[FIXED] How to add values occurring between 2 consecutive hours?

Issue

I have a df as follows:

dates   values
2020-01-01 00:15:00 87.321
2020-01-01 00:30:00 87.818
2020-01-01 00:45:00 88.514
2020-01-01 01:00:00 89.608
2020-01-01 01:15:00 90.802
2020-01-01 01:30:00 91.896
2020-01-01 01:45:00 92.393
2020-01-01 02:00:00 91.995
2020-01-01 02:15:00 90.504
2020-01-01 02:30:00 88.216
2020-01-01 02:45:00 85.929
2020-01-01 03:00:00 84.238

I want to just keep hourly values when the minute is 00 and the values occurring before it must be added.

Example: For finding the value at 2020-01-01 01:00:00, the values from 2020-01-01 00:15:00 to 2020-01-01 01:00:00 should be added (87.321+87.818+88.514+59.608 = 353.261). Similarly, for finding the value at 2020-01-01 02:00:00, the values from 2020-01-01 01:15:00 to 2020-01-01 02:00:00 should be added (90.802+91.896+92.393+91.995 = 348.887)

Desired output

 dates  values
 2020-01-01 01:00:00    353.261
 2020-01-01 02:00:00    348.887
 2020-01-01 03:00:00    333.67

I used df['dates'].dt.minute.eq(0) to obtain the boolean masking, but I am unable to find a way to add them.

Solution

hourly = df.set_index('dates') \  # Set the dates as index
           .resample('1H', closed='right', label='right') \  # Resample, so that you have one value for each hour
           .sum()  # Set the sum of values as new value

hourly = hourly.reset_index()  # If you want to have the dates as column again

Answered By - flurble