How to get all the historical values for particular days/times in pandas dataframe?

I want to get all the values for (a) particular day-time. I need this to calculate some sort of historical mean/std/.., which is day- and time-dependent from a pandas data frame. I rather explain the problem in codes. Let's say I have this dataframe:

df_datetime = pd.date_range(start='2010-01-01', end='2020-12-31', freq='30min')  df_ts = pd.DataFrame(data=np.random.random((df_datetime.shape)), index=df_datetime, columns=['Value'])  print(df_ts)                            Value  2010-01-01 00:00:00  0.148690  2010-01-01 00:30:00  0.639023  2010-01-01 01:00:00  0.339820  2010-01-01 01:30:00  0.226052  2010-01-01 02:00:00  0.893710  ...                       ...  2020-12-30 22:00:00  0.473275  2020-12-30 22:30:00  0.183648  2020-12-30 23:00:00  0.077264  2020-12-30 23:30:00  0.085483  2020-12-31 00:00:00  0.311474    [192817 rows x 1 columns]  

Now I want all the values in df for, let's say, this day-time: XXXX-12-30 22:00:00. XXXX mean all years included. The way I do it is like this:

df_sample = df_ts.loc[(df_ts.index.month==12) & (df_ts.index.day==30) & (df_ts.index.hour==22) & (df_ts.index.minute==0)]  print(df_sample)                            Value  2010-12-30 22:00:00  0.073103  2011-12-30 22:00:00  0.525378  2012-12-30 22:00:00  0.247066  2013-12-30 22:00:00  0.192340  2014-12-30 22:00:00  0.968341  2015-12-30 22:00:00  0.458732  2016-12-30 22:00:00  0.709913  2017-12-30 22:00:00  0.706581  2018-12-30 22:00:00  0.994208  2019-12-30 22:00:00  0.172340  2020-12-30 22:00:00  0.473275  

which works fine for a single day-time, but I don't know an elegant way (not for loop) of doing this for several day-times, let's say for example:

[`XXXX-12-30 22:00:00`, `XXXX-12-30 22:30:00`, `XXXX-12-30 23:00:00`]  

https://stackoverflow.com/questions/66146215/how-to-get-all-the-historical-values-for-particular-days-times-in-pandas-datafra February 11, 2021 at 06:45AM