a.apply(lambda x:x-x.max())/np.timedelta64(1,'D')的问题是您试图从时间戳（即x）获取max。但是，如错误消息中所述，“'Timestamp'对象不可调用”。因此，在这种情况下，它试图告诉您，可以理解，时间戳没有函数max。您正在寻找a.max()，而不是x.max()。

数据

import pandas as pd
from datetime import datetime

data = [datetime(1997,1,1),datetime(1997,1,12),datetime(1998,5,28),
        datetime(1997,12,12),datetime(1998,1,3)]

a = pd.Series(data, index=range(1,6), name='user_id')

print(a)

1   1997-01-01
2   1997-01-12
3   1998-05-28
4   1997-12-12
5   1998-01-03
Name: user_id, dtype: datetime64[ns]

代码

# using `pd.Timedelta` avoids having to import `np`

b = (a-a.max())/pd.Timedelta(days=1)
print(b)

1   -512.0
2   -501.0
3      0.0
4   -167.0
5   -145.0
Name: user_id, dtype: float64

# use `a.max()` instead of `x.max()`:

c = a.apply(lambda x:x-a.max())/pd.Timedelta(days=1)
print(b.equals(c))

# True

# refactored solution:

d = a.sub(a.max()).dt.days
print(d)

1   -512
2   -501
3      0
4   -167
5   -145
Name: user_id, dtype: int64

# chain `.astype(float)`, if you specifically want `floats`:

print(a.sub(a.max()).dt.days.astype(float).equals(b))

# True