python - 连续数据帧行之间的时间差

Question

类似于this问题，我想计算数据帧行之间的时间差。然而，与那个问题不同的是，区别应该是 groupby id。

所以敌人的例子，这个数据框:

df = pd.DataFrame(
    {'id': [6,6,6,6,6,10,10,10,10,10],
 'timestamp': ['2016-04-01 00:04:00','2016-04-01 00:04:20','2016-04-01 00:04:30',
              '2016-04-01 00:04:35','2016-04-01 00:04:54','2016-04-30 13:04:59',
              '2016-04-30 13:05:00','2016-04-30 13:05:12','2016-04-30 13:05:20',
               '2016-04-30 13:05:51']}
)
df.head()
    id        timestamp
0    6  2016-04-01 00:04:00
1    6  2016-04-01 00:04:20
2    6  2016-04-01 00:04:30
3    6  2016-04-01 00:04:35
4    6  2016-04-01 00:04:54
5   10  2016-04-30 13:04:59
6   10  2016-04-30 13:05:00
7   10  2016-04-30 13:05:12
8   10  2016-04-30 13:05:20
9   10  2016-04-30 13:05:51

然后我想为差异创建一个列 ΔT，如下所示:

df['timestamp'] = pd.to_datetime(df['timestamp'], format='%Y-%m-%d %H:%M:%S')
df['ΔT'] = df.groupby('id').index.to_series().diff().astype('timedelta64[s]')

AttributeError: 'DataFrameGroupBy' object has no attribute 'index'

预期输出:

    id        timestamp        ΔT
0    6  2016-04-01 00:04:00    0
1    6  2016-04-01 00:04:20   20
2    6  2016-04-01 00:04:30   10
3    6  2016-04-01 00:04:35    5
4    6  2016-04-01 00:04:54   19
5   10  2016-04-30 13:04:59    0
6   10  2016-04-30 13:05:00    1
7   10  2016-04-30 13:05:12   12
8   10  2016-04-30 13:05:20    8
9   10  2016-04-30 13:05:51   31

Answer 1

df.groupby('id')['timestamp'].diff().dt.total_seconds().fillna(0)