Resampling with custom periods

Question

Is there a \'cookbook\' way of resampling a DataFrame with (semi)irregular periods?

I have a dataset at a daily interval and want it to resample to what sometimes (in s

Answer 1

Using HYRY's data and solution up to the computation of the d variable, we can also do the following in pandas 0.11-dev or later (regardless of numpy version):

In [18]: from datetime import timedelta

In [23]: pd.Series([ timedelta(int(i)) for i in d ])
Out[23]: 
0             00:00:00
1     1 days, 00:00:00
2     2 days, 00:00:00
3     3 days, 00:00:00
4     4 days, 00:00:00
5     5 days, 00:00:00
6     6 days, 00:00:00
7     7 days, 00:00:00
8     8 days, 00:00:00
9     9 days, 00:00:00
10            00:00:00

47    6 days, 00:00:00
48    7 days, 00:00:00
49    8 days, 00:00:00
50    9 days, 00:00:00
Length: 51, dtype: timedelta64[ns]

The date is constructed similary to above

date = pd.Series(df.index) - pd.Series([ timedelta(int(i)) for i in d ])
df.groupby(date.values).mean()