从日期时间开始按日期分组的列的总和如何？ Python Pandas

Question

I would like to do the sum of the column duration group by date but the column begin and end are datetime in this piece of df:

begin                       end                         duration
2020-10-14 19:17:52.724020  2020-10-14 19:21:40.179003  227.45
2020-10-14 19:21:40.179003  2020-10-14 19:21:44.037103  3.86
2020-10-14 19:59:27.183161  2020-10-14 20:00:43.847816  76.66
2020-10-14 20:00:43.847816  2020-10-14 20:00:43.847822  0
2020-10-14 20:02:14.341240  2020-10-14 23:59:59.900000  14265.56
2020-10-15 00:00:00.000000  2020-10-15 05:25:32.935971  19532.94
2020-10-15 05:25:32.935971  2020-10-15 05:25:33.068959  0.13

df.info()

begin       41763 non-null  datetime64[ns] 
end         41763 non-null  datetime64[ns] 
duration    41763 non-null  float64   

The result must be:

begin         duration
2020-10-14    14,573.53
2020-10-15    19,533.07

So I tried on my all df, this but its works for certain date and no for other. Because I do the same with excel and for a date I have a different result.

import pandas as pd
import datetime

df = df.groupby(df['begin_'].dt.date)['duration_'].sum()/3600

Answer 1

You can use the method date of the datetime object. Apply it to the column and you get the date. Afterwards grouping is fine.

def reduce_to_date(value):
    return value.date()

df['begin'] = df['begin'].apply(reduce_to_date)

df.groupby('begin')['duration'].sum()/3600

Answer 2

The first step is to separate Time and Date in the timestamp you have. I give below and example where the dates are defined the same way they are defined in your dataframe.

0   2018-07-02 10:54:00 227.45
1   2018-07-02 10:54:00 3.86
2   2018-07-02 10:54:00 76.66
3   2018-07-02 10:54:00 14265.56
4   2018-07-02 10:54:00 19532.94

d ={'DATA':['2018-07-02 10:54:00','2018-07-02 10:54:00' , '2018-07-02 10:54:00' , '2018-07-02 10:54:00' ,'2018-07-02 10:54:00'],'duration': [227.45,3.86,76.66,14265.56,19532.94]}  
DF = df.assign(Date=df.Date.dt.date, Time=df.Date.dt.time, Duration = df.duration)

The next step is to groupby the way you did it, but by simple give information about which variable you group by:

DF.groupby(['Date']).sum()

which give

Date        Duration     duration
2018-07-02  34106.47    34106.47