verticapy.vDataFrame.append#

Merges the vDataFrame with another vDataFrame or an input relation, and returns a new vDataFrame.

Warning

Appending datasets can potentially increase the structural weight; exercise caution when performing this operation.

Parameters#

input_relation: SQLRelation: Relation to merge with.
expr1: SQLExpression, optional: List of pure-SQL expressions from the current vDataFrame to use during merging. For example, CASE WHEN "column" > 3 THEN 2 ELSE NULL END and POWER("column", 2) will work. If empty, all vDataFrame vDataColumns are used. Aliases are recommended to avoid auto-naming.
expr2: SQLExpression, optional: List of pure-SQL expressions from the input relation to use during the merging. For example, CASE WHEN "column" > 3 THEN 2 ELSE NULL END and POWER("column", 2) will work. If empty, all input relation columns are used. Aliases are recommended to avoid auto-naming.
union_all: bool, optional: If set to True, the vDataFrame is merged with the input relation using an ‘UNION ALL’ instead of an ‘UNION’.

Returns#

vDataFrame: vDataFrame of the Union

Examples#

Let’s begin by importing VerticaPy.

import verticapy as vp

Hint

By assigning an alias to verticapy, we mitigate the risk of code collisions with other libraries. This precaution is necessary because verticapy uses commonly known function names like “average” and “median”, which can potentially lead to naming conflicts. The use of an alias ensures that the functions from verticapy are used as intended without interfering with functions from other libraries.

Let us create two vDataFrame which we can merge for this example:

vdf = vp.vDataFrame(
    {
        "score": [12, 11, 13],
        "cat": ['A', 'B', 'A'],
    }
)


vdf_2 = vp.vDataFrame(
    {
        "score": [11, 1, 23],
        "cat": ['A', 'B', 'B'],
    }
)

We can conveniently append the the first vDataFrame with the second one:

vdf.append(vdf_2)

	123 score Integer 100%	Abc cat Varchar(1) 100%
1	12	A
2	11	B
3	13	A
4	11	A
5	1	B
6	23	B

We can also apply some SQL expressions on the append using expr1 and expr2. Let us try to limit the maximum value of the second vDataFrame to 20.

vdf.append(
    vdf_2,
    expr1 = [
        'CASE WHEN "score" > 20 THEN 20 ELSE "score" END',
        '"cat"',
    ],
)

	123 score Integer 100%	Abc cat Varchar(1) 100%
1	12	A
2	11	B
3	13	A
4	11	A
5	1	B
6	20	B

Note

VerticaPy offers the flexibility to use UNION ALL or simple UNION based on your specific use case. The former includes duplicates, while the latter handles them. Refer to union_all for more information.