verticapy.vDataColumn.rename#

vDataColumn.rename(new_name: str) → vDataFrame#

Renames the vDataColumn by dropping the current vDataColumn and creating a copy with the specified name.

Warning

SQL code generation will be slower if the vDataFrame has been transformed multiple times, so it’s better practice to use this method when first preparing your data.

Parameters#

new_name: str: The new vDataColumn alias.

Returns#

vDataFrame: self._parent

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 a dummy dataset and rename one of its columns:

vdf = vp.vDataFrame(
    {
        "val" : [0, 10, 20],
        "cat": ['a', 'b', 'c'],
    },
)

	123 val Integer 100%	Abc cat Varchar(1) 100%
1	0	a
2	10	b
3	20	c

We can copy the “val” column, and name the new column:

vdf["val"].rename("value")

	Abc cat Varchar(1) 100%	123 value Integer 100%
1	a	0
2	b	10
3	c	20