Teradata Package for Python Function Reference | 20.00 - array_sort - 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 - 20.00
- Deployment
- VantageCloud
- VantageCore
- Edition
- VMware
- Enterprise
- IntelliFlex
- 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_Enterprise_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.array_sort = array_sort(self, elements_order='ASC', nulls_order='LAST')
- DESCRIPTION:
Sort the elements of the array in ascending or descending order.
PARAMETERS:
elements_order:
Optional Argument.
Specifies the order in which the elements to be sorted.
Permitted Values: ASC, DESC
Default Value: 'ASC'
Types: str
nulls_order:
Optional Argument.
Specifies whether NULL values should appear first or last in the sorted array.
Permitted Values: 'FIRST', 'LAST'
Default Value: 'LAST'
Types: str
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: Sort elements of array column 'arr2' in ascending order.
>>> res = df.assign(sorted_arr = df.arr2.array_sort())
>>> res
arr1 arr2 arr3 sorted_arr
id
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') (24,26,180,NULL,NULL)
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') (26,28,50,90,95)
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') (22,23,25,140,200)
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') (21,23,40,200,215)
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') (27,30,250,NULL,NULL)
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') (25,29,46,160,170)
# Example 2: Sort elements of array column 'arr2' in descending order with NULLs first.
>>> res = df.assign(sorted_arr = df.arr2.array_sort(elements_order='DESC', nulls_order='FIRST'))
>>> res
arr1 arr2 arr3 sorted_arr
id
1 (10,20,30,40,50) (23,200,215,40,21) ('ab','bc','cd','ab','ef') (215,200,40,23,21)
3 (12,22,320,42,52) (25,22,140,200,23) ('pq','ab','ab','st','tu') (200,140,25,23,22)
4 (180,28,38,48,58) (30,NULL,NULL,250,27) ('mn','no',NULL,'op','pq') (NULL,NULL,250,30,27)
2 (150,25,35,45,55) (28,50,95,90,26) ('xy','yz','za','ab','xy') (95,90,50,28,26)
5 (14,24,34,44,54) (26,NULL,NULL,180,24) ('ij','jk',NULL,'kl','lm') (NULL,NULL,180,26,24)
6 (16,261,36,46,56) (29,170,160,46,25) ('uv','xy','ab','xy','yz') (170,160,46,29,25)