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| import base64 | |
| import io | |
| import matplotlib.pyplot as plt | |
| import pandas as pd | |
| from concurrent.futures import ThreadPoolExecutor, as_completed | |
| import FinanceDataReader as fdr | |
| def get_stock_prices(stock_code, days): | |
| try: | |
| df = fdr.DataReader(stock_code) | |
| df = df[df.index >= df.index.max() - pd.DateOffset(days=days)] # ์ต๊ทผ days์ผ ๋ฐ์ดํฐ๋ก ์ ํ | |
| return df['Close'] | |
| except Exception as e: | |
| print(f"Failed to fetch data for {stock_code}: {e}") | |
| return None | |
| def plot_stock_prices(stock_codes, days): | |
| # ์ฃผ์ ๊ทธ๋ํ ์์ฑ์ ์ํ ๋ณ๋ ฌ ์ฒ๋ฆฌ | |
| stock_prices = {} | |
| with ThreadPoolExecutor() as executor: | |
| futures = {executor.submit(get_stock_prices, stock_code.strip(), int(days)): stock_code.strip() for stock_code in stock_codes.split(',')} | |
| for future in as_completed(futures): | |
| stock_code = futures[future] | |
| try: | |
| prices = future.result() | |
| if prices is not None: | |
| stock_prices[stock_code] = prices | |
| except Exception as e: | |
| print(f"Failed to fetch data for {stock_code}: {e}") | |
| # ๊ฐ ์ฃผ์์ ๋ํ ๊ทธ๋ํ๋ฅผ ๊ทธ๋ฆผ | |
| plt.figure(figsize=(10, 6)) | |
| for stock_code, prices in stock_prices.items(): | |
| relative_prices = prices / prices.iloc[0] # ์ฒซ ๋ฒ์งธ ๋ฐ์ดํฐ ํฌ์ธํธ๋ฅผ ๊ธฐ์ค์ผ๋ก ์๋์ ๊ฐ๊ฒฉ ๊ณ์ฐ | |
| plt.plot(prices.index, relative_prices, label=stock_code.upper()) # ์ฃผ์ ์ฝ๋๋ฅผ ๋๋ฌธ์๋ก ํ์ | |
| plt.xlabel('Date') | |
| plt.ylabel('Relative Price (Normalized to 1)') | |
| plt.title(f'Relative Stock Prices Over the Last {days} Days') | |
| plt.legend() | |
| # ๊ทธ๋ํ๋ฅผ HTML๋ก ๋ณํํ์ฌ ๋ฐํ | |
| html_graph = io.BytesIO() | |
| plt.savefig(html_graph, format='png', dpi=300) | |
| html_graph.seek(0) | |
| graph_encoded = base64.b64encode(html_graph.getvalue()).decode() | |
| graph_html = f'<img src="data:image/png;base64,{graph_encoded}"/>' | |
| return graph_html | |