[FIXED] Integration of pandas timeframe

Issue

I want to integrate the following dataframe, such that I have the integrated value for every hour. I have roughly a 10s sampling rate, but if it is necissary to have an even timeinterval, I guess I can just use df.resample().

Timestamp                    Power [W]
2022-05-05 06:00:05+02:00    2.0
2022-05-05 06:00:15+02:00    1.2
2022-05-05 06:00:25+02:00    0.3
2022-05-05 06:00:35+02:00    4.3
2022-05-05 06:00:45+02:00    1.1
                            ... 
2022-05-06 20:59:19+02:00    1.4
2022-05-06 20:59:29+02:00    2.0
2022-05-06 20:59:39+02:00    4.1
2022-05-06 20:59:49+02:00    1.3
2022-05-06 20:59:59+02:00    0.8

So I want to be able to integrate over both hours and days, so my output could look like:

Timestamp                    Energy [Wh]
2022-05-05 07:00:00+02:00    some values
2022-05-05 08:00:00+02:00    .
2022-05-05 09:00:00+02:00    .
2022-05-05 10:00:00+02:00    .
2022-05-05 11:00:00+02:00    
                            ... 
2022-05-06 20:00:00+02:00    
2022-05-06 21:00:00+02:00    

(hour 07:00 is to include values between 06:00-07:00, and so on...)

and

Timestamp      Energy [Wh]
2022-05-05     .
2022-05-06     .

So how do I achieve this? I was thinking I could use scipy.integrate, but my outputs look a bit weird.

Thank you.

Solution

You could create a new column representing your Timestamp truncated to hours:

df['Timestamp_hour'] = df['Timestamp'].dt.floor('h')

Please note that in that case, the rows between hour 6.00 to hour 6.59 will be included into the 6 hour and not the 7 one.

Then you can group your rows by your new column before applying your integration computation:

df_integrated_hour = (
    df
    .groupby('Timestamp_hour')
    .agg({
        'Power': YOUR_INTEGRATION_FUNCTION
    })
    .rename(columns={'Power': 'Energy'})
    .reset_index()
)

Hope this will help you

Answered By - UPetit