Python Pandas: Aggregate data by hour and display it instead of the index

Question

I would like to aggregate some data by hour using pandas and display the date instead of an index.

The code I have right now is the following:

import pandas as pd
import numpy as np

dates = pd.date_range('1/1/2011', periods=20, freq='25min')
data = pd.Series(np.random.randint(100, size=20), index=dates)

result = data.groupby(data.index.hour).sum().reset_index(name='Sum')

print(result)

Which displays something along the lines of:

   index  Sum
0      0  131
1      1  116
2      2  180
3      3   62
4      4   95
5      5  107
6      6   89
7      7  169

The problem is that instead of index I want to display the date associated with that hour.

The result I'm trying to achieve is the following:

       index                Sum
0      2011-01-01 01:00:00  131
1      2011-01-01 02:00:00  116
2      2011-01-01 03:00:00  180
3      2011-01-01 04:00:00   62
4      2011-01-01 05:00:00   95
5      2011-01-01 06:00:00  107
6      2011-01-01 07:00:00   89
7      2011-01-01 08:00:00  169

Is there any way I can do that easily using pandas?

Answer 1

data.groupby(data.index.strftime('%Y-%m-%d %H:00:00')).sum().reset_index(name='Sum')

Answer 2

You could use resample .

data.resample('H').sum()

Output:

2011-01-01 00:00:00     84
2011-01-01 01:00:00    121
2011-01-01 02:00:00    160
2011-01-01 03:00:00     70
2011-01-01 04:00:00     88
2011-01-01 05:00:00    131
2011-01-01 06:00:00     56
2011-01-01 07:00:00    109
Freq: H, dtype: int32

Option #2

data.groupby(data.index.floor('H')).sum()

Output:

2011-01-01 00:00:00     84
2011-01-01 01:00:00    121
2011-01-01 02:00:00    160
2011-01-01 03:00:00     70
2011-01-01 04:00:00     88
2011-01-01 05:00:00    131
2011-01-01 06:00:00     56
2011-01-01 07:00:00    109
dtype: int32