如何在Pandas中使用resample或groupby对timedeltas求和？

import pandas as pd

# 创建一个包含时间序列数据的DataFrame对象
data = {'time': ['2022-01-01 12:00:00', '2022-01-01 12:01:00', '2022-01-01 12:02:00'],
        'timedelta': [pd.Timedelta(minutes=1), pd.Timedelta(minutes=2), pd.Timedelta(minutes=3)]}
df = pd.DataFrame(data)

# 将时间列设置为索引
df['time'] = pd.to_datetime(df['time'])
df.set_index('time', inplace=True)

# 使用resample方法按分钟进行重采样，并对timedeltas进行求和
resampled = df['timedelta'].resample('1Min').sum()

print(resampled)

import pandas as pd

# 创建一个包含时间序列数据的DataFrame对象
data = {'time': ['2022-01-01 12:00:00', '2022-01-01 12:01:00', '2022-01-01 12:02:00'],
        'timedelta': [pd.Timedelta(minutes=1), pd.Timedelta(minutes=2), pd.Timedelta(minutes=3)]}
df = pd.DataFrame(data)

# 将时间列设置为索引
df['time'] = pd.to_datetime(df['time'])
df.set_index('time', inplace=True)

# 使用groupby方法按分钟进行分组，并对timedeltas进行求和
grouped = df.groupby(pd.Grouper(freq='1Min'))['timedelta'].sum()

print(grouped)