How to sum up the power and time

Question

I have a dictionary data in which it is in form of dictionary within dictionary

{

{pw : 0.12345 , datetime.datetime(2022, 6, 14, 13, 10, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 13, 20, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 13, 43, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 14, 11, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 14, 14, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 14, 21, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 15, 09, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 15, 12, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 15, 40, 27)}

}

How to do I sum the data of both column based on hourly

I want to do like this -- Taking first hour

{pw : 0.12345 , datetime.datetime(2022, 6, 14, 13, 10, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 13, 20, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 13, 43, 27)},

Sum of pw : 0.12345 + 0.12345 + 0.12345

Sum of start : datetime.datetime(2022, 6, 14, 13, 10, 27) + datetime.datetime(2022, 6, 14, 13, 20, 27) + datetime.datetime(2022, 6, 14, 13, 43, 27)

Next sum I need to do this

{pw : 0.12345 , datetime.datetime(2022, 6, 14, 14, 11, 27)},
{pw : 0.12345 , datetime.datetime(2022, 6, 14, 14, 14, 27)}

Sum of pw : 0.12345 + 0.12345 Sum of start : datetime.datetime(2022, 6, 14, 14, 11, 27) + datetime.datetime(2022, 6, 14, 14, 14, 27)

More details on : datatime.datetime( YYYY , MM , DD , HH , MM , SS )

Final output

0.3735 , datetime.datetime(2022, 6, 14, 13, 10, 27) + datetime.datetime(2022, 6, 14, 13, 20, 27) + datetime.datetime(2022, 6, 14, 13, 43, 27)
0.249  , datetime.datetime(2022, 6, 14, 14, 11, 27) + datetime.datetime(2022, 6, 14, 14, 14, 27)
0.498  , ....

Start and End of date time

        Start                                             End 
datetime.datetime(2022, 6, 14, 13, 10, 27) , datetime.datetime(2022, 6, 14, 13, 43, 27)
    
datetime.datetime(2022, 6, 14, 14, 11, 27) , datetime.datetime(2022, 6, 14, 14, 14, 27)
    
datetime.datetime(2022, 6, 14, 15, 03, 27) ,  datetime.datetime(2022, 6, 14, 15, 40, 27)

So only difference is hour, so working `df.groupby('start')['pw'].sum()` ? Or need `df.groupby(pd.Grouper(key='start', freq='H'))['pw'].sum()` ? — jezrael, Oct 08 '22 at 07:07
@jezrael I have updated the question can you check. I want to sum `pw` and `datetime` — yyy62103, Oct 08 '22 at 07:15
@jezrael : I have added output .. But unable to calculate the date time .. checking how to sum HH , MM , SS — yyy62103, Oct 08 '22 at 07:23
`But unable to calculate the date time` - Yop, it is impossible. — jezrael, Oct 08 '22 at 07:23
@jezrael : I am using this to calculate : https://stackoverflow.com/questions/28988281/how-to-add-two-datetime-datetime-objects — yyy62103, Oct 08 '22 at 07:24
Do you read first sentence? `Agreeing with the previous poster, there isn't a meaningful way to add two datetimes` — jezrael, Oct 08 '22 at 07:26
hmmm, I have data in question only. So can you change input data with `end` datetimes and add expected output? — jezrael, Oct 08 '22 at 07:27
@jezrael : I have added start and end time may be this will help you to calculate the sum — yyy62103, Oct 08 '22 at 07:32
I ma confused more, it belongs to input data? Is possible remove part of question for add datetimes (what is impossible) ? And add expected ouput? — jezrael, Oct 08 '22 at 07:34
I understand what is grouping by hour, but no idea how is converted datetimes, because sum not possible. — jezrael, Oct 08 '22 at 07:35
@jezrael : At least based on datetime can you calculate sum of pw. That is also fine for me — yyy62103, Oct 08 '22 at 09:54
try `df1 = df.groupby(pd.Grouper(key='start', freq='H'))['pw'].sum().reset_index()` — jezrael, Oct 08 '22 at 09:55

How to sum up the power and time

0 Answers0