More flexible time series binning/resampling

[wesm]

e.g. http://stackoverflow.com/questions/16319106/whats-the-equivalent-of-cut-qcut-for-pandas-date-fields

[jreback]

This was fixed by 3e4f839

In [13]: np.random.seed(1234)

In [14]: def randomDates(size, start=134e7, end=137e7):
    ...:     return np.array(np.random.randint(start, end, size), dtype='datetime64[s]')
    ...: 
    ...: df = pd.DataFrame({'ship' : randomDates(10), 'recd' : randomDates(10), 
    ...:                    'qty' : np.random.randint(0,10,10), 'price' : 100*np.random.random(10)})
    ...: df
    ...: 
Out[14]: 
       price  qty                recd                ship
0  29.072855    8 2013-05-30 14:54:15 2013-01-04 01:36:47
1  24.639444    0 2012-10-05 14:17:13 2013-03-17 11:32:35
2  73.828677    5 2012-11-15 17:17:14 2013-02-17 21:31:18
3  88.922613    0 2012-11-24 15:26:22 2013-03-10 15:13:57
4  98.713930    9 2013-02-21 16:04:59 2012-06-29 13:55:24
5  11.744339    6 2012-10-28 15:13:34 2012-11-01 07:27:48
6  39.378235    2 2013-02-22 12:34:52 2013-01-08 11:57:12
7  45.272981    0 2012-10-23 18:48:28 2013-03-30 08:14:49
8  53.814784    5 2012-08-03 14:54:18 2013-05-09 06:43:27
9  79.062210    2 2013-05-20 10:35:34 2012-08-21 14:56:49
In [16]: df.groupby([pd.cut(df['recd'],bins=pd.date_range('2011', freq='A', periods=3)), 
    ...:             pd.cut(df['qty'], bins=[0,1,5,10]),
    ...:             pd.qcut(df['price'],q=3)]).count()
    ...:             
Out[16]: 
                                                                     price  qty  recd  ship
recd                                       qty     price                                   
(2011-12-31 00:00:00, 2012-12-31 00:00:00] (0, 1]  [11.744, 39.378]    NaN  NaN   NaN   NaN
                                                   (39.378, 73.829]    NaN  NaN   NaN   NaN
                                                   (73.829, 98.714]    NaN  NaN   NaN   NaN
                                           (1, 5]  [11.744, 39.378]    NaN  NaN   NaN   NaN
                                                   (39.378, 73.829]    2.0  2.0   2.0   2.0
                                                   (73.829, 98.714]    NaN  NaN   NaN   NaN
                                           (5, 10] [11.744, 39.378]    1.0  1.0   1.0   1.0
                                                   (39.378, 73.829]    NaN  NaN   NaN   NaN
                                                   (73.829, 98.714]    NaN  NaN   NaN   NaN
(2012-12-31 00:00:00, 2013-12-31 00:00:00] (0, 1]  [11.744, 39.378]    NaN  NaN   NaN   NaN
                                                   (39.378, 73.829]    NaN  NaN   NaN   NaN
                                                   (73.829, 98.714]    NaN  NaN   NaN   NaN
                                           (1, 5]  [11.744, 39.378]    1.0  1.0   1.0   1.0
                                                   (39.378, 73.829]    NaN  NaN   NaN   NaN
                                                   (73.829, 98.714]    1.0  1.0   1.0   1.0
                                           (5, 10] [11.744, 39.378]    1.0  1.0   1.0   1.0
                                                   (39.378, 73.829]    NaN  NaN   NaN   NaN
                                                   (73.829, 98.714]    1.0  1.0   1.0   1.0