1.创建CSV数据文件

（具体文件见首页资源处）

data = {
    '日期': ['2025-01-02', '2025-01-03', '2025-01-04', '2025-01-05', '2025-01-06', '2025-01-07', '2025-01-08', '2025-01-09', '2025-01-10'],
    '开盘价': [505.00, 473.00, 461.80, 453.60, 449.20, 463.60, 467.60, 453.20, 464.20],
    '最高价': [521.00, 475.00, 462.00, 465.00, 465.40, 477.40, 473.40, 457.00, 500.00],
    '最低价': [505.00, 461.80, 449.00, 449.20, 447.00, 461.40, 450.40, 445.40, 464.20],
    '收盘价': [481.00, 461.80, 445.00, 449.20, 451.20, 461.40, 450.40, 453.20, 485.00]
}

2.绘制走势图

import pandas as pd
import matplotlib.pyplot as plt

# 定义股票数据
data = {
    '日期': ['2025-01-02', '2025-01-03', '2025-01-04', '2025-01-05', '2025-01-06', '2025-01-07', '2025-01-08', '2025-01-09', '2025-01-10'],
    '开盘价': [505.00, 473.00, 461.80, 453.60, 449.20, 463.60, 467.60, 453.20, 464.20],
    '最高价': [521.00, 475.00, 462.00, 465.00, 465.40, 477.40, 473.40, 457.00, 500.00],
    '最低价': [505.00, 461.80, 449.00, 449.20, 447.00, 461.40, 450.40, 445.40, 464.20],
    '收盘价': [481.00, 461.80, 445.00, 449.20, 451.20, 461.40, 450.40, 453.20, 485.00]
}

# 创建 DataFrame
df = pd.DataFrame(data)

# 保存到 CSV 文件
df.to_csv('stock_data.csv', index=False)

# 读取 CSV 文件中的股票数据
def read_stock_data(file_path):
    try:
        data = pd.read_csv(file_path, index_col='日期', parse_dates=True)
        print("数据读取成功！")
        return data
    except Exception as e:
        print(f"读取数据时出错：{e}")
        return None

# 绘制股票价格波动图
def plot_stock_prices(data):
    # 绘制开盘价、最高价、最低价和收盘价
    data[['开盘价', '最高价', '最低价', '收盘价']].plot(figsize=(12, 6))
    
    # 添加标题和标签
    plt.title('Stock Price Movement')
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.legend()
    
    # 显示网格
    plt.grid(True)
    
    # 显示图表
    plt.show()

# 主函数
def main():
    input_file_path = 'stock_data.csv'  # 输入文件路径
    data = read_stock_data(input_file_path)
    if data is not None:
        plot_stock_prices(data)

# 运行主函数
if __name__ == "__main__":
    main()

3.运行结果