datatable.shift()

datatable.

shift

(

col,

n=1

)

sourcetests

Produce a column obtained from col shifting it n rows forward.

The shift amount, n, can be both positive and negative. If positive, a “lag” column is created, if negative it will be a “lead” column.

The shifted column will have the same number of rows as the original column, with n observations in the beginning becoming missing, and n observations at the end discarded.

This function is group-aware, i.e. in the presence of a groupby it will perform the shift separately within each group.

Examples

from datatable import dt, f, by DT = dt.Frame({"object": [1, 1, 1, 2, 2], "period": [1, 2, 4, 4, 23], "value": [24, 67, 89, 5, 23]}) DT

	object	period	value
	int32	int32	int32
0	1	1	24
1	1	2	67
2	1	4	89
3	2	4	5
4	2	23	23

5 rows × 3 columns

Shift forward - Create a “lag” column:

DT[:, dt.shift(f.period, n = 3)]

	period
	int32
0	NA
1	NA
2	NA
3	1
4	2

5 rows × 1 column

Shift backwards - Create “lead” columns:

DT[:, dt.shift(f[:], n = -3)]

	object	period	value
	int32	int32	int32
0	2	4	5
1	2	23	23
2	NA	NA	NA
3	NA	NA	NA
4	NA	NA	NA

5 rows × 3 columns

Shift in the presence of by():

DT[:, f[:].extend({"prev_value": dt.shift(f.value)}), by("object")]

	object	period	value	prev_value
	int32	int32	int32	int32
0	1	1	24	NA
1	1	2	67	24
2	1	4	89	67
3	2	4	5	NA
4	2	23	23	5

5 rows × 4 columns