datatable.rbind()

datatable.

rbind

(

*frames

,

force=False

,

bynames=True

)

sourcetests

Produce a new frame by appending rows of several frames.

This function is equivalent to:

dt.Frame().rbind(*frames, force=force, by_names=by_names)

Parameters

frames

Frame | List[Frame] | None

force

bool

If True, then the frames are allowed to have mismatching set of columns (either different counts or different names). Any gaps in the data will be filled with NAs.

In addition, when this parameter is True, rbind will no longer produce an error when combining columns of unrelated types. Instead, both columns will be converted into strings.

bynames

bool

Whether to match column names when rbinding.

return

Frame

A new frame that is created by appending rows from frames.

See also

• cbind() – function for col-binding several frames.

• dt.Frame.rbind() – Frame method for rbinding some frames to another.

Examples

from datatable import dt DT1 = dt.Frame({"Weight": [5, 4, 6], "Height": [170, 172, 180]}) DT1

	Weight	Height
	int32	int32
0	5	170
1	4	172
2	6	180

3 rows × 2 columns

DT2 = dt.Frame({"Height": [180, 181, 169], "Weight": [4, 4, 5]}) DT2

	Weight	Height
	int32	int32
0	4	180
1	4	181
2	5	169

3 rows × 2 columns

dt.rbind(DT1, DT2)

	Weight	Height
	int32	int32
0	5	170
1	4	172
2	6	180
3	4	180
4	4	181
5	5	169

6 rows × 2 columns

rbind() by default combines frames by names. The frames can also be bound by column position by setting the bynames parameter to False:

dt.rbind(DT1, DT2, bynames = False)

	Weight	Height
	int32	int32
0	5	170
1	4	172
2	6	180
3	180	4
4	181	4
5	169	5

6 rows × 2 columns

If the number of columns are not equal or the column names are different, you can force the row binding by setting the force parameter to True:

DT2["Age"] = dt.Frame([25, 50, 67]) DT2

	Weight	Height	Age
	int32	int32	int32
0	4	180	25
1	4	181	50
2	5	169	67

3 rows × 3 columns

dt.rbind(DT1, DT2, force = True)

	Weight	Height	Age
	int32	int32	int32
0	5	170	NA
1	4	172	NA
2	6	180	NA
3	4	180	25
4	4	181	50
5	5	169	67

6 rows × 3 columns