绘制列数可变的数据集的折线图

import matplotlib.pyplot as plt
import pandas as pd

def plot_variable_columns(dataframe, time_column, value_columns):
    """
    绘制列数可变的数据集的折线图
    
    :param dataframe: DataFrame, 包含数据的DataFrame
    :param time_column: str, 时间列的名称
    :param value_columns: list of str, 需要绘制的值列的名称列表
    """
    plt.figure(figsize=(10, 6))
    
    for column in value_columns:
        plt.plot(dataframe[time_column], dataframe[column], label=column)
    
    plt.xlabel(time_column)
    plt.ylabel('Values')
    plt.title('Variable Columns Line Plot')
    plt.legend()
    plt.grid(True)
    plt.show()

# 示例数据
data = {
    'Date': ['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04'],
    'A': [10, 15, 13, 17],
    'B': [5, 8, 12, 9],
    'C': [20, 22, 18, 25]
}

df = pd.DataFrame(data)
df['Date'] = pd.to_datetime(df['Date'])

# 绘制折线图
plot_variable_columns(df, 'Date', ['A', 'B', 'C'])

df.fillna(method='ffill', inplace=True)  # 前向填充缺失值

df.sort_values(by='Date', inplace=True)

fig, axes = plt.subplots(nrows=len(value_columns), ncols=1, figsize=(10, 6*len(value_columns)))
for ax, column in zip(axes, value_columns):
    ax.plot(df[time_column], df[column], label=column)
    ax.set_ylabel(column)
    ax.legend()
plt.xlabel(time_column)
plt.tight_layout()
plt.show()