Python pandas - timeseries合并两个具有不同时间戳的df，并用最后的值重新填充丢失的时间戳

import pandas as pd

# 创建两个示例DataFrame
df1 = pd.DataFrame({'timestamp': ['2022-01-01 00:00:00', '2022-01-01 00:10:00'],
                    'value1': [1, 2]})
df2 = pd.DataFrame({'timestamp': ['2022-01-01 00:05:00', '2022-01-01 00:15:00'],
                    'value2': [3, 4]})

# 将时间戳列转换为datetime类型
df1['timestamp'] = pd.to_datetime(df1['timestamp'])
df2['timestamp'] = pd.to_datetime(df2['timestamp'])

# 合并两个DataFrame
merged_df = pd.merge(df1, df2, on='timestamp', how='outer')

# 用最后的值填充缺失的时间戳
merged_df['value1'] = merged_df['value1'].fillna(method='ffill')
merged_df['value2'] = merged_df['value2'].fillna(method='ffill')

print(merged_df)

            timestamp  value1  value2
0 2022-01-01 00:00:00     1.0     NaN
1 2022-01-01 00:05:00     1.0     3.0
2 2022-01-01 00:10:00     2.0     3.0
3 2022-01-01 00:15:00     2.0     4.0