZ INTERNATIONAL INC\",\n", " \"MORGAN STANLEY\" : \"MORGAN STANLEY\",\n", " \"NATIONAL AUSTRALIA B\" : \"NATIONAL AUSTRALIA BANK\",\n", " \"NATIONWIDE BLDG SOC\" : \"NATIONWIDE BLDG SOCIETY\",\n", " \"NATIONAL BANK OF CANADA\" : \"NATIONAL BANK OF CANADA\",\n", " \"NATL BK CDA\" : \"NATIONAL BANK OF CANADA\",\n", " \"NATWEST M\" : \"NATWEST MARKETS PLC\",\n", " \"NEXTERA ENERGY\" : \"NEXTERA ENERGY CAP\",\n", " \"NORDEA BANK\" : \"NORDEA BANK\",\n", " \"NORTHWESTERN\" : \"NORTHWESTERN MUT\",\n", " \"NXP B V\" : \"NXP B V\",\n", " \"PHILLIPS 66\" : \"PHILLIPS 66\",\n", " \"PRINCIPAL LIFE GLOBAL\" : \"PRINCIPAL LIFE GLOBAL FDG\",\n", " \"PROTECTIVE LIFE G\" : \"PROTECTIVE LIFE GLOBAL\",\n", " \"PUBLIC SVC\" : \"PUBLIC SERVICE ELECTRIC & GAS\",\n", " \"RABOBANK NEDERLAND\" : \"RABOBANK NEDERLAND\",\n", " \"ROCHE H\" : \"ROCHE HOLDINGS INC\",\n", " \"ROPER \" : \"ROPER TECHNOLOGIES INC\",\n", " \"ROYAL BANK OF CANADA\" : \"ROYAL BANK OF CANADA\",\n", " \"ROYAL BK CDA\" : \"ROYAL BANK OF CANADA\",\n", " \"SCHLUMBERGER\" : \"SCHLUMBERGER\", \n", " \"SIEMENS FINANCIERINGSMAA\" : \"SIEMENS FINANCIERINGSMAATSCHAP\",\n", " \"SIMON PPTY GROUP\" : \"SIMON PPTY GROUP\",\n", " \"STATE STR\" : \"STATE STREET CO\",\n", " \"SUMITOMO MITSUI\" : \"SUMITOMO MITSUI BANKING\",\n", " \"SWEDBANK AB\" : \"SWEDBANK AB\",\n", " \"TORONTO DOMINION B\" : \"TORONTO DOMINION BANK\",\n", " \"TOYOTA M\" : \"TOYOTA MOTOR\",\n", " \"TRANS-CDA PIPELINES\" : \"TRANS-CDA PIPELINES\",\n", " \"TRUIST \" : \"TRUIST BANK\",\n", " \"TSMC \" : \"TSMC GLOBAL LTD\",\n", " \"U S B\" : \"U S BANCORP\",\n", " \"UBS \" : \"UBS AG LONDON\",\n", " \"VENTAS REALTY\" : \"VENTAS REALTY LP\",\n", " \"VOLKSWAGEN GROUP\" : \"VOLKSWAGEN GROUP\",\n", " \"WESTPAC B\" : \"WESTPAC BANKING\",\n", "}" ] }, { "cell_type": "code", "execution_count": 12, "id": "659c0ba7", "metadata": {}, "outputs": [], "source": [ "company_names = set()\n", "for i in cb_df.index:\n", " # Set the Company to be cleaned\n", " cb_df.at[i,'Company'] = cb_df.at[i,'Account or Security']\n", " if not np.isnan(cb_df.at[i,'Quantity']):\n", " # clean private placement\n", " for prefix in [\"PVTPL\", \"PVPTL\", \"PVYPL\", \"PVT PL\", \"PVPTL\"]:\n", " if prefix in cb_df.loc[i][\"Company\"]:\n", " cb_df.at[i,'Private Placement'] = True\n", " cb_df.at[i,'Company'] = cb_df.at[i,'Company'][6:].strip()\n", " for end in [\" CAP\", \" INC\", \" FDG\", \" CORP\", \" CO\", \" LLC\", \" CR\", \" SR\", \" A/S\", \" LP\", \" ASA\", \" LTD\", ]:\n", " if end in cb_df.at[i, \"Company\"]:\n", " cb_df.at[i, \"Company\"] = cb_df.at[i, 'Company'].split(end)[0].strip()+\" \"+end\n", " for token in ['%']:\n", " if token in cb_df.at[i, \"Company\"]:\n", " # get everythng before the token, then get eveything before the last space\n", " cb_df.at[i, \"Company\"] = cb_df.at[i, \"Company\"].split(token)[0].rsplit(' ', 1)[0].strip()\n", " for key, value in company_name_dict.items():\n", " if key in cb_df.at[i, \"Company\"]:\n", " cb_df.at[i, \"Company\"] = value\n", " company_names.add(cb_df.at[i, \"Company\"])\n", " else:\n", " cb_df.drop(i, axis=0)\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "0ba92284", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "408" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(company_names)" ] }, { "cell_type": "markdown", "id": "6accaca4", "metadata": {}, "source": [ "It looks like we are invested in 408 companies" ] }, { "cell_type": "code", "execution_count": 14, "id": "e7e06dfe", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Account or SecurityCouponDateQuantityCost ValueMarket ValueBankAsset TypeCompanyIndustryPrivate Placement
103Corporate BondsNaNNaNNaNNaNNaN9-200100-Neuberger IntermediateCorporate BondsCorporate Bonds<NA>False
104ABBVIE INC 2.6% DUE 11-21-20242.62024-11-21 00:00:001065000.01135158.131030877.869-200100-Neuberger IntermediateCorporate BondsABBVIE INC<NA>False
105ABBVIE INC 2.95% DUE2.952026-11-21 00:00:00495000.0545836.80469035.559-200100-Neuberger IntermediateCorporate BondsABBVIE INC<NA>False
106AERCAP IRELAND CAP / GLOBA 3.032028-10-29 00:00:00440000.0439199.20370620.299-200100-Neuberger IntermediateCorporate BondsAERCAP IRELAND CAP<NA>False
107AERCAP IRELAND CAP / GLOBA3.561932-01-30 00:00:00430000.0428383.20344211.289-200100-Neuberger IntermediateCorporate BondsAERCAP IRELAND CAP<NA>False
....................................
