Teradata Package for Python Function Reference on VantageCloud Lake - get - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.11
- Published
- August 2026
- ft:locale
- en-US
- ft:lastEdition
- 2026-08-13
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.get = get(self, index)
- DESCRIPTION:
Get an element from the array at the specified index.
PARAMETERS:
index:
Required Argument.
Specifies the index of the element to retrieve from the array.
Types: int OR ColumnExpression
RETURNS:
ColumnExpression
EXAMPLES:
>>> from teradataml import *
>>> load_example_data("array", "array_table")
# Create a DataFrame on 'array_table'.
>>> df = DataFrame("array_table")
>>> df
arr1 arr2 arr3
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef')
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq')
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy')
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz')
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu')
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm')
# Example 1: Get the element at index 3 from array column 'arr1'.
>>> res = df.assign(element_3 = df.arr1.get(3))
>>> res
arr1 arr2 arr3 element_3
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 30
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 38
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') 35
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 36
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') 320
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 34
# Example 2: Get the element at index specified by column 'col' from array column 'arr1'.
>>> df2 = df.assign(col=3)
>>> res = df2.assign(element_id=df2.arr1.get(df2.col))
>>> res
arr1 arr2 arr3 col element_id
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 3 30
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 3 38
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') 3 35
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 3 36
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') 3 320
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 3 34