ENH: enable pd.cut to handle i8 convertibles

[jreback]

so this should work for timedeltas AND datetimes.

Should be straight forward. detect an i8 convertible. turn into i8. do the cut. turn back to the original dtype.

In [15]: s = Series(pd.to_timedelta(np.random.randint(0,100,size=10),unit='ms')).sort_values()

In [16]: s
Out[16]:
3   00:00:00.005000
5   00:00:00.007000
7   00:00:00.010000
4   00:00:00.017000
9   00:00:00.023000
1   00:00:00.043000
0   00:00:00.045000
6   00:00:00.047000
8   00:00:00.065000
2   00:00:00.090000
dtype: timedelta64[ns]

In [18]: pd.cut(s, 5)
TypeError: unsupported operand type(s) for +: 'Timedelta' and 'float'

# works when converted
In [17]: pd.cut(s.astype('timedelta64[ms]'), 5)
Out[17]:
3    (4.915, 22]
5    (4.915, 22]
7    (4.915, 22]
4    (4.915, 22]
9       (22, 39]
1       (39, 56]
0       (39, 56]
6       (39, 56]
8       (56, 73]
2       (73, 90]
dtype: category
Categories (5, object): [(4.915, 22] < (22, 39] < (39, 56] < (56, 73] < (73, 90]]

[aileronajay]

@jreback in the above example should the return type of the final object be 'timedelta64'? (the datatype of the original input)

[jreback]

yes (it should be original dtype)

[aileronajay]

@jreback Does it currently return strings? I got the below output by printing typeof over the members of category object returned
Categories (5, object): [(2.915, 20] < (20, 37] < (37, 54] < (54, 71] < (71, 88]]
(2.915, 20] <type 'str'>
(2.915, 20] <type 'str'>
(37, 54] <type 'str'>
(37, 54] <type 'str'>
(37, 54] <type 'str'>
(37, 54] <type 'str'>
(54, 71] <type 'str'>
(54, 71] <type 'str'>
(71, 88] <type 'str'>
(71, 88] <type 'str'>

[jreback]

yes it returns strings
we don't have an interval type currently

[aileronajay]

@jreback i am bit confused now, as part of this enhancement we first need convert to a dtype which cut can handle (timedelta64[ms]) and then return the type (timedelta64[ns]) from which we originally started. Though the objects returned will still be strings but they will be strings composed of object types that we initially passed to cut (timedelta64[ns])?

[jreback]

yes this is a bit tricky. I think you:

• convert to i8
• do the binning
• construct the labels based on the bins / dtype
• stringify them

[aileronajay]

@jreback thanks, this is what i was thinking