How to Convert by the Minute Data to Hourly Average Data

Converting minutes data to hourly data

Use Grouper for aggregate by hours with column Unique_id by sum:

df['datetime'] = pd.to_datetime(df['datetime'])
df = df.groupby([pd.Grouper(freq='H', key='datetime'), 'Unique_id']).sum().reset_index()
print (df)
             datetime  Unique_id  Value
0 2018-01-28 00:00:00     105714   1285
1 2018-01-28 00:00:00     206714    888
2 2018-01-28 23:00:00     105714    225
3 2018-01-28 23:00:00     206714    410

How to convert minute data to hourly data correctly in R?

You can shift the time back 60 seconds, do as.hourly, then shift the time forward 60 seconds. This maintains the groupings. You'll need to rename the columns too:

setNames(shift.time(to.hourly(shift.time(data, -60)), 60), c("Open", "High", "Low", "Close"))
#>                     Open High Low Close
#> 2020-01-01 01:00:00    1    3   1     3
#> 2020-01-01 02:00:00    4    6   4     6
#> 2020-01-01 03:00:00    7    9   7     9
#> 2020-01-01 04:00:00   10   12  10    12

Aggregate15 minute data to hourly

When working with time series, I suggest you work with xts package for this, and for example hourly.apply:

 library(xts)
 dat.xts <- xts(Total_Solar_Gesamt$TotalSolar_MW,
                as.POSIXct(otal_Solar_Gesamt$Timedate))
 hourly.apply(dat.xts,sum)

More general you can use period.apply which is (lapply equivalent) , for example to aggregate your data each 2 hours you can do the following:

 ends <- endpoints(zoo.data,'hours',2) 
 period.apply(dat.xts,ends ,sum)

Aggregate 10 minute interval data to hourly

This worked perfectly:
df.resample('60T').mean()

how to convert 15 mins data to hourly in pandas?

Use resample with closed='right'. But first we convert your Time column to datetime type:

df['Time'] = pd.to_datetime(df['Time'])
df.resample('H', on='Time', closed='right').mean().reset_index()

                 Time  Gen1  Gen2
0 2021-01-09 00:00:00  14.5  20.0
1 2021-01-09 01:00:00  50.0  41.0

To convert the Time column back to time format, use:

df['Time'] = df['Time'].dt.time

       Time  Gen1  Gen2
0  00:00:00  14.5  20.0
1  01:00:00  50.0  41.0