Suppose I have a pandas Series with daily observations:
pd_series = pd.Series(np.random.rand(26281), index = pd.date_range('2022-01-01', '2024-12-31', freq = 'H'))
pd_series
2022-01-01 00:00:00 0.933746
2022-01-01 01:00:00 0.588907
2022-01-01 02:00:00 0.229040
2022-01-01 03:00:00 0.557752
2022-01-01 04:00:00 0.798649
2024-12-30 20:00:00 0.314143
2024-12-30 21:00:00 0.670485
2024-12-30 22:00:00 0.300531
2024-12-30 23:00:00 0.075403
2024-12-31 00:00:00 0.716685
What I want is to replace every observation by the monthly average. I know that the average can be calculated as
pd_series.resample('MS').mean()
but how do I put the observations to the respective observations? I’d appreciate any help. Many thanks in advance.
>Solution :
Use Resampler.transform:
print (pd_series.resample('MS').transform('mean'))
2022-01-01 00:00:00 0.495015
2022-01-01 01:00:00 0.495015
2022-01-01 02:00:00 0.495015
2022-01-01 03:00:00 0.495015
2022-01-01 04:00:00 0.495015
2024-12-30 20:00:00 0.508646
2024-12-30 21:00:00 0.508646
2024-12-30 22:00:00 0.508646
2024-12-30 23:00:00 0.508646
2024-12-31 00:00:00 0.508646
Freq: H, Length: 26281, dtype: float64