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Python FinMind Stock kline
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| import requests | |
| import pandas as pd | |
| import plotly.graph_objects as go | |
| from plotly.subplots import make_subplots | |
| from datetime import datetime | |
| # ====== 設定區 ====== | |
| token = "" # ←請填入你的 FinMind API token | |
| start_date = "2025-01-01" | |
| end_date = datetime.today().strftime('%Y-%m-%d') | |
| stock_ids = [ | |
| "2330", "2317", "2454", "2344", | |
| "3036", "3260", "2408", "3231", | |
| "3293", "2337", "6531", "4973" | |
| ] | |
| stock_names = { | |
| "2330": "台積電", | |
| "2317": "鴻海", | |
| "2454": "聯發科", | |
| "2344": "華邦電", | |
| "3036": "文曄", | |
| "3260": "威剛", | |
| "2408": "南亞科", | |
| "3231": "緯創", | |
| "3293": "鈊象", | |
| "2337": "旺宏", | |
| "6531": "AP Memory", | |
| "4973": "廣穎電通" | |
| } | |
| # ====== 建立 3x4 子圖 ====== | |
| rows, cols = 3, 4 | |
| fig = make_subplots( | |
| rows=rows, cols=cols, | |
| shared_xaxes=False, | |
| shared_yaxes=False, | |
| subplot_titles=[stock_names.get(sid, sid) for sid in stock_ids], | |
| column_widths=[1/cols]*cols, | |
| row_heights=[1/rows]*rows, | |
| vertical_spacing=0.07, | |
| horizontal_spacing=0.05 | |
| ) | |
| # ====== 抓資料並畫圖 ====== | |
| valid_stocks = [] | |
| url = "https://api.finmindtrade.com/api/v4/data" | |
| for idx, stock_id in enumerate(stock_ids): | |
| params = { | |
| "dataset": "TaiwanStockPrice", | |
| "data_id": stock_id, | |
| "start_date": start_date, | |
| "end_date": end_date, | |
| "token": token | |
| } | |
| resp = requests.get(url, params=params, verify=False) | |
| data = resp.json() | |
| df = pd.DataFrame(data.get("data", [])) | |
| df.dropna(subset=["open", "max", "min", "close"], inplace=True) | |
| df = df[(df["open"] > 0) & (df["close"] > 0)] | |
| if df.empty or "date" not in df.columns: | |
| print(f"[!] {stock_id} 無資料或格式錯誤") | |
| continue | |
| # 計算均線 | |
| df["MA5"] = df["close"].rolling(window=5).mean() | |
| df["MA20"] = df["close"].rolling(window=20).mean() | |
| row = idx // cols + 1 | |
| col = idx % cols + 1 | |
| # K 線 | |
| fig.add_trace( | |
| go.Candlestick( | |
| x=df['date'], | |
| open=df['open'], | |
| high=df['max'], | |
| low=df['min'], | |
| close=df['close'], | |
| name=stock_names.get(stock_id, stock_id), | |
| showlegend=False, | |
| increasing_line_color="red", # 收漲 → 紅色 | |
| decreasing_line_color="green" # 收跌 → 綠色 | |
| ), | |
| row=row, | |
| col=col | |
| ) | |
| # 5日均線 | |
| fig.add_trace( | |
| go.Scatter( | |
| x=df['date'], | |
| y=df['MA5'], | |
| mode="lines", | |
| line=dict(color="orange", width=1), | |
| name="MA5", | |
| showlegend=False | |
| ), | |
| row=row, | |
| col=col | |
| ) | |
| # 20日均線 | |
| fig.add_trace( | |
| go.Scatter( | |
| x=df['date'], | |
| y=df['MA20'], | |
| mode="lines", | |
| line=dict(color="blue", width=1), | |
| name="MA20", | |
| showlegend=False | |
| ), | |
| row=row, | |
| col=col | |
| ) | |
| valid_stocks.append(stock_id) | |
| # ====== 關閉所有有效子圖的 Range Slider ====== | |
| for i in range(1, len(valid_stocks) + 1): | |
| fig.layout[f'xaxis{i}'].rangeslider.visible = False | |
| # ====== 圖表美化 ====== | |
| fig.update_layout( | |
| height=900, | |
| width=1600, | |
| title_text="台股 12 檔股票 K 線圖 + MA5/MA20（資料來源：FinMind）", | |
| showlegend=False, | |
| margin=dict(t=100, b=50) | |
| ) | |
| fig.write_html("stock_kline_3x4.html", auto_open=True) | |
| # ====== 抓資料並計算週漲幅 ====== | |
| weekly_changes = pd.DataFrame() | |
| for stock_id in stock_ids: | |
| params = { | |
| "dataset": "TaiwanStockPrice", | |
| "data_id": stock_id, | |
| "start_date": start_date, | |
| "end_date": end_date, | |
| "token": token | |
| } | |
| resp = requests.get(url, params=params, verify=False) | |
| data = resp.json() | |
| df = pd.DataFrame(data.get("data", [])) | |
| if df.empty or "date" not in df.columns: | |
| print(f"[!] {stock_id} 無資料或格式錯誤") | |
| continue | |
| df["date"] = pd.to_datetime(df["date"]) | |
| df = df.set_index("date") | |
| # 取每週最後一個收盤價 | |
| weekly_close = df["close"].resample("W").last() | |
| # 計算週漲幅 (%) | |
| weekly_return = weekly_close.pct_change() * 100 | |
| weekly_return.name = stock_names.get(stock_id, stock_id) | |
| # 合併到表格 | |
| weekly_changes = pd.concat([weekly_changes, weekly_return], axis=1) | |
| # ====== 美化輸出 ====== | |
| weekly_changes = weekly_changes.round(2) | |
| weekly_changes.index.name = "date" # 🔹 指定 index 名稱，避免 KeyError | |
| # 彩色 HTML 表格函式 | |
| def highlight_table(val): | |
| try: | |
| num = float(val) | |
| num_fmt = f"{num:.2f}" | |
| if num > 0: | |
| return f'<td style="color:red;font-weight:bold;">{num_fmt}</td>' | |
| elif num < 0: | |
| return f'<td style="color:green;font-weight:bold;">{num_fmt}</td>' | |
| else: | |
| return f'<td style="color:black;">{num_fmt}</td>' | |
| except: | |
| return f"<td>{val}</td>" | |
| # 建立 HTML 表格 | |
| html_rows = [] | |
| # 加上表頭 | |
| header = ["日期"] + list(weekly_changes.columns) | |
| html_header = "<tr>" + "".join([f"<th>{col}</th>" for col in header]) + "</tr>" | |
| html_rows.append(html_header) | |
| # 內容 | |
| for idx, row in weekly_changes.reset_index().iterrows(): | |
| html_cells = [f"<td>{row['date'].strftime('%Y-%m-%d')}</td>"] | |
| for val in row[1:]: | |
| html_cells.append(highlight_table(val)) | |
| html_rows.append("<tr>" + "".join(html_cells) + "</tr>") | |
| # 組合 HTML | |
| html_custom = ( | |
| "<table border='1' style='border-collapse:collapse; text-align:center;'>" | |
| "<caption style='caption-side:top; font-weight:bold; font-size:16px;'>每週漲幅 (%)</caption>" | |
| + "".join(html_rows) + | |
| "</table>" | |
| ) | |
| # 輸出 HTML 檔 | |
| html_path = "weekly_changes.html" | |
| with open(html_path, "w", encoding="utf-8") as f: | |
| f.write(html_custom) |
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