I have a dateframe with, for every hour for each day, the amount of gas and electricity used:
elec gas day_of_week DuringBusinessHours
ts
2022-04-30 01:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 02:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 03:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 04:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 05:00:00+02:00 4.0000001192092896 0.0 5 False
2022-04-30 06:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 07:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 08:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 09:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 10:00:00+02:00 3.200000047683716 0.3000000119209289 5 False
2022-04-30 11:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 12:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 13:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 14:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 15:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 16:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 17:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 18:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 19:00:00+02:00 3.6000000834465027 0.0 5 False
2022-04-30 20:00:00+02:00 3.200000077486038 0.0 5 False
2022-04-30 21:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 22:00:00+02:00 3.200000047683716 0.0 5 False
2022-04-30 23:00:00+02:00 3.6000000834465027 0.0 5 False
2022-05-01 00:00:00+02:00 3.199999988079071 0.0 6 False
2022-05-01 01:00:00+02:00 3.200000047683716 0.0 6 False
2022-05-01 02:00:00+02:00 3.200000047683716 0.0 6 False
2022-05-01 03:00:00+02:00 3.6000000834465027 0.0 6 False
2022-05-01 04:00:00+02:00 3.6000000834465027 1.2000000476837158 6 False
2022-05-01 05:00:00+02:00 3.6000000834465027 0.4000000059604645 6 False
2022-05-01 06:00:00+02:00 3.6000000834465027 0.6000000238418579 6 False
For each week, I would like to get the lowest electricity value and display it in a new dataframe with the corresponding hour and day. But so far for each method I have used, it does not come up with the right minimum value. For example:
lowestUsage = BusinessUsageDf.groupby([pd.Grouper(level='ts', freq='W-SAT')])['elec'].min()
lowestUsage.head(5)
Gives:
ts
2022-04-23 00:00:00+02:00 3.200000047683716
2022-04-30 00:00:00+02:00 10.00000023841858
2022-05-07 00:00:00+02:00 10.400000095367432
2022-05-14 00:00:00+02:00 10.00000011920929
2022-05-21 00:00:00+02:00 10.00000023841858
Freq: W-SAT, Name: elektra, dtype: object
But the lowest value of the week between 04-30 and 05-07 is not 10.400.. because according to the data, this should be 3.100.. I also tried:
lowestUsageWeekDf = BusinessUsageDf.resample("W").min()
But this is neither giving the correct minimum value. What is going on in here?
