Teradata Package for Python Function Reference on VantageCloud Lake - element_state - 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.element_state = element_state(self, index)
- DESCRIPTION:
Check whether the element at the specified index in the array is initialized or not.
PARAMETERS:
index:
Required Argument.
Specifies the index of the array element to be checked.
Types: int
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: Check if element at index 2 in array column 'arr2' is initialized.
>>> res = df.assign(element_2_state = df.arr2.element_state(2))
>>> res
arr1 arr2 arr3 element_2_state
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 1
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 1
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') 1
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 1
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') 1
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 1
# Example 2: Check if element at index 6 in array column 'arr2' is initialized.
>>> res = df.assign(element_6_state = df.arr2.element_state(6))
>>> res
arr1 arr2 arr3 element_2_state
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') 0
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') 0
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') 0
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') 0
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') 0
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') 0
# Example 3: Create a array column with initialized elements with default_null=True
# and check the element state at index 6.
>>> sdf = df.assign(arr2=Array((df.id,20,30), atype=ARRAY_INTEGER('[7]' , default_null=True)))
>>> res = sdf.assign(element_6_state = sdf.arr2.element_state(6))
>>> res
arr1 arr2 arr3 element_6_state
id
1 (10,20,30,40,50) (1,20,30,NULL,NULL,NULL,NULL) ('ab','bc','cd','ab','ef') 1
4 (180,28,38,48,58) (4,20,30,NULL,NULL,NULL,NULL) ('mn','no',NULL,'op','pq') 1
2 (150,25,35,45,55) (2,20,30,NULL,NULL,NULL,NULL) ('xy','yz','za','ab','xy') 1
6 (16,261,36,46,56) (6,20,30,NULL,NULL,NULL,NULL) ('uv','xy','ab','xy','yz') 1
3 (12,22,320,42,52) (3,20,30,NULL,NULL,NULL,NULL) ('pq','ab','ab','st','tu') 1
5 (14,24,34,44,54) (5,20,30,NULL,NULL,NULL,NULL) ('ij','jk',NULL,'kl','lm') 1