### 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()
```