verticapy.vDataFrame.numcol#

vDataFrame.numcol(exclude_columns: str | list[str] | None = None) → list#

Returns a list of names of the numerical vDataColumns in the vDataFrame.

Parameters#

exclude_columns: SQLColumns, optional: List of the vDataColumns names to exclude from the final list.

Returns#

List: List of numerical vDataColumns names.

Examples#

We import 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’s create a small dataset:

data = vp.vDataFrame(
    {
        "empid": ['1', '2', '3', '4'],
        "weight": [140.5, 175, 156.5, 178],
        "height": [168.5, 175, 178.5, 170],
        "emp_cat":[933, 945, 723, 799],
    }
)
data

	Abc empid Varchar(1) 100%	...	123 weight Numeric(21) 100%	123 emp_cat Integer 100%
1	1	...	140.5	933
2	2	...	175.0	945
3	3	...	156.5	723
4	4	...	178.0	799

Let’s retrieve the numeric type vcolumns in the dataset.

data.numcol()
Out[2]: ['"weight"', '"height"', '"emp_cat"']