python - Int/Float weighted average datetime in DataFrame -


i trying figure out way take int or float weighted average of datetime fields. thinking on lines of converting datetime int , maths , convert datetime. not sure how so. appreciated.

i should have been more clear here. actual problem this

>>> 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')

now trying groupby id , take qty weighted starttime. please note starttime has microsecond component well.
following not seem work, though each item of starttime column timestamp:

>>> (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__'

you can use total_seconds() give integer can used average multiple datetime values.

def avg_date(lst):     epoch = datetime.datetime(1900, 1, 1)     seconds_per_day = 3600 * 24     avg = sum((d - epoch).total_seconds() d in lst) / len(lst)     return epoch + datetime.timedelta(avg // seconds_per_day, avg % seconds_per_day)

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