datatable.symdiff()¶
Find the symmetric difference between the sets of values in all frames.
Each frame should have only a single column or be empty. The values in each frame will be treated as a set, and this function will perform the symmetric difference operation on these sets.
The symmetric difference of two frames are those values that are present in either of the frames, but not in the both. The symmetric difference of more than two frames are those values that are present in an odd number of frames.
Parameters¶
Frame | Frame | ...Input single-column frames.
FrameA single-column frame. The column stype is the smallest common
stype of columns from the frames.
ValueError | NotImplementedErrorraised when one of the input frames has more than one column. |
|
raised when one of the columns has stype |
Examples¶
from datatable import dt
df = dt.Frame({'A': [1, 1, 2, 1, 2],
'B': [None, 2, 3, 4, 5],
'C': [1, 2, 1, 1, 2]})
df
| A | B | C | ||
|---|---|---|---|---|
| int32 | int32 | int32 | ||
| 0 | 1 | NA | 1 | |
| 1 | 1 | 2 | 2 | |
| 2 | 2 | 3 | 1 | |
| 3 | 1 | 4 | 1 | |
| 4 | 2 | 5 | 2 |
Symmetric difference of all the columns in the entire frame; Note that each column is treated as a separate frame:
dt.symdiff(*df)
| A | ||
|---|---|---|
| int32 | ||
| 0 | NA | |
| 1 | 2 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 5 |
Symmetric difference between two frames:
dt.symdiff(df["A"], df["B"])
| A | ||
|---|---|---|
| int32 | ||
| 0 | NA | |
| 1 | 1 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 5 |
See Also¶
intersect()– calculate the set intersection of values in the frames.setdiff()– calculate the set difference between the frames.union()– calculate the union of values in the frames.unique()– find unique values in a frame.