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| import os, sys | |
| sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | |
| import pandas as pd | |
| from database import get_pg_engine | |
| import os | |
| os.environ["DATABASE_URL"] = "sqlite:///portfolio_db.sqlite3" | |
| engine = get_pg_engine() | |
| tickers = ['AAPL', 'MSFT', 'GOOGL', 'AMZN', 'NVDA', 'META', 'TSLA', 'JPM', 'GS', 'XOM', 'CVX', 'TLT', 'IEF', 'SHY', 'LQD', 'HYG', 'GLD', 'SLV', 'USO', 'SPY', 'QQQ', 'DIA', 'ES=F', 'NQ=F', 'GC=F', 'CL=F'] | |
| all_rets = {} | |
| for t in tickers: | |
| df = pd.read_sql("SELECT date, close_price FROM daily_prices WHERE ticker=? ORDER BY date", engine, params=(t,)) | |
| df['date'] = pd.to_datetime(df['date']) | |
| df = df.set_index('date') | |
| all_rets[t] = df['close_price'].pct_change() | |
| print(f"{t}: {len(all_rets[t].dropna())}") | |
| comb = pd.DataFrame(all_rets).dropna() | |
| print("Combined dropna shape:", comb.shape) | |