How do i slice pandas Series with DatetimeIndex and put it in a DataFrame by rows?

Question

I have pandas Series object with DatetimeIndex:

2016-01-04 00:00:00    11.6
2016-01-04 01:00:00    11.7
2016-01-04 02:00:00    17.1
2016-01-04 03:00:00    36.5
2016-01-04 04:00:00    19.0
2016-01-04 05:00:00     7.5
2016-01-04 06:00:00    18.7
2016-01-04 07:00:00    14.5
2016-01-04 08:00:00     6.5
2016-01-04 09:00:00    41.9
2016-01-04 10:00:00    37.3
2016-01-04 11:00:00    30.3
2016-01-04 12:00:00    38.4
2016-01-04 13:00:00    26.0
2016-01-04 14:00:00    31.0
2016-01-04 15:00:00    32.3
2016-01-04 16:00:00    29.4
2016-01-04 17:00:00    43.5
2016-01-04 18:00:00    26.9
2016-01-04 19:00:00    20.4
2016-01-04 20:00:00    16.5
2016-01-04 21:00:00    10.9
2016-01-04 22:00:00    12.8
2016-01-04 23:00:00    16.4
2016-01-05 00:00:00    10.1
2016-01-05 01:00:00     9.4
2016-01-05 02:00:00    12.0
2016-01-05 03:00:00     8.6
2016-01-05 04:00:00    16.9
2016-01-05 05:00:00     8.4
...

How i can slice this series by dates and put it in a dates/hours pandas Dataframes like this:

              00   01   02   03   04 ...   22   23    
2016-01-04  11.6  1.7 17.1 36.5 19.0 ... 12.8 16.4
2016-01-05  10.1  9.4 12.0  8.6 16.9 ... 12.8 16.4
...

PS: Sorry my English

Answer 1

First convert your series to a dataframe with to_frame , then extract the hours and date with s.index.strftime('%H') and index.date . Finally pivot on these column to convert to "wide" format:

df = s.to_frame()
df['hour'] = df.index.strftime('%H')
df['date'] = df.index.date
df2 = df.pivot(columns='hour', index='date')