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| import pandas as pd
import talib
import matplotlib.pyplot as plt
# import yfinance as yf
# 安装必要库（若未安装）
# !pip install TA-Lib yfinance matplotlib
# 加载示例数据（以苹果公司2024年数据为例）
# df = yf.download("AAPL", start="2024-01-01", end="2025-06-23")
# df = df[['Close']].rename(columns={'Close': 'close'})
# 计算14日RSI（默认参数）
rsi_period = 14
df['rsi'] = talib.RSI(df['收盘'], timeperiod=rsi_period)
# 过滤初始无效数据（前14天无法计算RSI）
valid_data = df.dropna()
plt.figure(figsize=(16, 10))
gs = plt.GridSpec(2, 1, height_ratios=[3, 1])
# 主图：价格与RSI信号线
ax1 = plt.subplot(gs[0])
ax1.plot(valid_data['收盘'], label='Close Price', color='#1f77b4', linewidth=1.5)
ax1.set_title(f'AAPL Price & RSI ({rsi_period}-day)', fontsize=14)
ax1.legend(loc='upper left')
ax1.grid(True, alpha=0.3)
# RSI副图
ax2 = plt.subplot(gs[1], sharex=ax1)
ax2.plot(valid_data['rsi'], label='RSI', color='purple', linewidth=1.2)
# 超买超卖区域填充
ax2.fill_between(valid_data.index, 70, valid_data['rsi'],
where=(valid_data['rsi'] >=70),
facecolor='red', alpha=0.2, interpolate=True)
ax2.fill_between(valid_data.index, 30, valid_data['rsi'],
where=(valid_data['rsi'] <=30),
facecolor='green', alpha=0.2, interpolate=True)
# 水平参考线
ax2.axhline(70, color='darkred', linestyle='--', alpha=0.7)
ax2.axhline(30, color='darkgreen', linestyle='--', alpha=0.7)
# 坐标轴优化
ax2.set_ylim(0, 100)
ax2.set_yticks([30, 50, 70])
ax2.grid(True, alpha=0.3)
ax2.set_ylabel('RSI', fontsize=10)
plt.tight_layout()
plt.show()
|
