datatable.union()¶
Find the union 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 union operation on these sets.
The dt.union(*frames) operation is equivalent to
dt.unique(dt.rbind(*frames)).
Parameters¶
Frame | Frame | ...Input single-column frames.
FrameA single-column frame. The column stype is the smallest common
stype of columns in 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 |
Union of all the columns in a frame:
dt.union(*df)
| A | ||
|---|---|---|
| int32 | ||
| 0 | NA | |
| 1 | 1 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 5 |
Union of two frames:
dt.union(df["A"], df["C"])
| A | ||
|---|---|---|
| int32 | ||
| 0 | 1 | |
| 1 | 2 |
See Also¶
intersect()– calculate the set intersection of values in the frames.setdiff()– calculate the set difference between the frames.symdiff()– calculate the symmetric difference between the sets of values in the frames.unique()– find unique values in a frame.