Question :
Resample hourly TimeSeries with certain starting hour
I want to resample a TimeSeries in daily (exactly 24 hours) frequence starting at a certain hour.
Like:
index = date_range(datetime(2012,1,1,17), freq='H', periods=60)
ts = Series(data=[1]*60, index=index)
ts.resample(rule='D', how='sum', closed='left', label='left')
Result i get:
2012-01-01 7
2012-01-02 24
2012-01-03 24
2012-01-04 5
Freq: D
Result i wish:
2012-01-01 17:00:00 24
2012-01-02 17:00:00 24
2012-01-03 17:00:00 12
Freq: D
Some weeks ago you could pass '24H' to the freq argument and it worked totally fine.
But now it combines '24H' to '1D'.
Was I using a bug with '24H' which is fixed now?
And how can i get the wished result in a efficient and pythonic (or pandas) way back?
versions:
- python 2.7.3
- pandas 0.9.0rc1 (but doesn’t work in 0.8.1, too)
- numpy 1.6.1
Answer #1:
Resample has an base argument which covers this case:
ts.resample(rule='24H', closed='left', label='left', base=17).sum()
Output:
2012-01-01 17:00:00 24
2012-01-02 17:00:00 24
2012-01-03 17:00:00 12
Freq: 24H
Answer #2:
2020 Update: for dataframes
Use the base keyword as referred in the doc:
Code example:
df.resample(pd.Timedelta('24 hours'), # or '24H'
base=17 # <-- ADD THIS
).sum()