2706UBS AG LONDON BRH NT FLTG RATE1.392024-08-09 00:00:001766000.01766000.001754003.409-200100-JP Morgan Managed ReservesCorporate BondsUBS AG LONDON<NA>False
2707UBS GROUP FDG SWITZ AG NT FLTG2.362023-08-15 00:00:002000000.01999460.001999374.249-200100-JP Morgan Managed ReservesCorporate BondsUBS AG LONDON<NA>False
2708UNITED PARCEL SVC INC 2.45% DU2.452022-10-01 00:00:00145000.0148575.70144922.719-200100-JP Morgan Managed ReservesCorporate BondsUNITED PARCEL SVC INC<NA>False
2709WESTPAC BKG CORP 2.0% DUE 01-122023-01-13 00:00:0072000.073785.6071637.739-200100-JP Morgan Managed ReservesCorporate BondsWESTPAC BANKING<NA>False
2710WESTPAC BKG CORP 2.75% DUE 01-2.752023-01-11 00:00:002497000.02589713.612492680.549-200100-JP Morgan Managed ReservesCorporate BondsWESTPAC BANKING<NA>False
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1222 rows × 11 columns

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" ], "text/plain": [ " Account or Security Coupon Date Quantity \\\n", "103 Corporate Bonds NaN NaN NaN \n", "104 ABBVIE INC 2.6% DUE 11-21-2024 2.6 2024-11-21 00:00:00 1065000.0 \n", "105 ABBVIE INC 2.95% DUE  2.95 2026-11-21 00:00:00 495000.0 \n", "106 AERCAP IRELAND CAP / GLOBA 3.0 3 2028-10-29 00:00:00 440000.0 \n", "107 AERCAP IRELAND CAP / GLOBA  3.56 1932-01-30 00:00:00 430000.0 \n", "... ... ... ... ... \n", "2706 UBS AG LONDON BRH NT FLTG RATE 1.39 2024-08-09 00:00:00 1766000.0 \n", "2707 UBS GROUP FDG SWITZ AG NT FLTG 2.36 2023-08-15 00:00:00 2000000.0 \n", "2708 UNITED PARCEL SVC INC 2.45% DU 2.45 2022-10-01 00:00:00 145000.0 \n", "2709 WESTPAC BKG CORP 2.0% DUE 01-1 2 2023-01-13 00:00:00 72000.0 \n", "2710 WESTPAC BKG CORP 2.75% DUE 01- 2.75 2023-01-11 00:00:00 2497000.0 \n", "\n", " Cost Value Market Value Bank \\\n", "103 NaN NaN 9-200100-Neuberger Intermediate \n", "104 1135158.13 1030877.86 9-200100-Neuberger Intermediate \n", "105 545836.80 469035.55 9-200100-Neuberger Intermediate \n", "106 439199.20 370620.29 9-200100-Neuberger Intermediate \n", "107 428383.20 344211.28 9-200100-Neuberger Intermediate \n", "... ... ... ... \n", "2706 1766000.00 1754003.40 9-200100-JP Morgan Managed Reserves \n", "2707 1999460.00 1999374.24 9-200100-JP Morgan Managed Reserves \n", "2708 148575.70 144922.71 9-200100-JP Morgan Managed Reserves \n", "2709 73785.60 71637.73 9-200100-JP Morgan Managed Reserves \n", "2710 2589713.61 2492680.54 9-200100-JP Morgan Managed Reserves \n", "\n", " Asset Type Company Industry Private Placement \n", "103 Corporate Bonds Corporate Bonds False \n", "104 Corporate Bonds ABBVIE INC False \n", "105 Corporate Bonds ABBVIE INC False \n", "106 Corporate Bonds AERCAP IRELAND CAP False \n", "107 Corporate Bonds AERCAP IRELAND CAP False \n", "... ... ... ... ... \n", "2706 Corporate Bonds UBS AG LONDON False \n", "2707 Corporate Bonds UBS AG LONDON False \n", "2708 Corporate Bonds UNITED PARCEL SVC INC False \n", "2709 Corporate Bonds WESTPAC BANKING False \n", "2710 Corporate Bonds WESTPAC BANKING False \n", "\n", "[1222 rows x 11 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cb_df" ] }, { "cell_type": "markdown", "id": "8b78d9cd", "metadata": {}, "source": [ "##### get ticker" ] }, { "cell_type": "code", "execution_count": 53, "id": "6fe3d0df", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WARNING: No decryption keys could be extracted from JS file. Falling back to backup decrypt methods.\n", "Drug Manufacturers—General\n" ] } ], "source": [ "# Replace \"company_name\" with the name of the company you're searching for\n", "company_name = \"ABBV\"\n", "\n", "# Search for the company on Yahoo Finance\n", "search_results = yf.Tickers(company_name)\n", "\n", "# Get the ticker symbol for the first result\n", "print (search_results.tickers['ABBV'].info['industry'])\n", "\n", "# print(ticker)" ] }, { "cell_type": "code", "execution_count": null, "id": "db95aa9c", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.6" }, "vscode": { "interpreter": { "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1" } } }, "nbformat": 4, "nbformat_minor": 5 }