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| import streamlit as st | |
| import yfinance as yf | |
| import pandas as pd | |
| # Predefined list of S&P 500 stocks for selection | |
| stocks = ['AAPL', 'MSFT', 'AMZN', 'GOOGL', 'FB', 'BRK.B', 'JNJ', 'V', 'PG', 'JPM', | |
| 'UNH', 'MA', 'INTC', 'VZ', 'HD', 'T', 'DIS', 'MRK', 'PFE', 'BAC', | |
| 'KO', 'WMT', 'MCD', 'ABT', 'CSCO', 'PEP', 'NFLX', 'XOM', 'CVX', 'NKE', | |
| 'LLY', 'ADBE', 'CMCSA', 'ORCL', 'CRM', 'TMO', 'ACN', 'ABBV', 'AVGO', 'TXN', | |
| 'COST', 'DHR', 'MDT', 'NEE', 'PYPL', 'AMGN', 'HON', 'LIN', 'PM', 'BA', | |
| 'UNP', 'IBM', 'QCOM', 'LMT', 'BMY', 'SBUX', 'MMM', 'GE', 'CAT', 'CVS', | |
| 'WFC', 'SCHW', 'RTX', 'AMT', 'GS', 'DE', 'C', 'MS', 'GILD', 'UPS', | |
| 'BLK', 'MO', 'MDLZ', 'INTU', 'TGT', 'AXP', 'ANTM', 'ISRG', 'SYK', 'CI', | |
| 'PGR', 'BKNG', 'CL', 'SPGI', 'MMC', 'BDX', 'ADP', 'CME', 'USB', 'TJX', | |
| 'ZTS', 'FIS', 'GM', 'CB', 'CHTR', 'PLD', 'SO', 'COP', 'DUK', 'EL'] | |
| # Assuming you have an updated CSV with S&P 500 averages for financial ratios | |
| sp500_averages_path = 'sp500_averages.csv' | |
| def load_sp500_averages(filepath): | |
| # Load the CSV without specifying an index column name | |
| return pd.read_csv(filepath, header=0, names=['Ratio', 'Average']).set_index('Ratio') | |
| def fetch_stock_data(ticker_symbol): | |
| # Fetch financial data for a single stock | |
| ticker = yf.Ticker(ticker_symbol) | |
| info = ticker.info | |
| pb_ratio = info.get('priceToBook') | |
| book_to_market_ratio = 1 / pb_ratio if pb_ratio and pb_ratio > 0 else None | |
| financials = { | |
| 'P/E Ratio': info.get('forwardPE'), | |
| 'P/B Ratio': pb_ratio, | |
| 'P/S Ratio': info.get('priceToSalesTrailing12Months'), | |
| 'Debt to Equity Ratio': info.get('debtToEquity'), | |
| 'Return on Equity': info.get('returnOnEquity'), | |
| 'Book-to-Market Ratio': book_to_market_ratio, | |
| } | |
| return financials | |
| def compare_to_index(stock_ratios, index_averages): | |
| comparison = {} | |
| for ratio, value in stock_ratios.items(): | |
| # Check if the ratio exists in the index_averages DataFrame | |
| if ratio in index_averages.index: | |
| average = index_averages.loc[ratio]['Average'] | |
| comparison[ratio] = 'Higher' if value > average else 'Lower' | |
| else: | |
| comparison[ratio] = 'N/A' # Ratio not available in index averages | |
| return comparison | |
| # Load S&P 500 averages | |
| sp500_averages = load_sp500_averages(sp500_averages_path) | |
| # User interface in Streamlit | |
| st.title('S&P 500 Stock Comparison Tool') | |
| # Selection of stock from predefined list | |
| ticker_symbol = st.selectbox('Select a stock', options=stocks) | |
| if ticker_symbol: | |
| with st.spinner(f'Fetching data for {ticker_symbol}...'): | |
| stock_data = fetch_stock_data(ticker_symbol) | |
| comparison = compare_to_index(stock_data, sp500_averages) | |
| st.write(f"Financial Ratios for {ticker_symbol}:") | |
| for ratio, value in stock_data.items(): | |
| status = comparison.get(ratio, 'N/A') | |
| st.write(f"{ratio}: {value} ({status} than S&P 500 average)") | |