pandas- changing the start and end date of resampled timeseries

You can create a new index with the desired start and end day/times, resample the time series data and aggregate by count, then set the index to the new index.

import pandas as pd

# create the index with the start and end times you want
t_index = pd.DatetimeIndex(start='2009-06-01', end='2009-06-30 23:00:00', freq='1h')

# create the data frame
df = pd.DataFrame([['2009-06-07 02:07:42'],
                   ['2009-06-11 17:25:28'],
                   ['2009-06-11 17:50:42'],
                   ['2009-06-11 17:59:18']], columns=['daytime'])
df['daytime'] = pd.to_datetime(df['daytime'])

# resample the data to 1 hour, aggregate by counts,
# then reset the index and fill the na's with 0
df2 = df.resample('1h', on='daytime').count().reindex(t_index).fillna(0)

UPDATE:

The original answer has since depreciated, and will require you to alter the first line of code as suggested by @toni-penya-alba to:

t_index = pd.DatetimeIndex(pd.date_range(start='2009-06-01', end='2009-06-30 23:00:00', freq="1h"))