如何计算每个客户在Panda之前365天的运行总量

Question

我正在尝试使用panda计算前365天每个客户的运行总数，但我的代码不起作用。我的预期输出是这样的：

每日_total_per_customer1005080[/tr>50

日期		客户	rolling_total
2016-07-29	1	100
2016-08-01	1	150
2017-01-12	1	230
2017-10-23	1	180	260
2018-03-03		1	0	180
2018-03-06		1	40		220
2019-03-16	1	500
2017-04-07	2	50
2017-04-09	2	230	280
2018-02-11		2	80		360
2018年5月12日	2	0		80
2019-05-10	2	0	0

注释代码

# Parse the strings to datetime
df['date'] = pd.to_datetime(df['date'])
# Sort the dates in ASC order if not already sorted
df = df.sort_values(['customer', 'date']) 
# Group the dataframe by customer then for each group
# calculate rolling sum on 'daily_total_per_customer'
s = df.groupby('customer').rolling('365d', on='date')['daily_total_per_customer'].sum()
# Merge the result with original df
df.merge(s.reset_index(name='rolling_total'))

---

date  customer  daily_total_per_customer  rolling_total
0  2016-07-29         1                       100            100
1  2016-08-01         1                        50            150
2  2017-01-12         1                        80            230
3  2017-10-23         1                       180            260
4  2018-03-03         1                         0            180
5  2018-03-06         1                        40            220
6  2019-03-16         1                       500            500
7  2017-04-07         2                        50             50
8  2017-04-09         2                       230            280
9  2018-02-11         2                        80            360
10 2018-05-12         2                         0             80
11 2019-05-10         2                         0              0