verticapy.vDataFrame.explode_array#

vDataFrame.explode_array(index: str, column: str, prefix: str | None = 'col_', delimiter: bool | None = True) → vDataFrame#

Returns exploded vDataFrame of array-like columns in a vDataFrame.

New in version 10.0.0.

Parameters#

index: str: Index used to identify the Row.
column: str: The name of the array-like column to explode.
prefix: str, optional: The prefix for the column names of exploded values defaults to “col_”.
delimeter: str, optional: Specify if array-like data is separated by a comma defaults value is True.

Returns#

vDataFrame: horizontal exploded vDataFrame.

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.

For this example, let’s generate a dataset:

data = vp.vDataFrame(
    {
        "id": [1, 2, 3, 4],
        "values": [
            [70, 80, 90, 5],
            [47, 34, 93, 20, 13, 16],
            [1, 45, 56, 21, 10, 35, 56, 8, 39],
            [89],
        ]
    }
)

We can compute the exploded vDataFrame.

data.explode_array(index = "id", column = "values")

	123 id Integer 100%	...	123 col_0 Float(22) 100%	123 col_8 Float(22) 25%
1	1	...	70.0	[null]
2	3	...	1.0	39.0
3	2	...	47.0	[null]
4	4	...	89.0	[null]

Note

This function operates on various data types, including arrays and varchar representations of arrays. For arrays with elements separated by commas, as well as varchar representations of arrays with no delimiter (in which case you must specify delimiter as False).