我正在尝试找出int
或float
加权平均datetime
字段的方法。我正在考虑将datetime
转换为int
,然后进行数学计算,然后转换回datetime
。但不知道该怎么做。非常感谢任何帮助。
我应该在这里更清楚。实际问题是做这样的事情
>>> df1 = pd.DataFrame({'Date': {0: '2016-10-11', 1: '2016-10-11', 2: '2016-10-11', 3: '2016-10-11', 4: '2016-10-11',5: '2016-10-11'}, 'Qty': {0: 100, 1: 3232, 2: 4232, 3: 4322, 4: 666, 5: 98}, 'StartTime': {0: '08:00:00.241', 1: '08:00:00.243', 2: '12:34:23.563', 3: '08:14:05.908', 4: '18:54:50.100', 5: '10:08:36.657'},'Id':{0:'abc',1:'abc',2:'bcd',3:'bcd',4:'abc',5:'bcd'}})
>>> df1
Date Id Qty StartTime
0 2016-10-11 abc 100 08:00:00.241
1 2016-10-11 abc 3232 08:00:00.243
2 2016-10-11 bcd 4232 12:34:23.563
3 2016-10-11 bcd 4322 08:14:05.908
4 2016-10-11 abc 666 18:54:50.100
5 2016-10-11 bcd 98 10:08:36.657
>>> df1['StartTime'] = pd.to_datetime(df1['Date'] + ' ' + df1['StartTime'])
>>> df1['StartTime'][0]
Timestamp('2016-10-11 08:00:00.241000')
现在我正在尝试按Id
分组,并Qty
加权StartTime
。请注意,StartTime
也包含微秒成分
即使StartTime
列的每个项目都是Timestamp
,以下内容似乎也不起作用:
>>> (df1.groupby['Id']).apply(lambda x:np.average(x['StartTime'], weights=x['Qty']))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'instancemethod' object has no attribute '__getitem__'
答案 0 :(得分:1)
您可以使用total_seconds()
为您提供一个可用于平均多个datetime
值的整数。
def avg_date(lst):
epoch = datetime.datetime(1900, 1, 1)
seconds_per_day = 3600 * 24
avg = sum((d - epoch).total_seconds() for d in lst) / len(lst)
return epoch + datetime.timedelta(avg // seconds_per_day, avg % seconds_per_day)
答案 1 :(得分:0)
您可以使用时间戳
import datetime
dt1 = datetime.datetime.now()
dt2 = datetime.datetime(1980, 1, 1)
timestamp1 = dt1.timestamp()
timestamp2 = dt2.timestamp()
timestamp_avg = (timestamp2+timestamp1)/2
dt_avg = datetime.datetime.fromtimestamp(timestamp_avg)
print(dt_avg)